Research on Renewable Energy Trading Strategies Based on Evolutionary Game Theory

Fei Huang, Hua Fan, Yunlong Shang, Yuankang Wei, Sulaiman Z. Almutairi, Abdullah M. Alharbi, Hengrui Ma, Hongxia Wang

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The authors construct a tripartite evolutionary game model that considers renewable energy, traditional coal-fired power plants, and market users. We propose multiple income matrices under different strategies, conduct evolutionary stability analysis, and form a series of assumptions that meet the stability of the game. We also simulate and analyze the impact of key factors—such as assessment costs, different pricing behaviors of coal-fired power plants, electricity prices of renewable energy, and green electricity demand—on the stability of the game. In addition, the market equilibrium points that can be achieved by optimizing trading strategies and their optimization status in promoting renewable energy consumption are analyzed. Based on the operational characteristics of the Guangxi electricity market in China and the trading situation of renewable energy, an evolutionary game method is applied to conduct empirical research. The trading behavior and evolution of all parties in the market are fully analyzed and are then applied to the construction and mechanism improvement of the electricity market.

Original languageEnglish
Article number2671
JournalSustainability (Switzerland)
Volume16
Issue number7
DOIs
StatePublished - Apr 2024

Keywords

  • electricity market
  • evolutionary game
  • renewable energy consumption
  • stability analysis

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