Multi-objective Optimization Game Scheduling Method for Distributed Shared Energy Storage in Active Distribution Network

In order to solve the problems of low utilization efficiency and unclear transaction mechanism of distributed energy storage in active distribution network (ADN), this paper proposes unified management of shared energy storage operators (SESO), taking into account SESO benefits and ADN benefits, and establishes SESO and ADN multi-objective optimization model of Stackelberg game. First, the Stackelberg gam framework of SESO and ADN is introduced, and then a mathematical model is established in which the leader SESO has the greatest economic benefits and the follower ADN has the smallest operating cost and carbon emissions. It is solved using the particle swarm algorithm and verified and analyzed through the IEEE33 node power distribution system. The results show that compared with the independent operation mode, the distributed energy storage shared operation mode of the proposed strategy has improved energy storage utilization efficiency, improved economic benefits, and reduced ADN operating costs and carbon emissions.