Embedding scrapping criterion and degradation model in optimal operation of peak-shaving lithium-ion battery energy storage

Qingchun Hou, Yanghao Yu, Ershun Du, Hongjie He, Ning Zhang, Chongqing Kang, Guojing Liu and Huan Zhu

Applied Energy, 2020, vol. 278, issue C, No S0306261920311090

Abstract: Lithium-ion battery systems have been used in practical power systems for peak-shaving and demand response. However, a lithium-ion battery is degrading while cycling and would be scrapped when the capacity reduces to a certain experience-based threshold (e.g. 80%). The scrapping criterion could significantly affect battery lifetime and operation scheduling for grid application. Thus, such scraping criterion may not explore the maximum benefit from a new or re-used lithium-ion battery. In this paper, we propose a novel efficiency-based scrapping criterion for peak-shaving energy storage. This criterion is suitable for both new and re-used battery in grid application. Using the scraping criterion as a parameter, the maximum cycle number of battery is derived as a function of the depth of discharge, which makes the life model easy to embed in battery operation model. The results of the case study show that the operation method could maximize the benefit of peak-shaving energy storage while delaying battery degradation. Compared with the traditional 80% capacity-based scrapping criterion, our efficiency-based scrapping criterion can significantly improve the lifetime benefit of the battery by 97%.

Keywords: Power system peak shaving; Energy storage operation optimization; Lithium-ion battery life model; Battery scrapping criterion; Battery end of life (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (7)

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DOI: 10.1016/j.apenergy.2020.115601

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