Optimal Configuration of Energy Storage System Considering Uncertainty of Load and Wind Generation

Abstract

Energy storage systems are promising solutions to the mitigation of power fluctuations and the management of load demands in distribution networks. However, the uncertainty of load demands and wind generations increasingly seen in distribution networks may have a great impact on the configuration of ESS. To solve the problem, a novel optimal configuration method for energy storage system is proposed to reduce the influence of uncertainty of both load demands and WGs. The proposed method first reduce the uncertainty of load through a comprehensive demand response system based on time-of-use and incentive. Then, to predict the output of wind generations, we use the particle swarm optimization and backpropagation neural network to create a predictive model of the wind power. Then, an optimal configuration model is established to minimize the ESS investment cost and the network power loss reduction, subject to technical constraints such as ESS operational constraints and power balance constraint et al. An improved simulated annealing PSO algorithm is used to solve the optimization problem. Finally, the numerical studies on a modified IEEE 33-node distribution system show the advantages of the proposed methodology.