Electric Power Network Oligopoly as a Dynamic Stackelberg Game

Pedro A. Neto, Terry L. Friesz, Ke Han

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Over the last two decades, the electricity industry has shifted from regulation of monopolistic and centralized utilities towards deregulation and promoted competition. With increased competition in electric power markets, system operators are recognizing their pivotal role in ensuring the efficient operation of the electric grid and the maximization of social welfare. In this article, we propose a hypothetical new market of dynamic spatial network equilibrium among consumers, system operators and electricity generators as solution of a dynamic Stackelberg game. In that game, generators form an oligopoly and act as Cournot-Nash competitors who non-cooperatively maximize their own profits. The market monitor attempts to increase social welfare by intelligently employing equilibrium congestion pricing anticipating the actions of generators. The market monitor influences the generators by charging network access fees that influence power flows towards a perfectly competitive scenario. Our approach anticipates uncompetitive behavior and minimizes the impacts upon society. The resulting game is modeled as a Mathematical Program with Equilibrium Constraints (MPEC). We present an illustrative example as well as a stylized 15-node network of the Western European electric grid.

Original languageEnglish (US)
Pages (from-to)1211-1241
Number of pages31
JournalNetworks and Spatial Economics
Volume16
Issue number4
DOIs
StatePublished - Dec 1 2016

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Electricity
Deregulation
Profitability
Costs
Industry
Power markets

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

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Electric Power Network Oligopoly as a Dynamic Stackelberg Game. / Neto, Pedro A.; Friesz, Terry L.; Han, Ke.

In: Networks and Spatial Economics, Vol. 16, No. 4, 01.12.2016, p. 1211-1241.

Research output: Contribution to journalArticle

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