Dynamic Game-Theoretic Models of Electric Power Markets and their Vulnerability

  • Hobbs, Benjamin (PI)
  • Friesz, Terry Lee (CoPI)
  • Pang, Jong Shi (CoPI)
  • Harrington, Joseph (CoPI)

Project: Research project

Project Details

Description

The issues of market power, generation adequacy, and vulnerability in

network-constrained electric power markets are of increasing concern to

market participants, policy makers, and the general public. Although

price formation and investment are inherently dynamic processes, they

are usually studied using static economic and game theoretic models.

This disregarding of lags, expectations, and adjustment processes may

yield distorted conclusions about the effects of proposed changes to

market structure and designs. To investigate and overcome this

distortion, there is a need for (a) realistic models of dynamic

interactions among strategically behaved electric power market

participants, and (b) the design of efficient computational

methods that can handle the high dimensionality of realistic

power systems.

The proposed research and pedagogy have four objectives:

a) formulation of dynamic game theoretic models of pricing and generation

for transmission-constrained electric power markets, for a variety of

competitive circumstances and market structures

b) development of efficient algorithms for solving the models

c) demonstration and testing of models and algorithms using realistic data

d) development of educational curricula integrating game theory,

economics,

and electric power systems.

The project has several broader impacts, including contributions to

education and public policy. We will develop curricular offerings

in dynamic optimization and differential games for the modeling of

electric power markets. This material will be made available as a

professional tutorial and distributed to the educational community

via the project website. Our models hold the potential of

significantly enhancing the capability of regulatory agencies,

market operators, and stakeholders.

StatusFinished
Effective start/end date9/15/028/31/06

Funding

  • National Science Foundation: $430,007.00

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