Multi-agent collaborative pricing and scheduling strategy for active distribution network considering internal interaction of microgrid coalition

High renewable penetration necessitates the coordination of microgrids within active distribution networks to ensure economic and stable operation. This paper proposes a Stackelberg game optimization model between the Distribution System Operator and a Microgrid Coalition. Using fixed-point theory to describe pricing strategies, the model introduces a power interaction mechanism based on “surplus/shortage” states to enable internal energy sharing. In addition, a benefit allocation scheme based on interaction proportions is designed to balance fairness. A distributed iterative algorithm combining quantum particle swarm optimization and CPLEX is developed to efficiently solve the equilibrium while preserving privacy. Simulations on an improved IEEE-33 system demonstrate that the strategy effectively reduces costs, promotes renewable consumption, and enhances voltage quality.