Optimal Allocation of Energy Storage System in Transmission System Considering Wind Power

Abstract

Wind power uncertainties should be considered in power system operation and planning. Energy storage system (ESS) can facilitate wind power integration in the energy system. However, maximum benefits can be achieved by optimal determination of the location and sizing of ESSs. In this paper, five-point estimation method is utilized to discretise the wind power distribution into five discrete distributions. Combining the discretizing method with a multi-objective hybrid particle swarm optimisation (MOPSO) and nondominated sorting genetic algorithm (NSGAII), a hybrid probabilistic optimisation algorithm is constructed. The hybrid algorithm aims to search for the best site and size of energy storage system (ESSs) and considers the power uncertainties of wind farm. System's total expected cost restricted by investment budget, total expected voltage deviation and total expected carbon emission are the objective functions to be minimised IEEE 30-bus system is adopted to perform the case studies using the hybrid algorithm. The simulation results demonstrate the effectiveness of the hybrid method in solving the optimal allocation problem of ESSs and considering the uncertainties of wind farms' output power.