Grey Wolf Optimizer Based Battery Energy Storage System Sizing for Economic Operation of Microgrid

Abstract

Battery energy storage systems (BESSs) can support microgrid's economic operation. In this paper, the optimal capacity of BESS is determined for economic operation of microgrid. The BESS sizing problem is solved simultaneously with “mix-mode energy management system” (MM-EMS). Here, the MM-EMS is solved using linear programming (LP), and mixed integer linear programming (MILP) optimization techniques. Metaheuristic optimization techniques such as grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA) and genetic algorithm (GA) are used to solve the BESS sizing problem and a comparison of its performance is also carried out. It was found that GWO produces the most optimal solution than other optimization techniques. With this, the performance of the proposed BESS sizing method is validated with traditional tradeoff method. Moreover, a comparison in microgrid's operating cost with and without BESS is carried out. It was also found that, 70% savings in microgrid's operating cost can be achieved when microgrid is operated with BESS.