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The economic end of life of electrochemical energy storage

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  • He, Guannan
  • Ciez, Rebecca
  • Moutis, Panayiotis
  • Kar, Soummya
  • Whitacre, Jay F.

Abstract

The useful life of electrochemical energy storage (EES) is a critical factor to system planning, operation, and economic assessment. Today, systems commonly assume a physical end-of-life criterion: EES systems are retired when their remaining capacity reaches a threshold below which the EES is of little use because of insufficient capacity and efficiency. We have found, however, that there are some instances where, while the EES is still functional, it is no longer economically profitable; we call this criterion the economic end of life of the system. This criterion depends on the use case and degradation characteristics of the EES. Using an intertemporal operational framework to consider functionality and profitability degradation, our case study shows that the economic end of life could occur significantly faster than the physical end of life. We argue that both criteria should be applied in EES system planning and assessment. We also analyze how R&D efforts should consider cycling capability and calendar degradation rate when considering the economic end of life of EES.

Suggested Citation

  • He, Guannan & Ciez, Rebecca & Moutis, Panayiotis & Kar, Soummya & Whitacre, Jay F., 2020. "The economic end of life of electrochemical energy storage," Applied Energy, Elsevier, vol. 273(C).
    • Handle: RePEc:eee:appene:v:273:y:2020:i:c:s0306261920306632
    DOI: 10.1016/j.apenergy.2020.115151
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    1. Ma, Guijun & Zhang, Yong & Cheng, Cheng & Zhou, Beitong & Hu, Pengchao & Yuan, Ye, 2019. "Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    2. Zhang, Yongzhi & Xiong, Rui & He, Hongwen & Qu, Xiaobo & Pecht, Michael, 2019. "State of charge-dependent aging mechanisms in graphite/Li(NiCoAl)O2 cells: Capacity loss modeling and remaining useful life prediction," Applied Energy, Elsevier, vol. 255(C).
    3. William A. Braff & Joshua M. Mueller & Jessika E. Trancik, 2016. "Value of storage technologies for wind and solar energy," Nature Climate Change, Nature, vol. 6(10), pages 964-969, October.
    4. Shafiee, Soroush & Zamani-Dehkordi, Payam & Zareipour, Hamidreza & Knight, Andrew M., 2016. "Economic assessment of a price-maker energy storage facility in the Alberta electricity market," Energy, Elsevier, vol. 111(C), pages 537-547.
    5. Patil, Meru A. & Tagade, Piyush & Hariharan, Krishnan S. & Kolake, Subramanya M. & Song, Taewon & Yeo, Taejung & Doo, Seokgwang, 2015. "A novel multistage Support Vector Machine based approach for Li ion battery remaining useful life estimation," Applied Energy, Elsevier, vol. 159(C), pages 285-297.
    6. Hu, Chao & Jain, Gaurav & Tamirisa, Prabhakar & Gorka, Tom, 2014. "Method for estimating capacity and predicting remaining useful life of lithium-ion battery," Applied Energy, Elsevier, vol. 126(C), pages 182-189.
    7. Robert L. Fares & Michael E. Webber, 2017. "The impacts of storing solar energy in the home to reduce reliance on the utility," Nature Energy, Nature, vol. 2(2), pages 1-10, February.
    8. Jun Lu & Tianpin Wu & Khalil Amine, 2017. "State-of-the-art characterization techniques for advanced lithium-ion batteries," Nature Energy, Nature, vol. 2(3), pages 1-13, March.
    9. Guannan He & Qixin Chen & Panayiotis Moutis & Soummya Kar & Jay F. Whitacre, 2018. "An intertemporal decision framework for electrochemical energy storage management," Nature Energy, Nature, vol. 3(5), pages 404-412, May.
    10. Steven Chu & Arun Majumdar, 2012. "Opportunities and challenges for a sustainable energy future," Nature, Nature, vol. 488(7411), pages 294-303, August.
    11. A. Stephan & B. Battke & M. D. Beuse & J. H. Clausdeinken & T. S. Schmidt, 2016. "Limiting the public cost of stationary battery deployment by combining applications," Nature Energy, Nature, vol. 1(7), pages 1-9, July.
    12. Song, Ziyou & Feng, Shuo & Zhang, Lei & Hu, Zunyan & Hu, Xiaosong & Yao, Rui, 2019. "Economy analysis of second-life battery in wind power systems considering battery degradation in dynamic processes: Real case scenarios," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    13. Noah Kittner & Felix Lill & Daniel M. Kammen, 2017. "Energy storage deployment and innovation for the clean energy transition," Nature Energy, Nature, vol. 2(9), pages 1-6, September.
    14. Paul R. Shearing, 2016. "Batteries: Imaging degradation," Nature Energy, Nature, vol. 1(11), pages 1-2, November.
    15. Chang, Yang & Fang, Huajing & Zhang, Yong, 2017. "A new hybrid method for the prediction of the remaining useful life of a lithium-ion battery," Applied Energy, Elsevier, vol. 206(C), pages 1564-1578.
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