Life extension of a multi-unit energy storage system by optimizing the power distribution based on the degradation ratio

Xinjia Gao, Xiaogang Wu, Yinlong Xia and Yalun Li

Energy, 2024, vol. 286, issue C

Abstract: Battery energy storage systems are widely used to absorb renewable energy. However, the difference in the initial state and operating conditions led to inconsistent degradation between the battery units. It is urgent to develop life extension algorithms to solve the problem. In this study, a calculation scheme is proposed for the power distribution toward an optimized cycle life. First, the degradation ratio between the energy storage units was calculated based on the Arrhenius degradation model validated by aging experiments. A decisive correlation was revealed between the current rate and the degradation ratios using Pearson correlation analysis. Next, a simplified calculation method was proposed toward various operating conditions, which proved to acceptable errors less than 3 %. It was inferred that the degradation ratio could be directly controlled by the current rate ratio. Based on this concept, the degradation path was optimized based on genetic algorithm, to obtain the optimized power distribution factor of the entire life. The results showed that the cycle life could be extended by 21.9 % after separately adjusting the power distribution with 4-stage optimization. The study has effectively extended the service life of energy storage, which helps to develop the on-line control strategy toward life extension.

Keywords: Battery energy storage systems; Degradation ratio; Pearson correlation analysis; Genetic algorithm; Life extension (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:286:y:2024:i:c:s0360544223029924

DOI: 10.1016/j.energy.2023.129598

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