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Model for payback time of using retired electric vehicle batteries in residential energy storage systems

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  • Al-Wreikat, Yazan
  • Attfield, Emily Kate
  • Sodré, José Ricardo

Abstract

This work presents a mathematical model for the payback time of reusing electric vehicle batteries as residential energy storage systems from the end of life of automotive application. The model was developed using MATLAB software and calculates the payback time of a battery energy storage system (BESS) under different scenarios while considering the daily electricity consumption profile for a UK household. The results show that battery purchase price, BESS capacity, electricity unit rates and electricity demand profile are variables with large effects on the payback time. At the simulated baseline condition with residential households of two people, a BESS using second-life batteries from five different vehicle models showed payback time ranging from 8.3 to 12.8 years. The combination of battery rightsizing to attend peak and standard demand, battery price drop by 46%, reaching the level where EV price becomes competitive with conventional vehicles, and BESS application to three or more households provides the most favourable scenario with the minimum payback time of 4.8 years. Further reduction in the payback time of up to 41% can be achieved with subsidised off-peak electricity unit rate.

Suggested Citation

  • Al-Wreikat, Yazan & Attfield, Emily Kate & Sodré, José Ricardo, 2022. "Model for payback time of using retired electric vehicle batteries in residential energy storage systems," Energy, Elsevier, vol. 259(C).
    • Handle: RePEc:eee:energy:v:259:y:2022:i:c:s0360544222018746
    DOI: 10.1016/j.energy.2022.124975
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    Cited by:

    1. Gu, Pingwei & Zhang, Ying & Duan, Bin & Zhang, Chenghui & Kang, Yongzhe, 2024. "Rapid and flexible lithium-ion battery performance evaluation using random charging curve based on deep learning," Energy, Elsevier, vol. 293(C).
    2. Tang, Hong & Wang, Shengwei, 2023. "Life-cycle economic analysis of thermal energy storage, new and second-life batteries in buildings for providing multiple flexibility services in electricity markets," Energy, Elsevier, vol. 264(C).
    3. Ziad M. Ali & Martin Calasan & Shady H. E. Abdel Aleem & Francisco Jurado & Foad H. Gandoman, 2023. "Applications of Energy Storage Systems in Enhancing Energy Management and Access in Microgrids: A Review," Energies, MDPI, vol. 16(16), pages 1-41, August.
    4. Xiong, Wei & Xie, Fang & Xu, Gang & Li, Yumei & Li, Ben & Mo, Yimin & Ma, Fei & Wei, Keke, 2023. "Co-estimation of the model parameter and state of charge for retired lithium-ion batteries over a wide temperature range and battery degradation scope," Renewable Energy, Elsevier, vol. 218(C).

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