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Life Cycle Estimation of Battery Energy Storage Systems for Primary Frequency Regulation

Author

Listed:
  • Natascia Andrenacci

    (ENEA—Italian National Agency for New Technologies, Energy and Sustainable Economic Development, via Anguillarese 301, 00123 Rome, Italy)

  • Elio Chiodo

    (Department of Industrial Engineering, University of Naples Federico II, via Claudio 21, 80125 Naples, Italy)

  • Davide Lauria

    (Department of Industrial Engineering, University of Naples Federico II, via Claudio 21, 80125 Naples, Italy)

  • Fabio Mottola

    (Department of Industrial Engineering, University of Naples Federico II, via Claudio 21, 80125 Naples, Italy)

Abstract

An increasing share of renewable energy sources in power systems requires ad-hoc tools to guarantee the closeness of the system’s frequency to its rated value. At present, the use of new technologies, such as battery energy storage systems, is widely debated for its participation in the service of frequency containment. Since battery installation costs are still high, the estimation of their lifetime appears crucial in both the planning and operations of power systems’ regulation service. As the frequency response of batteries is strongly dependent on the stochastic nature of the various contingencies which can occur on power systems, the estimation of the battery lifetime is a very complex issue. In the present paper, the stochastic process which better represents the power system frequency is analyzed first; then the battery lifetime is properly estimated on the basis of realistic dynamic modeling including the state of the charge control strategy. The dynamic evolution of the state of charge is then used in combination with the celebrated rain-flow procedure with the aim of evaluating the number of charging/discharging cycles whose knowledge allows estimating the battery damage. Numerical simulations are carried out in the last part of the paper, highlighting the resulting lifetime probabilistic expectation and the impact of the state of the charge control strategy on the battery lifetime. The main findings of the present work are the proposed autoregressive model, which allows creating accurate pseudo-samples of frequency patterns and the analysis of the incidence of the control law on the battery lifetime. The numerical applications clearly show the prominent importance of this last aspect since it has an opposing impact on the economic issue by influencing the battery lifetime and technical effects by modifying the availability of the frequency regulation service.

Suggested Citation

  • Natascia Andrenacci & Elio Chiodo & Davide Lauria & Fabio Mottola, 2018. "Life Cycle Estimation of Battery Energy Storage Systems for Primary Frequency Regulation," Energies, MDPI, vol. 11(12), pages 1-24, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3320-:d:186104
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    References listed on IDEAS

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    5. Ahmed Gailani & Maher Al-Greer & Michael Short & Tracey Crosbie & Nashwan Dawood, 2020. "Lifetime Degradation Cost Analysis for Li-Ion Batteries in Capacity Markets using Accurate Physics-Based Models," Energies, MDPI, vol. 13(11), pages 1-21, June.
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    9. Wei Chen & Na Sun & Zhicheng Ma & Wenfei Liu & Haiying Dong, 2023. "A Two-Layer Optimization Strategy for Battery Energy Storage Systems to Achieve Primary Frequency Regulation of Power Grid," Energies, MDPI, vol. 16(6), pages 1-18, March.

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