Distributed Multi-microgrid Energy Dispatching Optimization Strategy Based on Cooperative Game

Microgrids, as a key technology for integrating distributed renewable energy and enhancing regional power supply reliability, are gradually evolving towards a distributed architecture with multi-agent collaboration. With the increasing penetration of intermittent energy sources such as photovoltaic and wind power, interconnected multi-microgrid systems have emerged as a crucial pathway for the low-carbon transition of modern power systems, enabling energy complementarity and load balancing. However, traditional centralized multi-microgrid systems lack efficient cross-regional coordination, making it difficult to balance local renewable energy consumption with overall cost optimization. Additionally, conflicts of interest among multiple stakeholders undermine cooperative stability, hindering the large-scale development of energy sharing. To address these challenges, this paper proposes a series of distributed energy scheduling optimization strategies for multi-microgrid systems. A cooperative game theory-based framework is introduced to facilitate multi-agent collaboration, incorporating dynamic models for the state of charge and state of health of energy storage systems to optimize their performance. The proposed strategy treats each microgrid as an independent intelligent agent capable of communicating with neighboring microgrids and exchanging surplus energy to achieve supply-demand balance and improve renewable energy utilization. A cooperative game model is established among multiple microgrids, and Nash bargaining is employed to coordinate energy transactions, generating an optimal distributed energy scheduling strategy. This approach provides a systematic solution to enhance the economic viability and sustainability of multi-microgrid systems.