Electricity: Agent-Based Computational Economics (Tesfatsion)

Agent-Based Computational Economics (ACE)
Research Area: Restructured Electricity Markets

Last Updated: 9 June 2009

Site Maintained By:
Leigh Tesfatsion
Professor of Economics and Mathematics
Iowa State University
Ames, IA 50011-1070
http://www.econ.iastate.edu/tesfatsi/
tesfatsi AT iastate.edu

General Resources on Electricity Restructuring
Electricity Market Open-Source Software
ACE Website

Table of Contents

Introduction
Basic Issues
Surveys
Other Readings
Software, Toolkits, and Demos
Resource Sites and Groups
Individual Researchers

Introduction

The U.S. electricity industry is currently undergoing substantial changes in both its structure (ownership and technology aspects) and its architecture (operational and oversight aspects). These changes involve attempts to move the industry away from highly regulated markets with administered cost-based pricing and towards competitive markets in which prices more fully reflect supply and demand forces. The goal of these changes is to provide industry participants with better incentives to control costs and introduce innovations. The process of enacting and implementing policies and laws to bring about these changes has come to be known as restructuring.
This restructuring process has been controversial. The meltdown in the restructured California wholesale power market in the summer of 2000 has shown what can happen when market designs are implemented without sufficient pre-testing. Following the California crisis, many energy researchers have eloquently argued the need to combine sound physical understanding of electric power and transmission grid operation with economic analysis of incentives in order to develop electricity markets with good real-world performance characteristics.
The goal of this resource site is to encourage the study of restructured electricity systems from a perspective that adequately addresses both economic and engineering concerns. In line with this goal, stress is placed on research making use of powerful new agent-based computational modeling tools. These tools permit restructured electricity systems to be modeled as commercial networks of strategically interacting traders and regulatory agencies learning to operate through time over realistically rendered transmission grids.
A comprehensive repository of general resources related to electricity restructuring is also available.

Basic Issues

What form should electricity restructuring take? To what extent should regions be permitted to design their own systems rather than adhere to a centralized design -- e.g., FERC's wholesale power market platform (aka standard market design) in the U.S.?
How should transmission grid constraints and congestion be properly accounted for in electricity market design? What role might "financial transmission rights" (PTP, flowgate, ...) play?
How important is demand responsiveness for the effective functioning of electricity markets?
To what extent can strategic participants "game the system" under currently proposed/implemented electricity market designs?
To what extent should independent system operators and other regulatory agencies intervene in electricity markets in an attempt to mitigate market power and inefficiency problems?
Are the goals of "market efficiency" and "reliable flow of electricity to consumers" necessarily at odds with each other?
How can electricity markets be protected against hackers, insider trading, and other illegal disruptive activities as these markets come to depend more heavily on Internet transactions?

Surveys

Massoud Amin, Restructuring the Electric Enterprise: Simulating the Evolution of the Electric Power Industry with Intelligent Adaptive Agents (pdf,450K), Chapter 3 in Market Analysis and Resource Management, edited by A. Faruqui and K. Eakin, Kluwer Publishers, March 2002.
Abstract: The author discusses the development of the Simulator for Electrical Power Industry Agents (SEPIA) sponsored by the Electric Power Research Institute (EPRI). SEPIA uses autonomous adaptive agents to represent possible industrial components (e.g., generation units, transmission system, load) and the corporate entities (e.g., GenCos and LoadCos) that own these components. Objectives are: (1) to develop a high-fidelity scenario-free modeling and optimization tool to use for gaining strategic insight into the operation of the deregulated power industry; (2) to show how networks of communicating and cooperating intelligent software agents can be used to adaptively manage complex distributed systems; and (3) to investigate how collections of agents (agencies) can be used to buy and sell electricity and participate in the electronic market place and, ultimately, to create self-optimizing and self-healing capabilities for the electric power grid and the interconnected critical infrastructures.

Vladimir S. Koritarov, "Real-World Market Representation with Agents" (pdf,2MB), IEEE Power and Energy Magazine, 2004, pp. 39-46
Abstract: "The electric power industry around the world is undergoing an extensive restructuring process. In many countries the traditional vertically integrated power utilities are being unbundled and replaced with a number of separate business entities dealing with the generation, transmission, and distribution of electric power. One of the most significant features of the restructuring process is the introduction of electricity markets, aimed at providing competitive electricity service to consumers. As power markets are relatively new and still continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of electricity markets over time and how market participants may act and react to the changing economic, financial, and regulatory environments in which they operate. (This paper argues that a) new and rather promising approach is to model the electricity market as a complex adaptive system using an agent-based modeling and simulation approach."

Frank Sensfuß, Mario Ragwitz, Massimo Genoese, and Dominik Möst, Agent-Based Simulation of Electricity Markets: A Literature Review (pdf,485K), Working Paper Sustainability and Innovation, No. S 5/2007, Fraunhofer Institute Systems and Innovation Research.
Abstract: "Liberalization, climate policy, and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players, and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets."

Anke Weidlich and Daniel Veit, “A Critical Survey of Agent-Based Wholesale Electricity Market Models” (doi/eneco), Energy Economics, in press, 2008.
Abstract: "The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed."

Steve Widergren, Junjie Sun, and Leigh Tesfatsion, "Market Design Test Environments" (pdf,136K), Proceedings, IEEE Power Engineering Society General Meeting, Montreal, June 2006.
Abstract: "Power industry restructuring continues to evolve at multiple levels of system operations. At the bulk electricity level, several organizations charged with regional system operation are implementing versions of a Wholesale Power Market Platform (WPMP) in response to U.S. Federal Energy Regulatory Commission initiatives. Recently the Energy Policy Act of 2005 and several regional initiatives have been pressing the integration of demand response as a resource for system operations. These policy and regulatory pressures are driving the exploration of new market designs at the wholesale and retail levels. The complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance demand a flexible computational environment where designs can be tested and sensitivities to power system and market rule changes can be explored. This paper discusses the use of agent-based computational methods for the study of electricity markets at the wholesale and retail levels, and explores distinctions in problem formulation between these levels."

Shun-Kun Yu and Jia-Hai Yuan, "Agent-Based Computational Economics: Methodology and Its Application in Electricity Market Research" (pdf,205K), Proceedings, The 7th International Power Engineering Conference (IPEC), 2005.
Abstract: "The restructured electricity market is a complex adaptive system and world-wide experiences show that market design is a complicated task. Recently, under the paradigm of agent-based computational economics (ACE), a new research focus is forming and a large number of literatures are springing up, but there is still no discussion on ACE’s theoretical value and insufficiency in the research of electricity market in a hierarchy of methodologies. Therefore the authors' research is an attempt in this aspect. By means of analyzing the evolution of economics methodology from mathematical deduction to simulation induction, and their inherent relevance, the unique superiority of ACE on the level of methodology is expounded. A further selective survey on existing literatures shows that with the ACE model the marketization process can be understood clearly in deeper level and wider scope. Finally, to give a reference to theoretical progress, the prospective application of ACE, especially its potential in China’s electric sector restructuring,is discussed."

Other Readings

Anthony J. Bagnall and George D. Smith, "A Multi-Agent Model of the UK Market in Electricity Generation" (pdf,678K), Draft, March 16, 2005.
Abstract: This paper describes an agent-based computational economics approach for studying the effect of alternative structures and mechanisms on behavior in a simulated model of the pre-NETA England and Wales electricity market. Agents learn using hierarchical learning classifier systems. The authors test to see whether the agents: (a) are able to learn optimal strategies when competing against non-adaptive agents; (b) are able to learn strategies observable in the real world when competing against other adaptive agents; and (c) are able to evolve cooperative behaviors without explicit communication.
John Bower and Derek Bunn, "Experimental Analysis of the Efficiency of Uniform-Price versus Discriminatory Auctions in the England and Wales Electricity Market", Journal of Economic Dynamics and Control 25, March 2001, pages 561-592.
Abstract: The authors develop an agent-based computational model of the wholesale market for electricity in England and Wales that allows them to compare market prices and the bidding strategies of individual generators under different trading arrangements. The authors use this framework to address several restructing issues under debate for the England and Wales market -- in particular, the efficacy of using a uniform-price versus a discriminatory-price auction format.
Timothy J. Brennan, Karen L. Palmer, and Salvador A. Martinez, Alternating Currents: Electricity Markets and Public Policy, Resources for the Future, Washington, D.C., 226 pp., 2002.
Derek Bunn and Fernando Oliveira, "Agent-Based Simulation: An Application to the New Electricity Trading Arrangements of England and Wales", IEEE Transactions on Evolutionary Computation, Volume 5, Number 5, October 2001, 493-503.
Abstract: This paper presents a large-scale application of a multi-agent evolutonary model of the proposed New Electricity Trading Arrangements (NETA) in the United Kingdom. The model is a detailed plant-by-plant model with an active specification of the demand side of the market. The model was able to provide pricing and strategic insights into the workings of the NETA prior to its actual introduction.
Derek Bunn and Fernando Oliveira, "Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation" (pdf,505K), Working Paper, August 2004, to appear in the Annals of Operations Research.
Abstract: The authors use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices.

Jack Casazza and Frank Delea, Understanding Electric Power Systems: An Overview of the Technology and the Marketplace, IEEE Press/Wiley-Interscience, Piscataway, NJ, 2003.
Abstract: "(This book) bridges the gap between technology, government policy, economics and finance, business arrangements, and the Internet - helping the reader to understand the interrelationship of the many aspects of the provision of electric power supply. ... For engineers, policymakers, and students alike, (this book) provides a high-level overview of how electric power is generated, transmitted, and controlled in the United States."

H. Chen, K. P. Wong, H. M. Nguyen, and C. Y. Chung, "Analyzing Oligopolistic Electricity Markets Using Coevolutionary Computation (pdf,431K), IEEE Transactions on Power Systems, Vol. 2(1), February, 2006.
Abstract: This paper presents a new unified framework for electricity market analysis based on coevolutionary computation (CCEM) for oligopoly electricity markets modeled as either one-shot or repeated games. The standard Cournot model and a new Pareto improvement model are explored. Both linear and constant elasticity demand functions are considered. A case study shows that CCEM is highly efficient and can handle nonlinear electricity market models that are difficult to handle by conventional methods.

Staff researchers with the Energy Information Administration (EIA) (U.S. Department of Energy, Washington, D.C.) have prepared a thoughtful, detailed, highly readable report titled "The Changing Structure of the Electric Power Industry 2000: An Update" (html), DOE/EIA-0562(00), October 2000, which is freely available either in pdf format (1.69MB) or in html.

Robert Entriken and Steve Wan, "Agent-Based Simulation of an Automatic Mitigation Procedure" (pdf,203K), Proceedings, 38th Hawaii International Conference on System Sciences, 2005.
Abstract: This paper describes experiments using computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Both authors are with the Electric Power Research Institute (EPRI). Other work by these two authors using agent-based tools includes EPRI Report 1007733 on automatic mitigation procedures (pdf,791K) and EPRI Report 1007755 on available capacity market designs (pdf,1.5M) , both reports focusing on the California electricity market.

Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers" (ps,215K), IEEE preprint, downloaded 5/11/05.
Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.

Software, Toolkits, and Demos

Open-Source Software for Electricity Market Research, Teaching, and Training

AMES Wholesale Power Market Test Bed (Java, Open Source)

The AMES Wholesale Power Market Test Bed, developed entirely in Java by an interdisciplinary team of researchers at Iowa State University, is a modular and extensible agent-based computational laboratory for studying the dynamic efficiency and reliability of wholesale power markets restructured in accordance with guidelines issued by the U.S. Federal Energy Regulatory Commission. AMES is an acronym for Agent-based Modeling of Electricity Systems.

AMES models traders with learning capabilities interacting over time in an ISO-managed wholesale power market operating over a transmission grid subject to congestion effects. Congestion on the grid is managed by means of locational marginal prices derived from optimal power flow solutions.

AMES is a free open-source tool suitable for research, teaching, and training applications. It is designed for the intensive experimental study of small to medium-sized systems (2-500 nodes). A graphical user interface permits the creation, modification, analysis and storage of scenarios, parameter initialization and editing, specification of behavioral rules (e.g. learning methods) for market participants, and output reports through table and chart displays.

EMCAS: Electricity Market Complex Adaptive System (Educational Version)

Argonne National Laboratory is now offering (upon request) an educational version of its agent-based power market analysis tool, EMCAS. Contact Guenter Conzelmann (guenter@anl.gov) for more information.

Annotated list of pointers to ACE/CAS General Software and Toolkits

Annotated list of pointers to ACE/CAS Computational Laboratories and Demonstration Software

Resource Sites and Groups

General Resources on Electricity Restructuring

A group of researchers at the Argonne National Laboratory (ANL) has developed the EMCAS (Electricity Markets Complex Adaptive Systems) Model. EMCAS is an agent-based computational framework that permits the exploratory study of a wide variety of electricity market designs via systematic computational experiments.

The Commonwealth Scientific and Industrial Research Organization (CSIRO) based in Australia is a diverse scientific organization focusing on the economic and social performance of many of Australia's leading industry sectors. One of the research areas under exploration by David Batten and other staff members of the CSIRO Agent-Based Modelling (CABM) Working Group, part of the CSIRO Centre for Complex System Science, is the agent-based computational modeling of Australia's National Electricity Market (NEM).

Chen-Ching Liu and Leigh Tesfatsion at Iowa State University are co-directors of the ISU Electric Energy Economics (E3) Group. The primary research focus of the ISU E3 Group is the integrated study of engineering and economics issues arising from the recent restructuring of the electricity industry. The development and use of an agent-based computational test-bed constitutes an important aspect of these research efforts.

Joseph Roop and Eihab Fathelrahaman, staff researchers at the Pacific Northwest National Laboratory, are using an agent-based approach to investigate to contract arrangements that determine the degree of responsiveness of residential households to changes in electricity prices.

A group of researchers at Sandia National Laboratories has developed an agent-based simulation laboratory Next-Generation Agent-Based Economic Laboratory (NABLE) (pdf,170K) for analyzing the economic factors, feedbacks, and downstream effects of infrastructure interdependencies, including (e.g.,) the effects of electric power outages. NABLE is a revised and restructured version of an earlier framework developed at Sandia, the Aspen Electricity Enhancement Model (Aspen-EE).

Raimo P. Hämäläinen and Pierre-Olivier Pineau (Systems Analysis Lab, Helsinki University, Finland) maintain a website on Deregulated Electricity Markets that they developed for a seminar they taught in Spring 1999, with a stress on Finland's restructuring efforts. This excellent site contains downloadable (pdf) slide presentations and recommended readings on the following electricity restructuring issues covered in the seminar: introductory surveys; optimal spot pricing; spot market models; transmission pricing; regional models (game aspects); financial tools; auction mechanisms; hydro reservoir management; customers behavior and pricing; and the on-line testing of an Internet based "PowerWeb" platform for auction simulation.

Raimo P. Hämäläinen, et al. (Systems Analysis Lab, Helsinki University, Finland) also maintain a Resource Site on Energy, Resources, and Environment that includes abstracts and citations for their papers on the following topics: dynamic pricing of electricity (development of a decision support system for consumers based on real-world natural and experimental data); agent-based simulation of computational electricity markets (development of prototype software called Power Agents); short-term load forecasting and load models (with computer implementation) ; contracting for multi-period electricity exchange (development of computational solution method); natural resource problems (dynamic game theory models); and pollution and environmental problems (two- and three-country transboundary air pollution models in a game theory setting, based on real-world emission reduction agreements among Finland, Russia, and Estonia).

Daniel Veit (Business School, University of Mannheim), Mario Ragwitz (Fraunhofer Institute for Systems and Innovation Research), and Wolf Fichtner (University of Karlsruhe) are collaborating on the PowerAce Project. This project uses an agent-based computational framework to examine the effects of a carbon dioxide emission allowance trading scheme on future power plant structures, investment decisions, and greenhouse gas emissions in a liberalized power market. A key motivation for this project is that an emissions trading system with obligatory participation is currently being launched in the European Union. Project publications are available for downloading at the main project site.

Individual Researchers

David Batten (CSIRO Agent-Based Modeling Working Group, Australia): Agent-based modelling of social, economic, and (bio)physical phenomena; Urban, regional, and evolutionary economics; Industrial ecology (energy, water, waste, and transportation).

Derek Bunn (Decision Sciences, London Business School): Business forecasting, decision technology, electricity and energy economics.

Silvano Cincotti (Department of Biophysical and Electronic Engineering, U of Genoa): Development of an agent-based computational framework for the study of electricity markets; Computational market design.

Tapas Das (Department of Industrial and Management Systems, U of South Florida,Tampa): Modeling and Design of Deregulated Electric Power Markets; Impact of Auction Based Pricing in Energy and Financial Transmission Rights (FTR) Markets.

Marija Ilic (Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh): Agent-based modeling of electricity spot markets; Large-scale systems modeling and simulation; Power systems control and pricing algorithms; Critical infrastructures and interdependencies.

Augusto Rupérez Micola (Universitat Pompeu Fabra, Barcelona): Simulation methods; Applied econometrics; Energy markets; European political economy.

Timothy Mount (Department of Applied Economics and Management, Cornell University, Ithaca, N.Y.): Econometric modeling and policy analysis relating to the use of fuels and electricity, and to their environmental consequences; Price behavior in auctions for electricity; Human-subject experimental tests of deregulated markets for electric power (market power and self-commitment).

Gerald B. Sheblé (Electrical and Computer Engineering, Portland State University): Agent-based computational modelling of electric power markets; Electric power auction market training simulator; Electric power strategy selector via genetic algorithms; Electric power futures contract market simulator.
Leigh Tesfatsion (Department of Economics, Iowa State University, Ames, Iowa): Market power and efficiency in computational electricity markets with auction pricing mechanisms; Role of learning v. structure in determining outcomes in restructured electricity markets; Agent-based computational economics.
Daniel Veit (Business Administration and Information Systems, University of Mannheim, Germany): Economic and technical coordination and cooperation in markets for non-storable goods; E-Business (design of mechanisms for electronic markets); Electricity market design (PowerACE project).

Anke Weidlich (Business Administration and Information Systems, University of Mannheim, Germany): Restructured electricity markets; Two-settlement systems; C02 emissions trading systems; German electricity industry; PowerACE; Agent-based computational economics.

Bart J. Wilson, (Department of Economics, George Mason University, Fairfax, VA): Industrial organization; Economic experiments; e-commerce electricity markets.

Copyright © 2009 Leigh Tesfatsion. All Rights Reserved.
Site Maintained By:: Leigh Tesfatsion; Professor of Economics and Mathematics; Iowa State University; Ames, IA 50011-1070; http://www.econ.iastate.edu/tesfatsi/; tesfatsi AT iastate.edu
General Resources on Electricity Restructuring
Electricity Market Open-Source Software
ACE Website: Abstract: The author discusses the development of the Simulator for Electrical Power Industry Agents (SEPIA) sponsored by the Electric Power Research Institute (EPRI). SEPIA uses autonomous adaptive agents to represent possible industrial components (e.g., generation units, transmission system, load) and the corporate entities (e.g., GenCos and LoadCos) that own these components. Objectives are: (1) to develop a high-fidelity scenario-free modeling and optimization tool to use for gaining strategic insight into the operation of the deregulated power industry; (2) to show how networks of communicating and cooperating intelligent software agents can be used to adaptively manage complex distributed systems; and (3) to investigate how collections of agents (agencies) can be used to buy and sell electricity and participate in the electronic market place and, ultimately, to create self-optimizing and self-healing capabilities for the electric power grid and the interconnected critical infrastructures.

Vladimir S. Koritarov, "Real-World Market Representation with Agents" (pdf,2MB), IEEE Power and Energy Magazine, 2004, pp. 39-46
Abstract: "The electric power industry around the world is undergoing an extensive restructuring process. In many countries the traditional vertically integrated power utilities are being unbundled and replaced with a number of separate business entities dealing with the generation, transmission, and distribution of electric power. One of the most significant features of the restructuring process is the introduction of electricity markets, aimed at providing competitive electricity service to consumers. As power markets are relatively new and still continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of electricity markets over time and how market participants may act and react to the changing economic, financial, and regulatory environments in which they operate. (This paper argues that a) new and rather promising approach is to model the electricity market as a complex adaptive system using an agent-based modeling and simulation approach."

Frank Sensfuß, Mario Ragwitz, Massimo Genoese, and Dominik Möst, Agent-Based Simulation of Electricity Markets: A Literature Review (pdf,485K), Working Paper Sustainability and Innovation, No. S 5/2007, Fraunhofer Institute Systems and Innovation Research.
Abstract: "Liberalization, climate policy, and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players, and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets."

Anke Weidlich and Daniel Veit, “A Critical Survey of Agent-Based Wholesale Electricity Market Models” (doi/eneco), Energy Economics, in press, 2008.
Abstract: "The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed."

Steve Widergren, Junjie Sun, and Leigh Tesfatsion, "Market Design Test Environments" (pdf,136K), Proceedings, IEEE Power Engineering Society General Meeting, Montreal, June 2006.
Abstract: "Power industry restructuring continues to evolve at multiple levels of system operations. At the bulk electricity level, several organizations charged with regional system operation are implementing versions of a Wholesale Power Market Platform (WPMP) in response to U.S. Federal Energy Regulatory Commission initiatives. Recently the Energy Policy Act of 2005 and several regional initiatives have been pressing the integration of demand response as a resource for system operations. These policy and regulatory pressures are driving the exploration of new market designs at the wholesale and retail levels. The complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance demand a flexible computational environment where designs can be tested and sensitivities to power system and market rule changes can be explored. This paper discusses the use of agent-based computational methods for the study of electricity markets at the wholesale and retail levels, and explores distinctions in problem formulation between these levels."

Shun-Kun Yu and Jia-Hai Yuan, "Agent-Based Computational Economics: Methodology and Its Application in Electricity Market Research" (pdf,205K), Proceedings, The 7th International Power Engineering Conference (IPEC), 2005.
Abstract: "The restructured electricity market is a complex adaptive system and world-wide experiences show that market design is a complicated task. Recently, under the paradigm of agent-based computational economics (ACE), a new research focus is forming and a large number of literatures are springing up, but there is still no discussion on ACE’s theoretical value and insufficiency in the research of electricity market in a hierarchy of methodologies. Therefore the authors' research is an attempt in this aspect. By means of analyzing the evolution of economics methodology from mathematical deduction to simulation induction, and their inherent relevance, the unique superiority of ACE on the level of methodology is expounded. A further selective survey on existing literatures shows that with the ACE model the marketization process can be understood clearly in deeper level and wider scope. Finally, to give a reference to theoretical progress, the prospective application of ACE, especially its potential in China’s electric sector restructuring,is discussed."; Abstract: "The electric power industry around the world is undergoing an extensive restructuring process. In many countries the traditional vertically integrated power utilities are being unbundled and replaced with a number of separate business entities dealing with the generation, transmission, and distribution of electric power. One of the most significant features of the restructuring process is the introduction of electricity markets, aimed at providing competitive electricity service to consumers. As power markets are relatively new and still continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of electricity markets over time and how market participants may act and react to the changing economic, financial, and regulatory environments in which they operate. (This paper argues that a) new and rather promising approach is to model the electricity market as a complex adaptive system using an agent-based modeling and simulation approach."

Frank Sensfuß, Mario Ragwitz, Massimo Genoese, and Dominik Möst, Agent-Based Simulation of Electricity Markets: A Literature Review (pdf,485K), Working Paper Sustainability and Innovation, No. S 5/2007, Fraunhofer Institute Systems and Innovation Research.
Abstract: "Liberalization, climate policy, and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players, and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets."

Anke Weidlich and Daniel Veit, “A Critical Survey of Agent-Based Wholesale Electricity Market Models” (doi/eneco), Energy Economics, in press, 2008.
Abstract: "The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed."

Steve Widergren, Junjie Sun, and Leigh Tesfatsion, "Market Design Test Environments" (pdf,136K), Proceedings, IEEE Power Engineering Society General Meeting, Montreal, June 2006.
Abstract: "Power industry restructuring continues to evolve at multiple levels of system operations. At the bulk electricity level, several organizations charged with regional system operation are implementing versions of a Wholesale Power Market Platform (WPMP) in response to U.S. Federal Energy Regulatory Commission initiatives. Recently the Energy Policy Act of 2005 and several regional initiatives have been pressing the integration of demand response as a resource for system operations. These policy and regulatory pressures are driving the exploration of new market designs at the wholesale and retail levels. The complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance demand a flexible computational environment where designs can be tested and sensitivities to power system and market rule changes can be explored. This paper discusses the use of agent-based computational methods for the study of electricity markets at the wholesale and retail levels, and explores distinctions in problem formulation between these levels."

Shun-Kun Yu and Jia-Hai Yuan, "Agent-Based Computational Economics: Methodology and Its Application in Electricity Market Research" (pdf,205K), Proceedings, The 7th International Power Engineering Conference (IPEC), 2005.
Abstract: "The restructured electricity market is a complex adaptive system and world-wide experiences show that market design is a complicated task. Recently, under the paradigm of agent-based computational economics (ACE), a new research focus is forming and a large number of literatures are springing up, but there is still no discussion on ACE’s theoretical value and insufficiency in the research of electricity market in a hierarchy of methodologies. Therefore the authors' research is an attempt in this aspect. By means of analyzing the evolution of economics methodology from mathematical deduction to simulation induction, and their inherent relevance, the unique superiority of ACE on the level of methodology is expounded. A further selective survey on existing literatures shows that with the ACE model the marketization process can be understood clearly in deeper level and wider scope. Finally, to give a reference to theoretical progress, the prospective application of ACE, especially its potential in China’s electric sector restructuring,is discussed."; Abstract: "Liberalization, climate policy, and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players, and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets."

Anke Weidlich and Daniel Veit, “A Critical Survey of Agent-Based Wholesale Electricity Market Models” (doi/eneco), Energy Economics, in press, 2008.
Abstract: "The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed."

Steve Widergren, Junjie Sun, and Leigh Tesfatsion, "Market Design Test Environments" (pdf,136K), Proceedings, IEEE Power Engineering Society General Meeting, Montreal, June 2006.
Abstract: "Power industry restructuring continues to evolve at multiple levels of system operations. At the bulk electricity level, several organizations charged with regional system operation are implementing versions of a Wholesale Power Market Platform (WPMP) in response to U.S. Federal Energy Regulatory Commission initiatives. Recently the Energy Policy Act of 2005 and several regional initiatives have been pressing the integration of demand response as a resource for system operations. These policy and regulatory pressures are driving the exploration of new market designs at the wholesale and retail levels. The complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance demand a flexible computational environment where designs can be tested and sensitivities to power system and market rule changes can be explored. This paper discusses the use of agent-based computational methods for the study of electricity markets at the wholesale and retail levels, and explores distinctions in problem formulation between these levels."

Shun-Kun Yu and Jia-Hai Yuan, "Agent-Based Computational Economics: Methodology and Its Application in Electricity Market Research" (pdf,205K), Proceedings, The 7th International Power Engineering Conference (IPEC), 2005.
Abstract: "The restructured electricity market is a complex adaptive system and world-wide experiences show that market design is a complicated task. Recently, under the paradigm of agent-based computational economics (ACE), a new research focus is forming and a large number of literatures are springing up, but there is still no discussion on ACE’s theoretical value and insufficiency in the research of electricity market in a hierarchy of methodologies. Therefore the authors' research is an attempt in this aspect. By means of analyzing the evolution of economics methodology from mathematical deduction to simulation induction, and their inherent relevance, the unique superiority of ACE on the level of methodology is expounded. A further selective survey on existing literatures shows that with the ACE model the marketization process can be understood clearly in deeper level and wider scope. Finally, to give a reference to theoretical progress, the prospective application of ACE, especially its potential in China’s electric sector restructuring,is discussed."; Abstract: "The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed."

Steve Widergren, Junjie Sun, and Leigh Tesfatsion, "Market Design Test Environments" (pdf,136K), Proceedings, IEEE Power Engineering Society General Meeting, Montreal, June 2006.
Abstract: "Power industry restructuring continues to evolve at multiple levels of system operations. At the bulk electricity level, several organizations charged with regional system operation are implementing versions of a Wholesale Power Market Platform (WPMP) in response to U.S. Federal Energy Regulatory Commission initiatives. Recently the Energy Policy Act of 2005 and several regional initiatives have been pressing the integration of demand response as a resource for system operations. These policy and regulatory pressures are driving the exploration of new market designs at the wholesale and retail levels. The complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance demand a flexible computational environment where designs can be tested and sensitivities to power system and market rule changes can be explored. This paper discusses the use of agent-based computational methods for the study of electricity markets at the wholesale and retail levels, and explores distinctions in problem formulation between these levels."

Shun-Kun Yu and Jia-Hai Yuan, "Agent-Based Computational Economics: Methodology and Its Application in Electricity Market Research" (pdf,205K), Proceedings, The 7th International Power Engineering Conference (IPEC), 2005.
Abstract: "The restructured electricity market is a complex adaptive system and world-wide experiences show that market design is a complicated task. Recently, under the paradigm of agent-based computational economics (ACE), a new research focus is forming and a large number of literatures are springing up, but there is still no discussion on ACE’s theoretical value and insufficiency in the research of electricity market in a hierarchy of methodologies. Therefore the authors' research is an attempt in this aspect. By means of analyzing the evolution of economics methodology from mathematical deduction to simulation induction, and their inherent relevance, the unique superiority of ACE on the level of methodology is expounded. A further selective survey on existing literatures shows that with the ACE model the marketization process can be understood clearly in deeper level and wider scope. Finally, to give a reference to theoretical progress, the prospective application of ACE, especially its potential in China’s electric sector restructuring,is discussed."; Abstract: "Power industry restructuring continues to evolve at multiple levels of system operations. At the bulk electricity level, several organizations charged with regional system operation are implementing versions of a Wholesale Power Market Platform (WPMP) in response to U.S. Federal Energy Regulatory Commission initiatives. Recently the Energy Policy Act of 2005 and several regional initiatives have been pressing the integration of demand response as a resource for system operations. These policy and regulatory pressures are driving the exploration of new market designs at the wholesale and retail levels. The complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance demand a flexible computational environment where designs can be tested and sensitivities to power system and market rule changes can be explored. This paper discusses the use of agent-based computational methods for the study of electricity markets at the wholesale and retail levels, and explores distinctions in problem formulation between these levels."

Shun-Kun Yu and Jia-Hai Yuan, "Agent-Based Computational Economics: Methodology and Its Application in Electricity Market Research" (pdf,205K), Proceedings, The 7th International Power Engineering Conference (IPEC), 2005.
Abstract: "The restructured electricity market is a complex adaptive system and world-wide experiences show that market design is a complicated task. Recently, under the paradigm of agent-based computational economics (ACE), a new research focus is forming and a large number of literatures are springing up, but there is still no discussion on ACE’s theoretical value and insufficiency in the research of electricity market in a hierarchy of methodologies. Therefore the authors' research is an attempt in this aspect. By means of analyzing the evolution of economics methodology from mathematical deduction to simulation induction, and their inherent relevance, the unique superiority of ACE on the level of methodology is expounded. A further selective survey on existing literatures shows that with the ACE model the marketization process can be understood clearly in deeper level and wider scope. Finally, to give a reference to theoretical progress, the prospective application of ACE, especially its potential in China’s electric sector restructuring,is discussed."; Abstract: "The restructured electricity market is a complex adaptive system and world-wide experiences show that market design is a complicated task. Recently, under the paradigm of agent-based computational economics (ACE), a new research focus is forming and a large number of literatures are springing up, but there is still no discussion on ACE’s theoretical value and insufficiency in the research of electricity market in a hierarchy of methodologies. Therefore the authors' research is an attempt in this aspect. By means of analyzing the evolution of economics methodology from mathematical deduction to simulation induction, and their inherent relevance, the unique superiority of ACE on the level of methodology is expounded. A further selective survey on existing literatures shows that with the ACE model the marketization process can be understood clearly in deeper level and wider scope. Finally, to give a reference to theoretical progress, the prospective application of ACE, especially its potential in China’s electric sector restructuring,is discussed."; Abstract: This paper describes an agent-based computational economics approach for studying the effect of alternative structures and mechanisms on behavior in a simulated model of the pre-NETA England and Wales electricity market. Agents learn using hierarchical learning classifier systems. The authors test to see whether the agents: (a) are able to learn optimal strategies when competing against non-adaptive agents; (b) are able to learn strategies observable in the real world when competing against other adaptive agents; and (c) are able to evolve cooperative behaviors without explicit communication.
John Bower and Derek Bunn, "Experimental Analysis of the Efficiency of Uniform-Price versus Discriminatory Auctions in the England and Wales Electricity Market", Journal of Economic Dynamics and Control 25, March 2001, pages 561-592.
Abstract: The authors develop an agent-based computational model of the wholesale market for electricity in England and Wales that allows them to compare market prices and the bidding strategies of individual generators under different trading arrangements. The authors use this framework to address several restructing issues under debate for the England and Wales market -- in particular, the efficacy of using a uniform-price versus a discriminatory-price auction format.
Timothy J. Brennan, Karen L. Palmer, and Salvador A. Martinez, Alternating Currents: Electricity Markets and Public Policy, Resources for the Future, Washington, D.C., 226 pp., 2002.
Derek Bunn and Fernando Oliveira, "Agent-Based Simulation: An Application to the New Electricity Trading Arrangements of England and Wales", IEEE Transactions on Evolutionary Computation, Volume 5, Number 5, October 2001, 493-503.
Abstract: This paper presents a large-scale application of a multi-agent evolutonary model of the proposed New Electricity Trading Arrangements (NETA) in the United Kingdom. The model is a detailed plant-by-plant model with an active specification of the demand side of the market. The model was able to provide pricing and strategic insights into the workings of the NETA prior to its actual introduction.
Derek Bunn and Fernando Oliveira, "Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation" (pdf,505K), Working Paper, August 2004, to appear in the Annals of Operations Research.
Abstract: The authors use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices.

Jack Casazza and Frank Delea, Understanding Electric Power Systems: An Overview of the Technology and the Marketplace, IEEE Press/Wiley-Interscience, Piscataway, NJ, 2003.
Abstract: "(This book) bridges the gap between technology, government policy, economics and finance, business arrangements, and the Internet - helping the reader to understand the interrelationship of the many aspects of the provision of electric power supply. ... For engineers, policymakers, and students alike, (this book) provides a high-level overview of how electric power is generated, transmitted, and controlled in the United States."

H. Chen, K. P. Wong, H. M. Nguyen, and C. Y. Chung, "Analyzing Oligopolistic Electricity Markets Using Coevolutionary Computation (pdf,431K), IEEE Transactions on Power Systems, Vol. 2(1), February, 2006.
Abstract: This paper presents a new unified framework for electricity market analysis based on coevolutionary computation (CCEM) for oligopoly electricity markets modeled as either one-shot or repeated games. The standard Cournot model and a new Pareto improvement model are explored. Both linear and constant elasticity demand functions are considered. A case study shows that CCEM is highly efficient and can handle nonlinear electricity market models that are difficult to handle by conventional methods.

Staff researchers with the Energy Information Administration (EIA) (U.S. Department of Energy, Washington, D.C.) have prepared a thoughtful, detailed, highly readable report titled "The Changing Structure of the Electric Power Industry 2000: An Update" (html), DOE/EIA-0562(00), October 2000, which is freely available either in pdf format (1.69MB) or in html.

Robert Entriken and Steve Wan, "Agent-Based Simulation of an Automatic Mitigation Procedure" (pdf,203K), Proceedings, 38th Hawaii International Conference on System Sciences, 2005.
Abstract: This paper describes experiments using computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Both authors are with the Electric Power Research Institute (EPRI). Other work by these two authors using agent-based tools includes EPRI Report 1007733 on automatic mitigation procedures (pdf,791K) and EPRI Report 1007755 on available capacity market designs (pdf,1.5M) , both reports focusing on the California electricity market.

Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers" (ps,215K), IEEE preprint, downloaded 5/11/05.
Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: The authors develop an agent-based computational model of the wholesale market for electricity in England and Wales that allows them to compare market prices and the bidding strategies of individual generators under different trading arrangements. The authors use this framework to address several restructing issues under debate for the England and Wales market -- in particular, the efficacy of using a uniform-price versus a discriminatory-price auction format.
Timothy J. Brennan, Karen L. Palmer, and Salvador A. Martinez, Alternating Currents: Electricity Markets and Public Policy, Resources for the Future, Washington, D.C., 226 pp., 2002.
Derek Bunn and Fernando Oliveira, "Agent-Based Simulation: An Application to the New Electricity Trading Arrangements of England and Wales", IEEE Transactions on Evolutionary Computation, Volume 5, Number 5, October 2001, 493-503.
Abstract: This paper presents a large-scale application of a multi-agent evolutonary model of the proposed New Electricity Trading Arrangements (NETA) in the United Kingdom. The model is a detailed plant-by-plant model with an active specification of the demand side of the market. The model was able to provide pricing and strategic insights into the workings of the NETA prior to its actual introduction.
Derek Bunn and Fernando Oliveira, "Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation" (pdf,505K), Working Paper, August 2004, to appear in the Annals of Operations Research.
Abstract: The authors use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices.

Jack Casazza and Frank Delea, Understanding Electric Power Systems: An Overview of the Technology and the Marketplace, IEEE Press/Wiley-Interscience, Piscataway, NJ, 2003.
Abstract: "(This book) bridges the gap between technology, government policy, economics and finance, business arrangements, and the Internet - helping the reader to understand the interrelationship of the many aspects of the provision of electric power supply. ... For engineers, policymakers, and students alike, (this book) provides a high-level overview of how electric power is generated, transmitted, and controlled in the United States."

H. Chen, K. P. Wong, H. M. Nguyen, and C. Y. Chung, "Analyzing Oligopolistic Electricity Markets Using Coevolutionary Computation (pdf,431K), IEEE Transactions on Power Systems, Vol. 2(1), February, 2006.
Abstract: This paper presents a new unified framework for electricity market analysis based on coevolutionary computation (CCEM) for oligopoly electricity markets modeled as either one-shot or repeated games. The standard Cournot model and a new Pareto improvement model are explored. Both linear and constant elasticity demand functions are considered. A case study shows that CCEM is highly efficient and can handle nonlinear electricity market models that are difficult to handle by conventional methods.

Staff researchers with the Energy Information Administration (EIA) (U.S. Department of Energy, Washington, D.C.) have prepared a thoughtful, detailed, highly readable report titled "The Changing Structure of the Electric Power Industry 2000: An Update" (html), DOE/EIA-0562(00), October 2000, which is freely available either in pdf format (1.69MB) or in html.

Robert Entriken and Steve Wan, "Agent-Based Simulation of an Automatic Mitigation Procedure" (pdf,203K), Proceedings, 38th Hawaii International Conference on System Sciences, 2005.
Abstract: This paper describes experiments using computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Both authors are with the Electric Power Research Institute (EPRI). Other work by these two authors using agent-based tools includes EPRI Report 1007733 on automatic mitigation procedures (pdf,791K) and EPRI Report 1007755 on available capacity market designs (pdf,1.5M) , both reports focusing on the California electricity market.

Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers" (ps,215K), IEEE preprint, downloaded 5/11/05.
Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This paper presents a large-scale application of a multi-agent evolutonary model of the proposed New Electricity Trading Arrangements (NETA) in the United Kingdom. The model is a detailed plant-by-plant model with an active specification of the demand side of the market. The model was able to provide pricing and strategic insights into the workings of the NETA prior to its actual introduction.
Derek Bunn and Fernando Oliveira, "Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation" (pdf,505K), Working Paper, August 2004, to appear in the Annals of Operations Research.
Abstract: The authors use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices.

Jack Casazza and Frank Delea, Understanding Electric Power Systems: An Overview of the Technology and the Marketplace, IEEE Press/Wiley-Interscience, Piscataway, NJ, 2003.
Abstract: "(This book) bridges the gap between technology, government policy, economics and finance, business arrangements, and the Internet - helping the reader to understand the interrelationship of the many aspects of the provision of electric power supply. ... For engineers, policymakers, and students alike, (this book) provides a high-level overview of how electric power is generated, transmitted, and controlled in the United States."

H. Chen, K. P. Wong, H. M. Nguyen, and C. Y. Chung, "Analyzing Oligopolistic Electricity Markets Using Coevolutionary Computation (pdf,431K), IEEE Transactions on Power Systems, Vol. 2(1), February, 2006.
Abstract: This paper presents a new unified framework for electricity market analysis based on coevolutionary computation (CCEM) for oligopoly electricity markets modeled as either one-shot or repeated games. The standard Cournot model and a new Pareto improvement model are explored. Both linear and constant elasticity demand functions are considered. A case study shows that CCEM is highly efficient and can handle nonlinear electricity market models that are difficult to handle by conventional methods.

Staff researchers with the Energy Information Administration (EIA) (U.S. Department of Energy, Washington, D.C.) have prepared a thoughtful, detailed, highly readable report titled "The Changing Structure of the Electric Power Industry 2000: An Update" (html), DOE/EIA-0562(00), October 2000, which is freely available either in pdf format (1.69MB) or in html.

Robert Entriken and Steve Wan, "Agent-Based Simulation of an Automatic Mitigation Procedure" (pdf,203K), Proceedings, 38th Hawaii International Conference on System Sciences, 2005.
Abstract: This paper describes experiments using computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Both authors are with the Electric Power Research Institute (EPRI). Other work by these two authors using agent-based tools includes EPRI Report 1007733 on automatic mitigation procedures (pdf,791K) and EPRI Report 1007755 on available capacity market designs (pdf,1.5M) , both reports focusing on the California electricity market.

Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers" (ps,215K), IEEE preprint, downloaded 5/11/05.
Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: The authors use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices.

Jack Casazza and Frank Delea, Understanding Electric Power Systems: An Overview of the Technology and the Marketplace, IEEE Press/Wiley-Interscience, Piscataway, NJ, 2003.
Abstract: "(This book) bridges the gap between technology, government policy, economics and finance, business arrangements, and the Internet - helping the reader to understand the interrelationship of the many aspects of the provision of electric power supply. ... For engineers, policymakers, and students alike, (this book) provides a high-level overview of how electric power is generated, transmitted, and controlled in the United States."

H. Chen, K. P. Wong, H. M. Nguyen, and C. Y. Chung, "Analyzing Oligopolistic Electricity Markets Using Coevolutionary Computation (pdf,431K), IEEE Transactions on Power Systems, Vol. 2(1), February, 2006.
Abstract: This paper presents a new unified framework for electricity market analysis based on coevolutionary computation (CCEM) for oligopoly electricity markets modeled as either one-shot or repeated games. The standard Cournot model and a new Pareto improvement model are explored. Both linear and constant elasticity demand functions are considered. A case study shows that CCEM is highly efficient and can handle nonlinear electricity market models that are difficult to handle by conventional methods.

Staff researchers with the Energy Information Administration (EIA) (U.S. Department of Energy, Washington, D.C.) have prepared a thoughtful, detailed, highly readable report titled "The Changing Structure of the Electric Power Industry 2000: An Update" (html), DOE/EIA-0562(00), October 2000, which is freely available either in pdf format (1.69MB) or in html.

Robert Entriken and Steve Wan, "Agent-Based Simulation of an Automatic Mitigation Procedure" (pdf,203K), Proceedings, 38th Hawaii International Conference on System Sciences, 2005.
Abstract: This paper describes experiments using computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Both authors are with the Electric Power Research Institute (EPRI). Other work by these two authors using agent-based tools includes EPRI Report 1007733 on automatic mitigation procedures (pdf,791K) and EPRI Report 1007755 on available capacity market designs (pdf,1.5M) , both reports focusing on the California electricity market.

Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers" (ps,215K), IEEE preprint, downloaded 5/11/05.
Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: "(This book) bridges the gap between technology, government policy, economics and finance, business arrangements, and the Internet - helping the reader to understand the interrelationship of the many aspects of the provision of electric power supply. ... For engineers, policymakers, and students alike, (this book) provides a high-level overview of how electric power is generated, transmitted, and controlled in the United States."

H. Chen, K. P. Wong, H. M. Nguyen, and C. Y. Chung, "Analyzing Oligopolistic Electricity Markets Using Coevolutionary Computation (pdf,431K), IEEE Transactions on Power Systems, Vol. 2(1), February, 2006.
Abstract: This paper presents a new unified framework for electricity market analysis based on coevolutionary computation (CCEM) for oligopoly electricity markets modeled as either one-shot or repeated games. The standard Cournot model and a new Pareto improvement model are explored. Both linear and constant elasticity demand functions are considered. A case study shows that CCEM is highly efficient and can handle nonlinear electricity market models that are difficult to handle by conventional methods.

Staff researchers with the Energy Information Administration (EIA) (U.S. Department of Energy, Washington, D.C.) have prepared a thoughtful, detailed, highly readable report titled "The Changing Structure of the Electric Power Industry 2000: An Update" (html), DOE/EIA-0562(00), October 2000, which is freely available either in pdf format (1.69MB) or in html.

Robert Entriken and Steve Wan, "Agent-Based Simulation of an Automatic Mitigation Procedure" (pdf,203K), Proceedings, 38th Hawaii International Conference on System Sciences, 2005.
Abstract: This paper describes experiments using computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Both authors are with the Electric Power Research Institute (EPRI). Other work by these two authors using agent-based tools includes EPRI Report 1007733 on automatic mitigation procedures (pdf,791K) and EPRI Report 1007755 on available capacity market designs (pdf,1.5M) , both reports focusing on the California electricity market.

Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers" (ps,215K), IEEE preprint, downloaded 5/11/05.
Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This paper presents a new unified framework for electricity market analysis based on coevolutionary computation (CCEM) for oligopoly electricity markets modeled as either one-shot or repeated games. The standard Cournot model and a new Pareto improvement model are explored. Both linear and constant elasticity demand functions are considered. A case study shows that CCEM is highly efficient and can handle nonlinear electricity market models that are difficult to handle by conventional methods.

Staff researchers with the Energy Information Administration (EIA) (U.S. Department of Energy, Washington, D.C.) have prepared a thoughtful, detailed, highly readable report titled "The Changing Structure of the Electric Power Industry 2000: An Update" (html), DOE/EIA-0562(00), October 2000, which is freely available either in pdf format (1.69MB) or in html.

Robert Entriken and Steve Wan, "Agent-Based Simulation of an Automatic Mitigation Procedure" (pdf,203K), Proceedings, 38th Hawaii International Conference on System Sciences, 2005.
Abstract: This paper describes experiments using computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Both authors are with the Electric Power Research Institute (EPRI). Other work by these two authors using agent-based tools includes EPRI Report 1007733 on automatic mitigation procedures (pdf,791K) and EPRI Report 1007755 on available capacity market designs (pdf,1.5M) , both reports focusing on the California electricity market.

Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers" (ps,215K), IEEE preprint, downloaded 5/11/05.
Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This paper describes experiments using computer-based agents to simulate the impact of the California ISO's proposed Automatic Mitigation Procedure (AMP) for limiting the exercise of market power. The experimental results indicate that the AMP is effective in reducing market clearing prices under situations where they would otherwise reach the price cap. Both authors are with the Electric Power Research Institute (EPRI). Other work by these two authors using agent-based tools includes EPRI Report 1007733 on automatic mitigation procedures (pdf,791K) and EPRI Report 1007755 on available capacity market designs (pdf,1.5M) , both reports focusing on the California electricity market.

Damien Ernst, Anna Minoia, and Marija Ilic, "Market Dynamics Driven by the Decision-Making Power Producers" (ps,215K), IEEE preprint, downloaded 5/11/05.
Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract:The authors develop an electricity market model in which strategic power producers interact through a spot market over a 2-node transmission grid with congestion managed by locational marginal pricing. They investigate the effects on market outcomes of the line transfer capacity, the number and size of generators, and the presence or absence of generator coalitions.

Jerry Jackson, "Are Utility Regulations Inhibiting Technological Progress?: An Agent-Based Microsimulation Analysis of the Diffusion of Customer-Owned Generating Systems" (pdf, 34pp), Working Paper, Jackson Associates, March 2005.
Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: The emergence of new small-scale electric generation technologies permits small-sized and medium-sized commercial utlity customers to generate some of their own electric power. This study develops and applies an agent-based microsimulation model of new technology choices to evaluate the impacts of utility regulatory practices specifically on the diffusion of combined heat and power (CHP) electric generation technologies. A cellular automaton process is used to model information dispersion and knowledge acquisition by individual agents. Analysis of a New York utility study area finds that current utility standby rate-setting practices are substantially reducing customer adoption of CHP systems and imposing significant additional energy costs on utility customers.

Paul L. Joskow, "The Difficult Transition to Competitive Electricity Markets in the U.S.", May 2003, Prepared for the conference "Electricity Deregulation: Where From Here?" at the Bush Presidential Conference Center, Texas A&M University, April 4, 2003. [Paper accessed 5/14/03 via link on Joskow's home page.]

Deddy P. Koesrindartoto and Leigh Tesfatsion, "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach" [ (ppt talk,265K), (pdf,45K)], Energy, Environment, and Economics in a New Era, Proceedings of the 24th USAEE/IAEE North American Conference, Washington, D.C., July 8-10, 2004. (Proceedings distributed by USAEE/IAEE on a CD).
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design encompassing real-time, day-ahead, ancillary, and financial transmission rights markets. The WPMP has been adopted in some regions of the U.S. but resisted in others on the grounds that the reliability of the design has not yet been sufficiently tested or demonstrated. This study reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue addressed is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion.

Deddy P. Koesrindartoto, Junjie Sun, and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs" (pdf,112K), Proceedings, Vol. 1, IEEE Power Engineering Society General Meeting, San Francisco, California, June 2005, 931-936.
Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: Previous work by Koesrindartoto and Tesfatsion (2004) reports on the development of an agent-based model for exploring the economic reliability of the Wholesale Power Market Platform proposed by FERC in April 2003. This paper reports on the Repast/Java implementation of this model as an agent-based computational laboratory. Initial experiments focusing on optimal power flow solution methods for the day-ahead and real-time markets are discussed.

Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets" (download site), ISU Economics Working Paper #09009, June 2009.
Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This study uses the AMES Wholesale Power Market Test Bed to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs.

Ross Little and Bruce Sawhill, "Market Feedback Replaces Regulation: Adaptation in the Electric Power Industry", Complexity, Vol. 3/No. 4, March/April 1998, 46-50.

Charles M. Macal and Michael J. North, "Validation of an Agent-Based Model of Deregulated Electric Power Markets" (pdf,66K), presented at the North American Association for Computational and Social Organization (NAACSOS) Conference, Notre Dame, Indiana, June 26-28, 2005.
Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: EMCAS (Electricity Market Complex Adaptive System) is an agent-based simulation model of the electric power market designed to investigate market restructuring and deregulation and to understand the implications of a competitive power market on electricity prices, availability, and reliability. Model validation is an essential part of the model development process if models are to be accepted and used to support decision making. This paper describes the validation process for the EMCAS model and its results for use in practical decision making. The validation process also is an initial attempt to establish a general and practical framework for agent-based model validation.

Vishnuteja Nanduri and Tapas K. Das, "A Reinforcement Learning Model to Assess the Market Power Under Auction-Based Energy Bidding" (pdf,734K), IEEE Transactions on Power Systems 22(1):85-95, February 2007.
Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This paper develops a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in double-auction (DA) electricity markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl–Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue- based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network.

James Nicolaisen, Valentin Petrov, and Leigh Tesfatsion, "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing" (pdf,367K), IEEE Transactions on Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 504-523. [ (pdf with colored figures,162K), (pdf presentation,116K)].
Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Georgios Papageorgiou, "Modelling of Electricity Markets Using Software Agents" (pdf,167pp.), a dissertation submitted to the University of Manchester Institute of Science and Technology for the degree of Master of Science in Electrical Power Engineering, Department of Electrical Engineering and Electronics, UMIST, 2004.
Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This paper develops an agent-based computational model to investigate the bidding behavior of generating companies in a short-term bilateral market. Each generating company is modelled with specific strategic and operational objectives and bounded reasoning abilities based on principles of reinforcement learning. Price and market power effects are explored under a number of different treatments (e.g., settlement procedures, demand conditions, number of generators).

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Using Experiments to Inform the Privatization/Deregulation Movement in Electricity", The Cato Journal 21 (3), Winter 2002, 515-544.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Discriminatory Price Auctions in Electricity Markets: Low Volatility at the Expense of High Price Levels", Journal of Regulatory Economics 23(2), 2003, 109-123.

Stephen J. Rassenti, Vernon L. Smith, and Bart J. Wilson, "Controlling Market Power and Price Spikes in Electricity Networks: Demand-Side Bidding", Proceedings of the National Academy of Sciences 100(5), March 4, 2003, 2998-3003.
Steve Silberman, "The Energy Web" (html), Wired, July 2001.
Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: Silberman provides ideas on how to use multi-agent systems techniques to distribute electric power. "The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else."

Abhishek Somani and Leigh Tesfatsion, "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures" (pdf,2.8M), IEEE Computational Intelligence Magazine, Vol. 3, No. 4, November 2008, 56-72.
Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), Proceedings, IEEE Power Engineering Systems General Meeting, Tampa, Florida, June 2007.
Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This proceedings paper is a brief summary of a Computational Economics article (see below). It reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects.

Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework" [ (pdf,2.2MB), (ppt,625K)], Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) -- for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. It is shown for this example that generators easily learn to implicitly collude on higher-than-true marginal costs when the demand bids of load-serving entities take the form of fixed loads.

Daniel J. Veit, Anke Weidlich, Jian Yao, and Shmuel Oren, "Simulating the Dynamics in Two-Settlement Electricity Markets via an Agent-Based Approach" (pdf,1.4M), International Journal of Management Science and Engineering Management, Vol. 1, No. 2, 2006, 83-97.
Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; Abstract: This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices. Keywords: two settlements, electricity markets, Cournot, agent-based simulation

P. Visudhiphan and Marija D. Ilic, "An Agent-Based Approach to Modeling Electricity Spot Markets", 2001 IFAC-SME Meeting Proceedings, Austria, September 6-8, 2001.; The AMES Wholesale Power Market Test Bed, developed entirely in Java by an interdisciplinary team of researchers at Iowa State University, is a modular and extensible agent-based computational laboratory for studying the dynamic efficiency and reliability of wholesale power markets restructured in accordance with guidelines issued by the U.S. Federal Energy Regulatory Commission. AMES is an acronym for Agent-based Modeling of Electricity Systems.; AMES models traders with learning capabilities interacting over time in an ISO-managed wholesale power market operating over a transmission grid subject to congestion effects. Congestion on the grid is managed by means of locational marginal prices derived from optimal power flow solutions.; AMES is a free open-source tool suitable for research, teaching, and training applications. It is designed for the intensive experimental study of small to medium-sized systems (2-500 nodes). A graphical user interface permits the creation, modification, analysis and storage of scenarios, parameter initialization and editing, specification of behavioral rules (e.g. learning methods) for market participants, and output reports through table and chart displays.

EMCAS: Electricity Market Complex Adaptive System (Educational Version)

Argonne National Laboratory is now offering (upon request) an educational version of its agent-based power market analysis tool, EMCAS. Contact Guenter Conzelmann (guenter@anl.gov) for more information.

Annotated list of pointers to ACE/CAS General Software and Toolkits

Annotated list of pointers to ACE/CAS Computational Laboratories and Demonstration Software; Argonne National Laboratory is now offering (upon request) an educational version of its agent-based power market analysis tool, EMCAS. Contact Guenter Conzelmann (guenter@anl.gov) for more information.

Annotated list of pointers to ACE/CAS General Software and Toolkits

Annotated list of pointers to ACE/CAS Computational Laboratories and Demonstration Software

Agent-Based Computational Economics (ACE) Research Area: Restructured Electricity Markets

Introduction

Basic Issues

Surveys

Other Readings

Software, Toolkits, and Demos

Resource Sites and Groups

Individual Researchers

Copyright © 2009 Leigh Tesfatsion. All Rights Reserved.

Agent-Based Computational Economics (ACE)
Research Area: Restructured Electricity Markets