Economic Optimization Scheduling Strategy for Battery Energy Storage System Based on Particle Swarm Optimization

SUN Jinlei, LIU Ruihang, MA Qian, TANG Chuanyu, WANG Tianru, PENG Fuming

Abstract


The power scheduling of Battery Energy Storage System(BESS) directly affects its scheduling cost, and a reasonable power allocation scheme is the basis for ensuring the economic operation of the power system. In this paper, the goal of optimization is to minimize scheduling cost of per unit period, in order to realize the reasonable power allocation of BESS. The BESS power scheduling cost is established, and the Particle Swarm Optimization (PSO) is used to achieve global optimization. The proposed method could complete the scheduling task while minimizing the scheduling cost. The results of the case simulation showed that comparing with the traditional equal-proportion power allocation scheme, the PSO optimal scheduling method used in this paper saved the scheduling cost by about 19.5%, when the life of BESS was terminated (2524 times) under the traditional scheduling method. Besides, the proposed method continued for an additional 515 times, which increased the operational life of the BESS by about 20.4%, which proved the superiority and economy of the new method.

Keywords


Battery energy storage system; power scheduling; scheduling cost; particle swarm optimization; economy


DOI
10.12783/dteees/iceee2018/27818

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