Optimal Allocation of Shared Energy Storage Capacity Considering Source-Load Interconnection in Multiple Distribution Transformer Areas

The rapid development of the Chinese economy has result in a surge in electricity demand, imposing significant strain on the transformer planning capacity within distribution areas. The substantial integration of an increasing number of renewable energy, including photovoltaics, into the grid has introduced new challenges, potentially causing grid instability and safety concerns. To adapt flexibly to regional load demands, improve the capability of high-proportion photovoltaic integration in distribution areas, reduce the peak-to-valley difference of load in distribution areas, and promote the grid’s safe and stable operation in a scientific and economic manner, this paper proposes a method for optimizing the allocation of shared energy storage capacity by considering the source-load interconnection across multiple distribution areas. The purpose of the method is to integrate the renewable energy in the distribution areas through the allocation of shared energy storage capacity. This approach concurrently alleviates the pressure on the power supply during peak power consumption in high-loaded areas, minimizes the impact of renewable energy integration on the grid, and enhances the security and stability of the grid operation. Addresses the existing problems in the distribution areas, the method establishes a model for allocating shared storage capacity based on the load characteristics, considering the construction and operation costs of the shared storage, the revenue from interaction with distribution areas, and the revenue of participation in the peak shaving ancillary service market. The model is solved by the Particle Swarm Optimization algorithm to determine the shared energy storage capacity.The Simulation results demonstrate that this method effectively allocates shared energy storage capacity between distribution areas, achieving superior peak shaving and valley filling objectives while enhancing energy storage utilization. This, in turn, leads to cost savings and profit realization.