A Cooperative Game-based Optimal Dispatch Strategy for Multi-microgrids Integrating Renewable Uncertainty and Dual-Contribution Profit Allocation

Under review · Second author · Year not specified

Abstract

The coordinated operation of multi-microgrids (MMGs) is challenged by renewable energy uncertainty and the contributions of autonomous participants. This paper proposes a distributed cooperative optimization framework for MMGs. Wind and photovoltaic uncertainty is represented using Monte Carlo simulation (MCS), Kantorovich-distance-based scenario reduction, and Wasserstein distributionally robust optimization. An asymmetric Nash bargaining model is formulated for the multi-microgrid alliance (MGA). It maximizes the alliance-wide benefit while accounting for the cooperative gain of each microgrid (MG). Based on the principles of energy and carbon equity, the energy and carbon dimension asymmetric Nash bargaining mechanism is proposed to reflect the differentiated bargaining power of different MG. In the optimization objective, the comprehensive bargaining weights are determined according to both energy and low carbon contributions of each MG, while the peer-to-peer (P2P) electricity transaction quantities and prices are incorporated into the profit allocation process within the MGA. Case studies show that, under renewable energy uncertainty and integrated demand response, the total operating cost under cooperative operation is 45.11% lower than that under independent operation. Beyond this system-level cost reduction, the case studies further demonstrate that, compared with a profit-allocation scheme based solely on energy contribution, the proposed mechanism reallocates cooperative profits by jointly considering P2P electricity transactions and low-carbon performance, thereby improving allocation fairness and strengthening low-carbon incentives.

Keywords

Renewable Energy Uncertainty; Multi-Microgrids Coordination; Energy Contribution; Profit Allocation; Low Carbon Contribution