The cost of energy storage allocation contradicts the smoothing effect of power fluctuation

while energy storage capacity optimization is a feasible way to solve this problem. Firstly

by taking the minimum target value offset variance as the optimal object

the optimal expected output is calculated to eliminate the subjectivity during the determination of output target value of power fluctuation smoothing. Such a line of thought is regarded as the theoretical basis of energy storage capacity optimization. Secondly

considering the parameter of state of charge (SOC) and based on the fuzzy control theory

the charge and discharge power is adjusted timely according to the SOC and the charge-discharge state. Then the charge and discharge strategy for the energy storage system (ESS) is devised while excessive charge or discharge is obviously restrained. Finally

the optimization mathematical model is developed to minimize the sum of penalty cost and running cost

while the energy storage capacity optimization balancing the dispatching decision demand

ESS service life and operating economy are realized. The improved particle swarm optimization (PSO) algorithm is adopted for optimization calculation

with the effectiveness of the method shown by actual wind farm data.