Research on regulation strategy of integrated energy system based on game theory and divide-and-conquer algorithm

• Published in: Energy (Oxford) Vol. 319; p. 134860
• Main Authors: Wu, Yanjuan, Jin, Pengfei, Li, Qing
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.03.2025
• Subjects: algorithms; carbon; case studies; Divide-and-conquer algorithm; Electricity market regulation; energy; game theory; hybrids; Integrated energy system; issues and policy; Non-cooperative game; Stackelberg game; stakeholders; Integrated energy system; Electricity market regulation; Non-cooperative game; Stackelberg game; Divide-and-conquer algorithm
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2025.134860

Integrated energy system is an energy supply method that enables the complementary and efficient utilization of multiple energy sources. However, integrated energy system involves multiple stakeholders, including the integrated energy operator, energy storage system, and energy user. Their behaviors can lead to reduced system benefits, increased carbon emissions, and even violations. To address the above issues, an integrated energy system hybrid game model with the participation of the regulatory agency is constructed, and a divide-and-conquer algorithm is proposed to solve it. Firstly, this study establishes a Stackelberg game model to analyze the interactions among participants within the system and formulates a non-cooperative game model to investigate the relationship between integrated energy system and regulatory agency. Then, game theory is combined with the divide-and-conquer algorithm to solve the hybrid game model, evaluating the optimal strategies for the integrated energy operator as the leader, the energy storage system and energy user as followers under regulatory agency's interventions. Finally, a case study is conducted to analyze the regulatory agency's goal of maximizing overall system benefits and environmental benefits. By analyzing the impacts of various regulatory strategies on the system, this study provides actionable decision support and policy recommendations for the regulatory agency. •Regulatory optimization model for energy operators, storage systems and users.•Game theory model analyzes energy system interactions between system participants and regulatory agencies.•Novel solution method that combines game theory with divide-and-conquer algorithm.•Evaluating regulatory strategies using a multiple performance index framework.