Abstract
Due to the ever increasing in the energy demand and the growth of the pollution problem, further interest in renewable energy becomes prominent, especially wind energy. However, the intermittent nature of the wind speed results in the system's insecurity problems. Integrating the energy storage system (ESS) optimally is the best so far solution. In this paper, a probabilistic discretizing method is derived and generalized to consider the uncertainties of the wind generators. Moreover, a mixed integer non-linear optimisation problem is constructed comprises three objective functions to be minimized simultaneously. The objectives comprising the total operation and planning cost of ESSs, the average voltage deviation and average power losses. The solving method is a hybrid algorithm incorporates the non-dominated sorting genetic algorithm (NSGAII), multi-objective particle swarm optimisation (MOPSO) and a decision-making algorithm. The aim is to determine the optimal location and sizing of ESSs considering their reactive power capability. 69 radial bus distribution system is adopted to demonstrate the efficacy of the proposed hybrid algorithm and performing some case studies. The simulation results verified the capability of ESSs to enhance the voltage profile and reduce the power losses, notably when reactive power capability is examined.
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