Two new working papers by Tesfatsion

April 28, 2021

Dr. Leigh TesfatsionLeigh Tesfatsion, professor emerita, has two new working papers. They are:

Leigh Tesfatsion (2021), Agent-Based Computational Economics: Overview and Brief History, WP #21004, Economics Working Paper Series, ISU Digital Repository, Iowa State University, Ames, IA.

    Abstract: Scientists seek to understand how real-world systems work. Models devised for scientific purposes must always simplify reality. However, scientists should be permitted to tailor these simplifications to purposes at hand; they should not be forced to distort reality in specific predetermined ways in order to apply a modeling approach. Adherence to this modeling precept was a key goal motivating my development of Agent-Based Computational Economics (ACE), a variant of agent-based modeling characterized by seven specific modeling principles. This perspective provides an overview of ACE and a brief history of its development.

Rui Cheng, Leigh Tesfatsion, and Zhaoyu Wang (2021), "A Multiperiod Consensus-Based Transactive Energy System for Unbalanced Distribution Networks,” WP #21005, Economics Working Paper Series, ISU Digital Repository, Iowa State University, Ames, IA.

    Abstract: This study develops a consensus-based transactive energy system design managed by an independent distribution system operator (DSO) for an unbalanced radial distribution network. The network is populated by welfare-maximizing customers with price-sensitive and fixed (non-price-sensitive) demands who make multiple successive power decisions during each real-time operating period OP. The DSO and customers engage in an iterative negotiation process in advance of each OP to determine retail price-to-go sequences for OP that align customer power decisions with network reliability constraints in a manner that respects customer privacy. The convergence properties of a dual decomposition algorithm developed to implement this negotiation process are analytically established. A case study is presented for an unbalanced 123-bus radial distribution network populated by household customers that demonstrates the practical effectiveness of the design.