Hybrid Game-Based Optimal Scheduling of Multiple Integrated Energy Microgrids Considering Distribution Network Constraints

With the increasing penetration of distributed renewable energy, coordinated operation between distribution networks and multiple integrated energy microgrids (IEMs) has become increasingly important for improving operational economy and maintaining system security. To address the insufficient integration of network constraints, P2P energy sharing, and contribution-based benefit allocation, this paper proposes a hybrid game-based optimal scheduling model for multi-IEM systems under distribution network constraints. In the upper level, a Stackelberg game is established between the distribution system operator (DSO) and the multi-IEM alliance to coordinate electricity trading and distribution network operation. In the lower level, an asymmetric Nash bargaining-based cooperative game is developed to enable peer-to-peer (P2P) energy sharing and allocate cooperative benefits according to the actual energy-sharing contributions of individual IEMs. Furthermore, a distributed solution framework combining the Success-History Adaptive Differential Evolution (SHADE) algorithm and an improved alternating direction method of multipliers (ADMM) is adopted to preserve data privacy and improve computational efficiency. Case studies based on the modified IEEE 33-bus distribution system demonstrate that the proposed method eliminates voltage violations and reduces network losses by 9.0%. Meanwhile, the proposed cooperative mechanism decreases the total operating cost of the IEM alliance by 7815.8 CNY and yields a more contribution-consistent profit allocation among participating microgrids. In addition, the improved ADMM reduces computation time by 42.1% compared with the conventional serial ADMM. The results demonstrate the effectiveness of the proposed method in enhancing distribution network security, promoting renewable energy sharing, and improving the economic performance of multi-IEM systems.