Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids

Abstract

The main challenge in integrating a Battery Energy Storage System (BESS) into a microgrid is to evaluate an optimum size of BESS to prevent the microgrid from instability and system collapse. The installation of BESS at a random size or non-optimum size can increase in cost, system losses and larger BESS capacity. Thus, this paper proposes the new method to evaluate an optimum size of BESS at minimal total BESS cost by using particle swarm optimization (PSO)-based frequency control of the stand-alone microgrid. The research target is to propose an optimum size of BESS by using the PSO method-based frequency control in order to prevent the microgrid from instability and system collapse after the loss of the utility grid (e.g., blackout or disasters) and minimize the total cost of BESS for 15years installation in the microgrid. Then, the economical performance of BESS with modern different storage technologies is investigated and compared in the typical microgrid. Results show that the optimum size of BESS-based PSO method can achieve higher dynamic performance of the system than the optimum size of BESS-based analytic method and the conventional size of BESS. In terms of BESS economical performance with modern storage technologies, the installation of the polysulfide–bromine BESS is likely to be more cost-effective than the installation of the vanadium redox BESS for 15years installation in the typical microgrid. It is concluded that the proposed PSO method-based frequency control can improve significantly power system stability, grid security, and planning flexibility for the microgrid system. At the same time, it can fulfill the frequency control requirements with a high economic profitability.