Optimal Capacity Configuration of Energy Storage System for Wind Farm Using Improved Stochastic Particle Swarm Optimization

Abstract

Wind power generation is not stable and cannot supply constant electrical output, which challenges the attempt to integrate large scale wind power scheme into grids. Hybrid energy storage system (HESS) composed of super-capacitor and battery generally has strong complementarities on the technical performance, which can greatly improve the economic and technical performance of the system when it is used to smooth the volatility of the wind power. However, the main factor influencing the composite energy storage system efficiency is capacity configuration of the storage system. In order to get optimal capacity configuration of the HESS, this paper presents an optimization scheme to improve performance/cost ratio of the HESS while meeting the requirement of smoothing wind power fluctuations. In the optimization model, the power output average and maximum fluctuations in wind farm are taken as main constraints, and simulated annealing method is introduced into Stochastic Particle Swarm Optimization (SPSO) to improve its convergence, which creates an Improved Stochastic Particle Swarm Optimization (ISPSO) to seek the optimal ratio of super-capacitor and battery. Simulation comparison of ISPSO, SPSO and PSO verifies the feasibility and effectiveness of the model for capacity optimization. Meanwhile, it can provide decision-making reference for energy storage system design of wind farm.