Optimal allocation of energy storage power station based on improved multi-objective particle swarm optimization
The electrochemical energy storage power station has been gradually applied on a large scale in a high proportion of the new energy power grid,and its optimal configuration strategy largely determines the effectiveness of frequency and voltage regulation in its auxiliary power grid.To realize the optimal configuration of the electrochemical energy storage power station,this study first examines the control strategy of energy storage participating in the frequency and voltage regulation of the power system under a high proportion of new energy.It proposes a control method based on the variable coefficient frequency-voltage sag.Then,the multi-objective optimal configuration model for the energy storage system participating in the frequency and voltage regulation of the power grid under a high proportion of the new energy grid is established.The model considers the comprehensive indices of frequency modulation,voltage regulation,and system cost as optimization objectives.The improved multi-objective particle swarm optimization algorithm is employed to optimize the configuration of control parameters and the location and capacity of the energy storage system.To address subjectivity in the data,the entropy weight method is used to select the optimal scheme from the obtained multi-objective solution set.Finally,a practical example of a regional power grid of a city is used to optimize the allocation of energy storage.The comprehensive indices of regional power grid voltage regulation and frequency modulation were reduced by 9.2%and 25.1%,respectively.The voltage and frequency deviation of regional power grid nodes was considerably reduced,improving the effect of voltage regulation and frequency modulation.This verifies the effectiveness and superiority of the proposed energy storage fixed capacity location allocation method.
energy storagenew energy with high proportionmulti-objectiveoptimized configuration
国家科技期刊平台
NSTL
万方数据
维普
