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A unified model to optimize configuration of battery energy storage systems with multiple types of batteries

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  • Jiang, Yinghua
  • Kang, Lixia
  • Liu, Yongzhong

Abstract

Aiming to minimize the total cost of hybrid power system (HPS), a mathematical model for the configuration of battery energy storage system (BESS) with multiple types of batteries was proposed. The effects of battery types and capacity degradation characteristics on the optimal capacity configurations of the BESS and power scheduling schemes of the HPS were investigated. The effectiveness of the proposed model was verified and illustrated through a case study of a HPS with photovoltaic-wind-biomass-batteries. Results show that the optimal configuration of the BESS can be obtained by solving the proposed model, including the types and the capacities of batteries, and the power scheduling schemes of the batteries. For the integration of the HPS, the BESS with multiple types of batteries has certain economic advantages when compared with the BESS with a single type of batteries. In addition, the types and capacities of batteries in the BESS and the relative power scheduling schemes would change with the electricity curtailment rate of the renewable energy supply of HPS. The total cost of the HPS can be reduced at the expense of a certain amount of renewable energy supply.

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  • Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2019. "A unified model to optimize configuration of battery energy storage systems with multiple types of batteries," Energy, Elsevier, vol. 176(C), pages 552-560.
    • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:552-560
    DOI: 10.1016/j.energy.2019.04.018
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    4. Yu, Shiwei & Zhou, Shuangshuang & Chen, Nan, 2024. "Multi-objective optimization of capacity and technology selection for provincial energy storage in China: The effects of peak-shifting and valley-filling," Applied Energy, Elsevier, vol. 355(C).
    5. Yang, Bo & Zhu, Tianjiao & Zhang, Xiaoshun & Wang, Jingbo & Shu, Hongchun & Li, Shengnan & He, Tingyi & Yang, Lei & Yu, Tao, 2020. "Design and implementation of Battery/SMES hybrid energy storage systems used in electric vehicles: A nonlinear robust fractional-order control approach," Energy, Elsevier, vol. 191(C).
    6. Yang, Bo & Wang, Jingbo & Sang, Yiyan & Yu, Lei & Shu, Hongchun & Li, Shengnan & He, Tingyi & Yang, Lei & Zhang, Xiaoshun & Yu, Tao, 2019. "Applications of supercapacitor energy storage systems in microgrid with distributed generators via passive fractional-order sliding-mode control," Energy, Elsevier, vol. 187(C).
    7. Jiří Jaromír Klemeš & Petar Sabev Varbanov & Paweł Ocłoń & Hon Huin Chin, 2019. "Towards Efficient and Clean Process Integration: Utilisation of Renewable Resources and Energy-Saving Technologies," Energies, MDPI, vol. 12(21), pages 1-32, October.
    8. Liu, Jia & Chen, Xi & Yang, Hongxing & Li, Yutong, 2020. "Energy storage and management system design optimization for a photovoltaic integrated low-energy building," Energy, Elsevier, vol. 190(C).
    9. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2020. "Optimal configuration of battery energy storage system with multiple types of batteries based on supply-demand characteristics," Energy, Elsevier, vol. 206(C).
    10. Zehra, Syeda Shafia & Ur Rahman, Aqeel & Ahmad, Iftikhar, 2022. "Fuzzy-barrier sliding mode control of electric-hydrogen hybrid energy storage system in DC microgrid: Modelling, management and experimental investigation," Energy, Elsevier, vol. 239(PD).
    11. Meng, Jinhao & Cai, Lei & Stroe, Daniel-Ioan & Ma, Junpeng & Luo, Guangzhao & Teodorescu, Remus, 2020. "An optimized ensemble learning framework for lithium-ion Battery State of Health estimation in energy storage system," Energy, Elsevier, vol. 206(C).

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