A Master–Slave Game-Based Strategy for Trading and Allocation of Virtual Power Plants in the Electricity Spot Market

Na Yang, Liuzhu Zhu, Bao Wang, Rong Fu (), Ling Qi, Xin Jiang and Chengyang Sun
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Na Yang: Economic and Technical Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230038, China
Liuzhu Zhu: Economic and Technical Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230038, China
Bao Wang: Economic and Technical Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230038, China
Rong Fu: College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Ling Qi: College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Xin Jiang: College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Chengyang Sun: College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Energies, 2025, vol. 18, issue 2, 1-19

Abstract: With the transformation of the energy structure, the integration of numerous small-scale, widely distributed renewable energy sources into the power grid has introduced operational safety challenges. To enhance the operational competitiveness, the virtual power plant (VPP) has emerged to aggregate and manage these distributed energy resources (DERs). However, current research on the VPP’s frequency modulation performance and bidding strategy remains insufficient in the joint market of electrical energy and frequency modulation (FM) ancillary services, with inadequate coordination of internally distributed resources. To fully leverage the flexibility of VPPs and incentivize their participation in electricity market operations, this paper investigates game-based bidding strategies and internal distributed resources allocation methods for VPPs in the joint market for electrical energy and frequency ancillary services. Firstly, the regulatory performance indicators of VPPs participating in the joint market and develops the corresponding market-clearing model. Secondly, to address the competition among distributed resources within VPPs, a master-slave game approach is innovatively employed to optimize the VPP’s trading strategies. This method ensures the rational allocation of electricity consumption among distributed energy resources within the VPP and derives the optimized bidding prices and quantities for both the VPP and its internal members. Finally, the case study shows that the proposed trading strategy provides effective bidding strategies for distributed energy resources participating in the joint market for energy and frequency regulation ancillary services. It enhances the regulatory performance of VPPs in the energy-frequency regulation market, ensures the profitability of distributed energy resources, and contributes to the economically stable operation of the market.

Keywords: virtual power plant; distributed energy resources; master–slave game; the joint market of electric energy and FM ancillary service; market-clearing price (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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