A Distributed Optimization and Revenue Allocation Approach for Multi-microgrids under Uncertain Environment

The interconnection of multi-microgrids (MMG) can effectively achieve the economic and flexible operation of microgrids (MG). However, the multi-energy coupling and the uncertain environment pose challenges to the steady operation of MMG. To optimize the operation, a methodology for distributed optimization and the allocation of revenue is provided. Firstly, the MMG system with multi-energy interaction is launched, and the distributionally robust chance constraint (DRCC) is utilized to address the uncertainties of MMG. Next, on the basis of bargaining games, the MMG peer-to-peer (P2P) transactions of electricity are established and solved by the alternating direction method of multipliers (ADMM) algorithm. Afterwards, a revenue allocation approach based on the Nash-Harsanyi bargaining game (NHBG) is developed to realize the equitable distribution of the revenue for the MMG cooperative operation. Finally, a case study is conducted to confirm the proposed model and approach. The findings demonstrate that the proposed method can effectively implement the fair and reasonable allocation of MG revenue while balancing economy and reliability.