Energy Management Method of Energy Storage System Considering the SOH of Battery Pack

被引：0
|
作者：
Li X. [1 ]
Ma R. [1 ]
机构：
[1] State Key Laboratory of Control and Operation of Renewable Energy and Storage Systems, China Electric Power Research Institute, Haidian District, Beijing
来源：
Dianwang Jishu/Power System Technology | 2020年 / 44卷 / 11期
关键词：
Battery energy storage system; Battery life; Energy management; Power distribution;
D O I：
10.13335/j.1000-3673.pst.2020.0316
中图分类号：
学科分类号：
摘要：
Battery Energy Storage System (BESS) has been widely used in power system. BESS is different in actual operating conditions, resulting in different attenuation rates of battery life. In order to delay the battery life attenuation and increase the BESS service life, this paper proposes, a BESS energy management method considering the state of health (SOH). This method firstly determines the charge/discharge number of the battery pack according to the power size of the scheduling instruction, then integrates the SOH into the battery pack charge/discharge priority ranking rules, and finally uses the mathematical programming algorithm to solve the power distribution among the battery packs. BESS historical operation curve of an PV/BESS station in Qinghai province is taken as an example. Comparative tests show that the proposed energy management method of variable reference value can be based on the principle of "deep charging and deep discharging of new batteries and shallow charging and shallow discharging of old batteries". The power distribution among the batteries can be adjusted adaptively to extend the battery life. © 2020, Power System Technology Press. All right reserved.
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页码：4210 / 4217
页数：7
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  • [1] Li Xiangjun, Wang Shangxing, Hui Dong, Summary and prospect of operation control and application method for battery energy storage systems, Power System Technology, 41, 10, pp. 3315-3325, (2017)
  • [2] Yang Tianmeng, Song Zhuoran, Lou Suhua, Et al., Sizing of hybrid energy storage for improving wind power penetration, Power System Technology, 42, 5, pp. 1488-1494, (2018)
  • [3] Yang Yanhong, Pei Wei, Deng Wei, Et al., Day-ahead scheduling optimization for microgrid with battery life model, Transactions of China Electrotechnical Society, 30, 22, pp. 172-180, (2015)
  • [4] Qian Hong, Zhang Lianyao, Chen Qiqi, Capacity allocation of the frequency modulation system for thermal power unit based on battery life loss, Journal of Engineering for Thermal Energy and Power, 33, 3, pp. 128-132, (2018)
  • [5] Han Xiaojuan, Cheng Cheng, Ji Tianming, Et al., Capacity optimal modeling of hybrid energy storage systems considering battery life, Proceedings of the CSEE, 33, 34, pp. 91-97, (2013)
  • [6] Ding Ruoxing, Dong Ge, Wu Heping, Et al., Research on power sharing results parameterization of hybrid energy storage system, Transactions of China Electrotechnical Society, 31, S1, pp. 190-195, (2016)
  • [7] Han Xiaojuan, Tian Chunguang, Cheng Cheng, Et al., Power allocation method of hybrid energy storage system based on empirical mode decomposition, Acta Energiae Solaris Sinica, 35, 10, pp. 1889-1896, (2014)
  • [8] Zhang Ye, Guo Li, Jia Hongjie, Et al., An energy management method of hybrid energy storage system based on smoothing control, Automation of Electric Power Systems, 36, 16, pp. 36-41, (2012)
  • [9] Sun Yushu, Tang Xisheng, Sun Xiaozhe, Et al., Research on multi-type energy storage coordination control strategy based on MPC-HHT, Proceedings of the CSEE, 38, 9, pp. 2580-2588, (2018)
  • [10] Chai Wei, Li Zheng, Cai Xu, Et al., Variable step-size control method of large capacity battery energy storage system based on the life model, Transactions of China Electrotechnical Society, 31, 14, pp. 58-66, (2016)
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