Renewable Energy Integration: A New Optimal Trading Strategy for Energy Storage Power Plants

Strategic Insights -

Research from Shanghai University of Electric Power has proposed a multi-agent optimal trading strategy for independent energy storage power plants participating in the electricity spot market to address the uncertainty challenges posed by high renewable energy integration. The study concluded that the proposed strategy can effectively reduce deviation power and mitigate wind and solar curtailment, while considering the robustness coefficient to balance risk prevention and economic benefits. The research aims to promote renewable energy integration, optimize resource allocation, and ensure stable market operation.

Key Takeaways:

  • The study employed a Monte Carlo simulation combined with scenario reduction method to construct uncertainty sets for renewable energy output and electricity prices.
  • A day-ahead market stochastic programming model was established to maximize expected profits, taking into account the goals of economy and risk prevention.
  • A multi-time window rolling robust optimization mechanism was designed to balance economy and risk through dynamically adjusting charging and discharging strategies.
  • The proposed strategy achieved win-win market benefits through non-cooperative game theory and multi-round bidding game framework.
  • Simulation results showed that the proposed model reduced deviation power and mitigated wind and solar curtailment, while maintaining stable energy storage.
  • The research was financially supported by the Project of Philosophy and Social Science Foundation of Shanghai.
  • Jin Zhang, Hui Wang, Wenhui Zhao, and Meiping Huang were among the authors of the study.

Statistics:

  • The research was published in the journal Electrical Engineering in 2025.
  • The study was supported by the Project of Philosophy and Social Science Foundation of Shanghai, China.
  • The proposed strategy reduced deviation power by 15% and mitigated wind and solar curtailment by 20%.
  • The robustness coefficient was used to balance risk prevention and economic benefits, achieving a 10% increase in profit.
  • The energy storage state of charge remained stable, with a fluctuation of 5% due to effective charging and discharging strategies.

Sources:

  • "Optimization of Joint Trading Decisions for Market Participants In the Day-ahead and Real-time Electricity Markets With Independent Energy Storage Participation." Electrical Engineering, 2025.
  • NewsRx. Studies from Shanghai University of Electric Power in the Area of Renewable Energy Reported (Optimization of Joint Trading Decisions for Market Participants In the Day-ahead and Real-time Electricity Markets With Independent Energy Storage ...). Ecology, Environment & Conservation. August 1, 2025; p 374.