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

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  • Gao, Xinjia
  • Wu, Xiaogang
  • Xia, Yinlong
  • Li, Yalun

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.

Suggested Citation

  • Gao, Xinjia & Wu, Xiaogang & Xia, Yinlong & Li, Yalun, 2024. "Life extension of a multi-unit energy storage system by optimizing the power distribution based on the degradation ratio," Energy, Elsevier, vol. 286(C).
  • Handle: RePEc:eee:energy:v:286:y:2024:i:c:s0360544223029924
    DOI: 10.1016/j.energy.2023.129598
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    References listed on IDEAS

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    1. Qahtan, Talal F. & Alade, Ibrahim O. & Rahaman, Md Safiqur & Saleh, Tawfik A., 2023. "Mapping the research landscape of hydrogen production through electrocatalysis: A decade of progress and key trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    2. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Hou, Jun & Zhang, Xiaowu & Ouyang, Minggao, 2015. "The optimization of a hybrid energy storage system at subzero temperatures: Energy management strategy design and battery heating requirement analysis," Applied Energy, Elsevier, vol. 159(C), pages 576-588.
    3. He, Li & Zhang, Shiyue & Chen, Yizhong & Ren, Lixia & Li, Jing, 2018. "Techno-economic potential of a renewable energy-based microgrid system for a sustainable large-scale residential community in Beijing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 631-641.
    4. Olabi, A.G. & Wilberforce, Tabbi & Sayed, Enas Taha & Abo-Khalil, Ahmed G. & Maghrabie, Hussein M. & Elsaid, Khaled & Abdelkareem, Mohammad Ali, 2022. "Battery energy storage systems and SWOT (strengths, weakness, opportunities, and threats) analysis of batteries in power transmission," Energy, Elsevier, vol. 254(PA).
    5. Usman Bashir Tayab & Junwei Lu & Seyedfoad Taghizadeh & Ahmed Sayed M. Metwally & Muhammad Kashif, 2021. "Microgrid Energy Management System for Residential Microgrid Using an Ensemble Forecasting Strategy and Grey Wolf Optimization," Energies, MDPI, vol. 14(24), pages 1-19, December.
    6. Felipe Gonzalez & Marc Petit & Yannick Perez, 2021. "Plug-in behavior of electric vehicles users: Insights from a large-scale trial and impacts for grid integration studies," Post-Print hal-03363782, HAL.
    7. Francesco Pietro Colelli & Johannes Emmerling & Giacomo Marangoni & Malcolm N. Mistry & Enrica Cian, 2022. "Increased energy use for adaptation significantly impacts mitigation pathways," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    8. Wang, Shuoqi & Guo, Dongxu & Han, Xuebing & Lu, Languang & Sun, Kai & Li, Weihan & Sauer, Dirk Uwe & Ouyang, Minggao, 2020. "Impact of battery degradation models on energy management of a grid-connected DC microgrid," Energy, Elsevier, vol. 207(C).
    9. McIlwaine, Neil & Foley, Aoife M. & Best, Robert & Morrow, D. John & Kez, Dlzar Al, 2023. "Modelling the effect of distributed battery energy storage in an isolated power system," Energy, Elsevier, vol. 263(PC).
    10. Zhang, Xuehan & Son, Yongju & Cheong, Taesu & Choi, Sungyun, 2022. "Affine-arithmetic-based microgrid interval optimization considering uncertainty and battery energy storage system degradation," Energy, Elsevier, vol. 242(C).
    11. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    12. Mohamad, Farihan & Teh, Jiashen & Lai, Ching-Ming, 2021. "Optimum allocation of battery energy storage systems for power grid enhanced with solar energy," Energy, Elsevier, vol. 223(C).
    13. Du, Jiuyu & Zhang, Xiaobin & Wang, Tianze & Song, Ziyou & Yang, Xueqing & Wang, Hewu & Ouyang, Minggao & Wu, Xiaogang, 2018. "Battery degradation minimization oriented energy management strategy for plug-in hybrid electric bus with multi-energy storage system," Energy, Elsevier, vol. 165(PA), pages 153-163.
    14. Sukumar, Shivashankar & Mokhlis, Hazlie & Mekhilef, Saad & Naidu, Kanendra & Karimi, Mazaher, 2017. "Mix-mode energy management strategy and battery sizing for economic operation of grid-tied microgrid," Energy, Elsevier, vol. 118(C), pages 1322-1333.
    15. Xing, Wei & Wang, Hewu & Lu, Languang & Han, Xuebing & Sun, Kai & Ouyang, Minggao, 2021. "An adaptive virtual inertia control strategy for distributed battery energy storage system in microgrids," Energy, Elsevier, vol. 233(C).
    16. Xu, Xiaodong & Tang, Shengjin & Yu, Chuanqiang & Xie, Jian & Han, Xuebing & Ouyang, Minggao, 2021. "Remaining Useful Life Prediction of Lithium-ion Batteries Based on Wiener Process Under Time-Varying Temperature Condition," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    Full references (including those not matched with items on IDEAS)

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