Optimization of Shared Energy Storage Capacity for Multi-microgrid Operation with Flexible Loads and Economic Dispatch

Currently, the investment cost of energy storage devices is relatively high, while the utilization rate is low. Therefore, it is necessary to use energy storage stations to avoid market behavior caused by abandoned wind and solar power. Therefore, this article studies the capacity configuration of shared energy storage systems in multi-microgrids, which is of great significance in effectively improving the consumption level of distributed energy and enhancing the economic operation of the system. In order to achieve the goal of matching the capacity configuration of the shared energy storage station with the wind and solar power consumption generated by each microgrid and to ensure the economic efficiency of the system, this article first considers the operational variables and planning variables of the system in the planning stage, and establishes a two-level optimization model under the goal of user demand response and economic efficiency. Secondly, a two-level decision game model is proposed to solve the capacity configuration and optimization scheduling of the shared energy storage system in multi-microgrids. The upper and lower layers of this two-level decision game model use whale algorithm and second-order cone algorithm respectively to solve the planning problem of the multi-microgrid shared energy storage system and the scheduling optimization problem of the shared energy storage system in multi-microgrids. The upper and lower layers iteratively optimize alternately. Finally, in order to meet the actual operation, the peak-valley electricity price mechanism is used in the electricity purchase price in this article. The experimental results show that this article provides the optimal configuration and scheduling plan for the multi-microgrid shared energy storage system, which ensures the optimal operation of the system. Furthermore, the computational speed and solution accuracy of the proposed (WOA-SOCP)algorithm are further improved in this article. The results show that the construction of a shared energy storage system in multi-microgrids has significantly reduced the cost and configuration capacity and rated power of individual energy storage systems in each microgrid. The wind and solar power utilization rate of the multi-microgrid shared energy storage system reached 96.53%, which is significantly higher than the overall wind and solar power utilization rate of individual-microgrids configuring energy storage systems. It can be concluded that the shared energy storage system in multi-microgrids can further optimize the abandoned wind and solar power rate compared to individual microgrids configuring energy storage stations.