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An Evolutionary Game Theory Strategy for Carbon Emission Reduction in the Electricity Market

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  • Ryle S. Perera

    (Department of Applied Finance and Actuarial Studies, Faculty of Business and Economics, Macquarie University, Sydney, NSW 2109, Australia)

Abstract

We study how a government can manage a policy of environmental sustainability in a competitive electricity market. We assume that the government plays a Stackelberg game as leader, to study the evolutionary stable equilibria of the problem under this game theory paradigm. We then analyze a bimatrix coordination game to have many equilibria when no single power plant has incentives to deviate when the others reduce carbon emissions. In fact for power plants the adapted behavior is to avoid heavy tariffs, preserve the market share and minimize the environmental impact. We use the notion of quantal response equilibrium (QRE) in the case of bounded rationality to obtain a unique Nash equilibrium known as the centroid-dominant equilibrium of the game. This proposed quantitative framework can be applied by policy makers to determine incentives and tariffs to meet the environmental obligations in the electricity market.

Suggested Citation

  • Ryle S. Perera, 2018. "An Evolutionary Game Theory Strategy for Carbon Emission Reduction in the Electricity Market," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-20, December.
    • Handle: RePEc:wsi:igtrxx:v:20:y:2018:i:04:n:s0219198918500081
    DOI: 10.1142/S0219198918500081
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    Cited by:

    1. Meng Ding & Hui Zeng, 2022. "Multi-Agent Evolutionary Game in the Recycling Utilization of Sulfate-Rich Wastewater," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    2. Xinyi Xie & Liming Ying & Xue Cui, 2022. "Price Strategy Analysis of Electricity Retailers Based on Evolutionary Game on Complex Networks," Sustainability, MDPI, vol. 14(15), pages 1-17, August.
    3. İzgi, Burhaneddin & Özkaya, Murat & Üre, Nazım Kemal & Perc, Matjaž, 2023. "Extended matrix norm method: Applications to bimatrix games and convergence results," Applied Mathematics and Computation, Elsevier, vol. 438(C).
    4. Jieli Hu & Tieli Wang, 2023. "Strategies of Participants in the Carbon Trading Market—An Analysis Based on the Evolutionary Game," Sustainability, MDPI, vol. 15(14), pages 1-24, July.

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