Journal
JOURNAL OF ENERGY STORAGE
Volume 55, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.est.2022.105634
Keywords
Battery energy storage system; Lithium-ion; Degradation model; Aging; Operation; Optimization
Categories
Funding
- Bavarian Research Foundation via the research project SmartB4P, Germany
- German Federal Ministry of Education and Research (BMBF) via the research project greenBattNutzung
- [AZ-1376-19]
- [03XP0302D]
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The deployment of battery energy storage systems (BESS) has been increasing steadily, with lithium-ion batteries being the most commonly used technology. However, these batteries are subject to degradation due to various aging mechanisms, which can have a significant impact on the economics and safety of BESS. To address this issue, researchers have developed degradation modeling approaches and operation strategies to increase the lifetime of BESS. Through simulation case studies, key stress factors that influence degradation have been identified.
The amount of deployed battery energy storage systems (BESS) has been increasing steadily in recent years. For newly commissioned systems, lithium-ion batteries have emerged as the most frequently used technology due to their decreasing cost, high efficiency, and high cycle life. As a result of a multitude of cell internal aging mechanisms, lithium-ion batteries are subject to degradation. The effects of degradation, in particular decreasing capacity, increasing resistance, and safety implications, can have significant impact on the economics of a BESS. Influenced by aging stress factors such as the state of charge, charge-discharge rate, cycle count, and temperature, the extent of degradation is directly affected by the operating conditions. Significant amount of literature can be found that focuses on aging aware operation of BESSs. In this review, we provide an overview of relevant aging mechanisms as well as degradation modeling approaches, and deduce the key aspects from the state of the art in those topics for BESS operation. Following that, we review and categorize methods that aim to increase BESS lifetime by accounting for battery degradation effects in the operation strategy. The literature shows that using empirical or semi-empirical degradation models as well as the exact solution approach of mixed integer linear programming are particularly common for that purpose, as is the method of defining aging costs for the objective function. Furthermore, through a simulation case study, we identify the most relevant stress factors that influence degradation for the key applications of self consumption increase, peak shaving, and frequency containment reserve.
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