Research on Location Determination and Capacity Optimization Method for Large-Scale Energy Storage Station in Regional Power Grid

In this paper, an optimization method is proposed to optimize the location and capacity of large-scale energy storage station in regional power gird. First, according to the requirement of power system, a multi-objective function is built for performance evaluation, which includes node voltage fluctuation, load fluctuation and investment of energy storage station. Then, an improved particle swarm algorithm (PSA) is proposed for location and capacity optimization. Since traditional PSA is easy to get stuck on locally optimal value, weight coefficients with nonlinear adjustment functions and cross-compilation processes in the genetic algorithm are employed to avoid the local optimal results. In the end, the regional power grid in Pingdingshan, Henan Province is taken as a case study to evaluate the effectiveness of the proposed optimization method. The proposed optimization result shows that the proposed method shows quickness and accuracy in location and capacity optimization for large-scale energy storage station.