• Chen-Ching Liu (Project PI, Professor and Deputy Principal, College of Engineering, Mathematical, and Physical Sciences, National University of Ireland, Dublin)
  liu AT ucd.ie
• Leigh Tesfatsion (Project PI, Professor of Econ, Math, and ECpE, ISU, Heady 375, 515-294-7318)
  tesfatsi AT iastate.edu
• Nanpeng Yu (EPRC Forecasting Project RA, Start Date 1/14/08; ISU ECpE Ph.D. Candidate, Coover 1121, 515-294-9338, Cell: 515-708-5277)
  eric.ynp AT gmail.com
• Qun Zhou (EPRC Forecasting Project RA, Start Date 8/20/07, ISU ECpE Ph.D. Candidate, Coover 3108, Cell: 515-509-1525)
  zhouqun8508 AT gmail.com

• Jorge Sierrra (EPRC Industry Project Advisor, Power Market Research, National Energy Dispatch Center, XM S.A. E.S.P, Tel: +57 (4) 315 7948, Fax: +57 (4) 317 0833)
  jsierra AT xm.com.co
• Hongyan Li (EPRC MISO Energy Project RA, ISU ECpE Ph.D. Candidate, Coover 1131, 515-294-2525, Cell: 515-441-1763)
  lihy AT iastate.edu
• Abhishek Somani (NSF RA, ISU Econ Ph.D. Candidate, Start Date 8/07)
  somaniabhishek AT yahoo.com
• Junjie Sun (Financial Economist, OCC, U.S. Treasury; ISU Econ Ph.D. 2007)
  junjie.sun AT occ.treas.gov

Current Project Support

EPRC Forecasting Project:

Sponsor: Electric Power Research Center (EPRC)

Title: "Forecasting Grid Congestion for Transmission Grid Operation and Investment"

Principle Investigators: Chen-Ching Liu and Leigh Tesfatsion

Date of Award: Funding Start Date - August 2007

Duration of Award: Three years (conditional on successful end-of-year progress reviews)

Related EPRC Risk Management Project:

Sponsor: Electric Power Research Center (EPRC)

Title: "Financial and Operational RIsk Management for Restructured Wholesale Power Markets"

Principle Investigators: Leigh Tesfatsion

Date of Award: Funding Start Date - August 2009

Duration of Award: Three years (conditional on successful end-of-year progress reviews)

Related EPRC MISO Energy Project:

Sponsor: Electric Power Research Center (EPRC)

Title: "Testing the Efficiency and Reliability Impacts of MISO's Midwest Market Initiative"

Principle Investigators: Leigh Tesfatsion (Lead PI) and Herman C. Quirmbach

Date of Award: Funding Start Date - August 2006

Duration of Award: Three years (conditional on successful end-of-year progress reviews)

Project Interim Reports

• EPRC Forecasting Project: 2009 Interim Report (pdf,428K), Last Updated: April 2009.

• EPRC Forecasting Project: 2009 Interim Report -- Slide Presentation (pdf,456K), Last Updated: May 2009.

Recent Project-Related Publications and Working Papers (By Date of Posting)

• Hongyan Li and Leigh Tesfatsion, "Development of Open Source Software for Power Market Research: The AMES Test Bed" (pdf preprint,601K), Journal of Energy Markets, Vol. 2, No. 2, Summer 2009.

  Abstract: This study discusses potential benefits and drawbacks of developing open-source software for power market research, using the AMES Wholesale Power Market Test Bed for concrete illustration.

• Hongyan Li and Leigh Tesfatsion, "The AMES Wholesale Power Market Test Bed: A Computational Laboratory for Research, Teaching, and Training" (pdf,930K), IEEE Proceedings, Power and Energy Society General Meeting, Calgary, Alberta, CA, July 26-30, 2009.
  Abstract: Wholesale power markets around the world are currently undergoing a controversial restructuring of their architecture and rules of operation. Some commentators have argued that restructuring has not produced the intended improvements in market efficiency while at the same time it has complicated efforts to ensure reliability and fairness of operations. This situation suggests the desirability of having publicly available test beds suitable for the objective study of this restructuring process. This study reports on the AMES Wholesale Power Market Test Bed. AMES is an open-source agent-based computational laboratory designed for the systematic study of restructured wholesale power markets operating over AC transmission grids subject to congestion. The AMES traders have learning capabilities permitting them to evolve their trading strategies over time. The potential usefulness of AMES for research, teaching, and training purposes is discussed and illustrated.

  Haifeng Liu, Leigh Tesfatsion, and A. A. Chowdhury, "Derivation of Locational Marginal Prices for Restructured Wholesale Power Markets", Journal of Energy Markets, Vol. 2, No. 1, Spring 2009, 3-27.

  Note: An abridged version of this paper was presented at the IEEE Power and Energy Society General Meeting, Calgary, CA, July 26-30, 2009.

  Abstract: Although Locational Marginal Pricing (LMP) plays an important role in many restructured wholesale power markets, the detailed derivation of LMPs as actually used in industry practice is not readily available. This lack of transparency greatly hinders the efforts of researchers to evaluate the performance of these markets. In this paper, different AC and DC optimal power flow (OPF) models are presented to help understand the derivation of LMPs. As a byproduct of this analysis, we are able to provide a rigorous explanation of the basic LMP and LMP-decomposition formulas (neglecting real power losses) presented without derivation in the business practice manuals of the U.S. Midwest Independent System Operator (MISO).

  Qun Zhou, Leigh Tesfatsion, and Chen-Ching Liu, "Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets" (pdf,176K), IEEE Proceedings, Power Systems & Exposition Conference, Seattle, WA, March 15-18, 2009.

  Abstract: In current restructured wholesale power markets, the short length of time series for prices makes it difficult to use empirical price data to test existing price forecasting tools and to develop new price forecasting tools. This study therefore proposes a two-stage approach for generating simulated price scenarios based on the available price data. The first stage consists of an Autoregressive Moving Average (ARMA) model for determining scenarios of cleared demands and scheduled generator outages (D&O), and a moment-matching method for reducing the number of D&O scenarios to a practical scale. In the second stage, polynomials are fitted between D&O and wholesale power prices in order to obtain price scenarios for a specified time frame. Time series data from the Midwest ISO (MISO) are used as a test system to validate the proposed approach. The simulation results indicate that the proposed approach is able to generate price scenarios for distinct seasons with empirically realistic characteristics.

  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.

  Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Dynamic LMP Response Under Alternative Price-Cap and Price-Sensitive Demand Scenarios" (pdf,465K), IEEE Proceedings, Power and Energy Society General Meeting, Pittsburgh, July 20-24, 2008.

  Abstract: This study investigates the complicated nonlinear effects of demand-bid price sensitivity and supply-offer price caps on Locational Marginal Prices (LMPs) for bulk electric power when profit-seeking generators can learn over time how to strategize their supply offers. Systematic computational experiments are conducted using AMES, an open-source agent-based test bed developed by the authors. AMES models a restructured wholesale power market operating through time over an AC transmission grid subject to line constraints, generation capacity constraints, and strategic trader behaviors.

  Nanpeng Yu, Chen-Ching Liu, and Leigh Tesfatsion, "Modeling of Suppliers’ Learning Behaviors in an Electricity Market Environment" (pdf,277K), International Journal of Engineering Intelligent Systems, vol. 15, no. 2, pp. 115-121, 2007.

  Abstract: The Day-Ahead electricity market is modeled as a multi-agent system with interacting agents including supplier agents, Load Serving Entities and a Market Operator. Simulation of the market clearing results under the scenario in which agents have learning capabilities is compared with the scenario where agents report true marginal costs. It is shown that, with Q-Learning, electricity suppliers are making more profits compared to the scenario without learning due to strategic gaming. As a result, the LMP at each bus is substantially higher.

  Guang Li, Chen-Ching Liu, Chris Mattson, and Jacques Lawarrée, "Day-Ahead Electricity Price Forecasting in a Grid Environment", IEEE Transactions on Power Systems, Volume 22, No. 1, February 2007.

  Abstract: This article applies various forecasting techniques to different time horizons for electricity price forecasting in locational marginal pricing (LMP) spot markets. Available correlated data are selected to improve the short-term forecasting performance. Fuzzy inference systems (FIS), least-squares estimation (LSE), and a combination of FIS and LSE are proposed as forecasting techniques. Based on extensive comparative testing against a variety of more standard forecasting techniques, it is concluded that LSE provides the most accurate results while FIS, which is also highly accurate, provides transparency and interpretability.

  Junjie Sun and Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design" (pdf,724K), IEEE Proceedings, Power and Energy Society 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", Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025 (pdf,2.2MB).

  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, and the Southwest, and adopted for implementation in California. Strong opposition to the WPMP persists among some industry stakeholders, however, due in part 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.

  Junjie Sun and Leigh Tesfatsion, "Open-Source Software for Power Industry Research, Teaching, and Training: A DC-OPF Illustration" (pdf,115K), IEEE Proceedings, Power and Energy Society General Meeting, Tampa, Florida, June 2007.

  Abstract: This proceedings paper is a brief summary of ISU Economics Working Paper No. 06014 (see below). It reports on the development and implementation of a stand-alone open-source Java solver for DC optimal power flow (DC-OPF) problems suitable for research, teaching, and training purposes. The DC-OPF solver is shown to match or exceed the accuracy of BPMPD (a proprietary third-party QP solver highly recommended by MatPower) when tested on a public repository of small to medium-sized QP problems. The capabilities of the DC-OPF solver are illustrated for a 5-node DC-OPF test case commonly used for training purposes.

  Junjie Sun and Leigh Tesfatsion, "DC Optimal Power Flow Formulation and Testing Using QuadProgJ" (pdf,526K), ISU Economics Working Paper No. 06014, Department of Economics, Iowa State University, Revised October 2007.

  Abstract: Under a set of simplifying assumptions, a nonlinear AC Optimal Power Flow (OPF) problem can be approximated by a linearized DC OPF problem to solve for power quantities and locational marginal prices in restructured electric wholesale power markets. We first establish that a commonly used DC OPF approximation in per unit form can be represented as a strictly convex quadratic programming (SCQP) problem subject to mixed equality and inequality constraints, given a physically meaningful Lagrangian augmentation. We then show how this SCQP problem can be solved using QuadProgJ, a Java SCQP solver newly developed by the authors that implements the well-known dual active-set SCQP algorithm by Goldfarb and Idnani (1983). QuadProgJ appears to be the first open-source SCQP solver developed completely in Java. QuadProgJ is specifically designed for the fast and efficient desktop solution of SCQP problems for research and training purposes with a maximum count of about 1500 decision variables plus constraints. Several numerical examples are provided to illustrate the accuracy of QuadProgJ, including 3-node and 5-node DC OPF case studies taken from power systems texts and ISO-NE/PJM training manuals.

Open-Source Software Under Development for Project Use

AMES Wholesale Power Market Test Bed (Java): A Free Open-Source Computational Laboratory for the Agent-Based Modeling of Electricity Systems

The AMES Wholesale Power Market Test Bed (Java), developed by Hongyan Li (ISU), Junjie Sun (OCC, U.S. Treasury), and Leigh Tesfatsion (ISU), is an extensible and modular agent-based computational laboratory for the systematic experimental study of restructured wholesale power markets. AMES models strategic traders with learning capabilities interacting within an ISO-managed wholesale power market operating over an AC transmission grid subject to congestion effects. Congestion on the grid is managed by means of locational marginal prices derived from bid/offer-based optimal power flow solutions. AMES is a free open-source tool suitable for research, teaching, and training applications. 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. AMES is an acronym for Agent-based Modeling of Electricity Systems.



DCOPFJ (Java): A Free Open-Source Solver for DC Optimal Power Flow Problems

The DCOPFJ Package (Java), developed by Junjie Sun (OCC, U.S. Treasury) and Leigh Tesfatsion (ISU), is a free open-source stand-alone solver for small to medium-sized DC optimal power flow problems having a strictly convex quadratic programming (SCQP) formulation. The DCOPFJ package incorporates an SCQP solver (QuadProgJ) wrapped in an outer SI-to-PU data processing shell. QuadProgJ implements the well-known dual active-set SCQP algorithm developed by Goldfarb and Idnani (1983). QuadProgJ has been shown to match or exceed the accuracy of the proprietary C-language QP solver BPMPD (highly recommended by MATPOWER) when tested on a public repository of small to medium-sized SCQP problems. The DCOPFJ package has been successfully run on DC-OPF test cases commonly used for training purposes.

Project-Related Presentations to External Groups (Ordered by Date of Presentation)

• Leigh Tesfatsion, "Auction Basics for Wholesale Power Markets: Objectives and Pricing Rules", IEEE Power and Energy Society General Meeting, Calgary, CA, July 26-30, 2009.

• Hongyan Li and Leigh Tesfatsion, "The AMES Wholesale Power Market Test Bed: A Computational Laboratory for Research, Teaching, and Training", IEEE Power and Energy Society General Meeting, Calgary, CA, July 26-30, 2009.

• Hongyan Li and Leigh Tesfatsion, "Development of Open Source Software for Power Market Research: An Illustrative Case Study", IEEE Power and Energy Society General Meeting, Calgary, CA, July 26-30, 2009.

• Haifeng Liu, Leigh Tesfatsion, and A. A. Chowdhury, "Locational Marginal Pricing Basics for Restructured Wholesale Power Markets", IEEE Power and Energy Society General Meeting, Calgary, CA, July 26-30, 2009.

• Leigh Tesfatsion, "Stress Testing Institutional Arrangements via Agent-Based Modeling: Illustrative Results for U.S. Power Markets", ICES/Department of Economics, George Mason University, Fairfax, VA, April 3, 2009.

• Qun Zhou, Leigh Tesfatsion, and Chen-Ching Liu, "Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets", IEEE Power Systems Conference & Exposition, Seattle, WA, March 15-18, 2009.

• Hongyan Li and Leigh Tesfatsion, "Capacity Withholding in Restructured Wholesale Power Markets: An Agent-Based Test Bed Study", IEEE Power Systems Conference & Exposition, Seattle, WA, March 15-18, 2009.

• Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Dynamic LMP Response Under Alternative Price-Cap and Price-Sensitive Demand Scenarios", Institute for Operations Research and Management Science (INFORMS), Washington DC, October 12-15, 2008.

• Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Dynamic LMP Response Under Alternative Price-Cap and Price-Sensitive Demand Scenarios", IEEE Power and Energy Society General Meeting, David L. Lawrence Convention Center, Pittsburgh, PA, July 21-24, 2008.

• Nanpeng Yu and Chen-Ching Liu, "Multi-Agent Systems and Electricity Markets: State-of-the-Art and the Future", IEEE Power and Energy Society General Meeting, David L. Lawrence Convention Center, Pittsburgh, PA, July 20-24, 2008.

• Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Dynamic Price Response Under Alternative Price-Cap and Price-Sensitive Demand Scenarios", Summer North American Meetings of the Econometric Society, Carnegie Mellon University, Pittsburgh, PA, June, 2008.

• Hongyan Li, Junjie Sun, and Leigh Tesfatsion, "Dynamic LMP Response Under Alternative Price-Cap and Price-Sensitive Demand Scenarios", International Industrial Organization Conference, Washington, D.C., May 16-18, 2008.

• Leigh Tesfatsion, "Agent-Based Test Beds for Critical Infrastructure Research, Teaching, and Training", Department of Energy - National Renewable Energy Laboratory (DOE-NREL), Washington, D.C., February 22, 2008.

• Lynne Kiesling and Leigh Tesfatsion, "A Test Bed for the Integrated Experimental Study of Retail and Wholesale Power Market Designs: Seaming GridLab-D with AMES", Tele-Seminar and Webcast, sponsored by the Pacific Northwest National Laboratory (PNNL), February 15, 2008.

• Leigh Tesfatsion, "Agent-Based Test Beds for Power Industry Research, Teaching, and Training", Tele-Seminar and Webcast, sponsored by the Power Systems Energy Research Center (PSERC), Cornell University, February 5, 2008.

• Leigh Tesfatsion, "Agent-Based Test Beds for Critical Infrastructure Research, Teaching, and Training", Plenary Address, AGENT 2007, Northwestern University, November 17, 2007.

• Nanpeng Yu, "Modeling of Suppliers' Learning Behaviors in an Electricity Market Environment", 14th International Conference on Intelligent Systems Applications to Power Systems (ISAP 2007), Kaohsiung, Taiwan, November 5, 2007.

• Leigh Tesfatsion, "Open-Source Software for Power Industry Research, Teaching, and Training: A DC-OPF Illustration", IEEE Power and Energy Society General Meeting, Tampa, Florida, June 25-28, 2007.

• Leigh Tesfatsion, "An Agent-Based Computational Laboratory for Wholesale Power Market Design", IEEE Power and Energy Society General Meeting, Tampa, Florida, June 25-28, 2007.

• Junjie Sun, "Dynamic Testing of Wholesale Power Market Designs: An Agent-Based Computational Approach", North American Meetings of the Econometric Society, Duke University, Durham, NC, June 21-24, 2007.

• Junjie Sun, "Dynamic Testing of Wholesale Power Market Designs: An Agent-Based Computational Approach", 13th International Conference on Computing in Economics and Finance, Society for Computational Economics, Montreal, Canada, June 14-16, 2007.

• Junjie Sun, "Dynamic Testing of Wholesale Power Market Designs: An Agent-Based Computational Approach", 5th Annual International Industrial Organization Conference (IIOC), Savannah, Georgia, April 14-15, 2007.

• Leigh Tesfatsion, "Agent-Based Computational Economics: A Constructive Approach to Economic Theory" Allied Social Science Associations (ASSA) Annual Meeting, Chicago, IL, January 5-7, 2007.

• Leigh Tesfatsion and Junjie Sun, "Agent-Based Test Beds for Market Design", Allied Social Science Association (ASSA) Annual Meeting, Chicago, IL, January 5-7, 2007.

Background Readings

• FERC, "Final Report to Congress on Competition in the Wholesale and Retail Markets for Electric Energy" (pdf,1.6M), U.S. Federal Energy Regulatory Commission. Accessed: April 27, 2007. See, also, the comment on an earlier draft of this report released on 6/26/06 by Lynne Kiesling and Michael Giberson (Mercatus Center, George Mason University).
  Abstract: This report, required by Secton 1815 of the Energy Policy Act of 2005, provides an overview and summarizes progress in the U.S. toward wholesale and retail competition over the past 25 years, the current state of wholesale and retail competition in the U.S., and the economic and political issues surrounding the transition to wholesale and retail competition.

  Timothy J. Brennan, Karen L. Palmer, and Salvador A. Martinez, Alternating Currents: Electricity Markets and Public Policy, Resources for the Future, Washington, D.C., 2002.

  Abstract (from the book jacket): "(This book) provides a timely (nontechnical) overview and analysis of the concerns facing industry regulators, legislators, and others as they consider whether, when, and how to open electricity markets. (The authors) offer background on the history of regulatory policy and the technology for producing and delivering electric power. They then provide insights into the policy degates and economic issues involved in eleven important topics, including industry structure, system integrity and reliability, the mitigation of market power, and environment protection."

  Jack Casazza and Frank Delea, Understanding Electric Power Systems: An Overview of the Technology and the Marketplace, IEEE Press, Wiley-Interscience, 2003.

  Abstract: "(This book) bridges the gaps 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."

  William W. Hogan, "Market Design and Electricity Restructuring" (pdf,209K), Presentation to the Association of Power Exchanges (APEx), 2005 Annual Conference, Orlando, Florida, November 1, 2005.

  Abstract: The author reviews the tortured history of electricity restructuring in the U.S. and outlines the requirements for SMD ("Successful Market Design").

  Paul Joskow, "Markets for Power in the United States: An Interim Assessment" (pdf,5.4MB), The Energy Journal, Volume 27, Number 1, 2006, pp. 1-36.

  Abstract: "The transition to competitive wholesale and retail markets for electricity in the U.S. has been a difficult and contentious process. This paper examines the progress that has been made in the evolution of wholesale and retail electricity market institutions. Various indicia of the performance of these market institutions are presented and discussed. Significant progress has been made on the wholesale competition front but major challenges must still be contronted. The framework for supporting retail competition has been less successful, especially for small customers. Empirical evidence suggests that well-designed competitive market reforms have led to performance improvements in a number of dimensions and benefited customers through lower retail prices.

  Mohammad Shahidehpour, Hatim Yamin, and Zuyi Li, Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management, IEEE Wiley Interscience, John Wiley & Sons, Inc., 2002.

  Abstract: Topics covered in this book include: market structure and operation of electric power systems; load and price forecasting and arbitrage; price-based unit commitment and security constrained unit commitment; market power analysis and game theory applications; ancillary services auction market design; and transmission pricing and congestion.

  Lizhi Wang, "Using a System Model to Decompose the Effects of Influential Factors on Locational Marginal Prices", IEEE Transactions on Power Systems, Volume 22, No. 4, November 2007.

  Abstract: Locational marginal prices (LMPs) are influenced by various factors such as load uncertainty, thermal limit, capacity reserve, and market power. This paper develops a method to quantitatively analyze the effects of these individual factors and their interactions on the mean and standard deviations of the LMPs. This decomposition method is used to address two questions: (1) To what extent does market power raise the LMPs above marginal cost; and (2) what effects will generation or transmission capacity expansion have on relieving high LMPs under alternative demand scenarios? Findings are illustrated using an IEEE 30-bus test system.

Key Online Data Resources

• MISO Market Reports Site

• MISO Day-Ahead Reports

  • For a detailed explanation of the data provided in the following day-ahead reports, see the Day-Ahead Report Readers Guide.

  • MISO Day-Ahead Market Cleared Bids
    Data Description: Cleared bids data is posted in daily files. There are four types of cleared bids, represented by D, I, P or F. D stands for decrease (decrements), which are virtual bids. I stands for increase (increments), which are treated as negative virtual bids. F stands for fixed, which are physical (as opposed to virtual) fixed price bids. P stands for price sensitive, which are physical (as opposed to virtual) bids with price curves.

    MISO Day-Ahead Market Cleared Offers

    Data Description: These files provide cleared hourly day-ahead offer data for the Midwest ISO energy market.

    MISO Expanded Day-Ahead Reports

    Data Description: These expanded day-ahead reports give daily cleared demand (in GW, classified as physical-fixed, physical-price sensitive, virtual), cleared supply (in GW, classified as physical, virtual), and offered generation resources (in GW, divided into self-scheduled, must run, economic, emergency).

    MISO Historical Day-Ahead Market LMPs

    Data Description: These daily files provide Day-Ahead Market LMPs for each hour of the day. Two components of LMP -- the Marginal Congestion Component (MCC) and the Marginal Loss Component (MLC) -- are also reported.

• MISO Day-Ahead Pricing Reports

  • For a detailed explanation of the data provided in the MISO Day-Ahead Pricing Reports, see the Day-Ahead Pricing Report Readers Guide.

  • MISO Day-Ahead Market Pricing Reports
    Data Description: These day-ahead pricing reports provide hourly-level summaries of the pricing results of the day-ahead market for the Midwest ISO system and associated hubs. The highest, lowest, and average LMP for the Midwest ISO system are all displayed.

• MISO Real-Time Reports

  • For a detailed explanation of the data provided in the following reports, see the Expanded Real-Time Report Readers Guide.

  • MISO Expanded Real-Time Market Reports
    Data Description: These daily files compare economic maximum, load, net scheduled imports, outages, and offers of total economic maximum based on the Forward Reliability Assessment Commitment for the MISO Real-time Market.

    MISO Real-Time Market Cleared Offers

    Data Description: These files provide cleared 5-minute real-time offer data for the Midwest ISO energy market.

    MISO Historical Real-Time Market LMPs

    Data Description: These daily files provide Real-Time Market LMPs for each hour of the day. Two components of LMP -- the Marginal Congestion Component (MCC) and the Marginal Loss Component (MLC) -- are also reported.

• MISO Real-Time Pricing Reports

  • For a detailed explanation of the data provided in the following real-time pricing reports, see the Real-Time Pricing Report Readers Guide.

  • MISO Real-Time Market Pricing Reports
    Data Description: These real-time pricing reports provide hourly-level summaries of pricing results for the real-time market for the Midwest ISO system and its associated hubs.

• The Midwest Independent System Operator (MISO) Maintains a MISO Dynamic LMP Contour Map for real-time LMPs, updated every five minutes, accompanied by real-time and day-ahead LMP information in tabular form. The LMPs (real-time and day-ahead) are decomposed into loss (MLC), congestion (MCC), and energy (LMP - MLC - MCC) components. Congested areas of the MISO footprint are indicated by use of a differently colored "heat map." Congestion and demand conditions underlying the displayed LMP patterns can be accessed at the MISO Real-Time Market Information Site.
  Note: Viewing the contour map at this site requires the free installation of Adobe's SVG Viewer; a link to this viewer is provided at the above site.

  The New England Independent System Operator (ISO-NE) maintains ISO-NE Dynamic LMP Contour Maps for both day-ahead and real-time LMPs, refreshed every five minutes. Note: Viewing the contour maps at this site requires a Java-enabled browser.

  The New York Independent System Operator (NYISO) maintains NYISO LMP Contour Maps for both day-ahead and real-time LMPs, refreshed every two minutes. Note: Viewing the contour maps at this site requires a Java-enabled browser.

Other Online Resource Materials

• General Resources on Electricity Restructuring

• Agent-Based Computational Electricity Research

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

• The PowerWorld Simulator, a licensed energy model developed by PowerWorld Inc., is an interactive package for the analysis of power systems. In addition to optimal AC and DC power flows, it provides detailed modeling of LTC (load tap changer) and phase-shifting transformers, switched shunts, generator reactive capability curves, generator cost curves, load schedules, transaction schedules, dc lines, multi-section lines, and remote bus voltage control. There is also an attempt to include economic data into the power flow solution to evaluate the economic importance of a system change. A demonstration model can be obtained at the PowerWorld site free of charge.

Miscellaneous

• Steven Jones, "Power Switch: Software Looks to be Better Test of Wholesale Power Markets", Around LAS, Iowa State University, October 15, 2007.
  Note: Media report on the development of the AMES Market Test Bed by research team Hongyan Li, Junjie Sun, and Leigh Tesfatsion.