Abstract：Battery energy storage system(BESS) has promising applicable future in power system because of its flexibility, quick response rate and no site restrictions. A battery lifetime predication method is proposed in this paper, taking the effect of depth of discharge on battery life into consideration, which is a primary determinant of battery life. To evaluate the benefits of static functions of BESS, which are known as peak shaving or time shifting, an evaluation model is established with lifetime prediction method of BESS. The proposed method and model are applied in the IEEE RTS-96 system to determine the appropriate size of BESS to be installed. Results are presented to show the feasibility and effectiveness of the proposed method.
娄素华,易林,吴耀武,侯婷婷,杨育丰. 基于可变寿命模型的电池储能容量优化配置[J]. 电工技术学报, 2015, 30(4): 265-271.
Lou Suhua,Yi Lin,Wu Yaowu,Hou Tingting,Yang Yufeng. Optimizing Deployment of Battery Energy Storage Based on Lifetime Predication. Transactions of China Electrotechnical Society, 2015, 30(4): 265-271.
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2015, Vol. 30 
