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Multi-service battery energy storage system optimization and control

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  • Hanif, Sarmad
  • Alam, M.J.E.
  • Roshan, Kini
  • Bhatti, Bilal A.
  • Bedoya, Juan C.

Abstract

Battery energy storage systems (BESS) have become a fundamental part of modern power systems due to their ability to provide multiple grid services. As renewable penetration increases, BESS procurement is also expected to increase and is envisioned to play a systematic and strategic role in power systems planning and operation. Therefore, in this paper we present a multiple grid service procurement and operation approach for BESS, including energy arbitrage, reserve/regulation services, power factor correction, and demand management. The proposed framework considers an optimal multi-temporal dimension and is designed to be operable for both planning and real-time operation. Moreover, the nonlinearity inherent to BESS services and the uncertainty associated with market forecast variables are addressed using techniques such as polyhedral norms and robust optimization approaches. The developed model is tested using a utility-scaled BESS, and the results show the effectiveness of the systematic BESS multi-service planning and operation approach.

Suggested Citation

  • Hanif, Sarmad & Alam, M.J.E. & Roshan, Kini & Bhatti, Bilal A. & Bedoya, Juan C., 2022. "Multi-service battery energy storage system optimization and control," Applied Energy, Elsevier, vol. 311(C).
    • Handle: RePEc:eee:appene:v:311:y:2022:i:c:s0306261922000885
    DOI: 10.1016/j.apenergy.2022.118614
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    References listed on IDEAS

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    Cited by:

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    2. Xie, Jiahang & Yang, Rufan & Gooi, Hoay Beng & Nguyen, Hung Dinh, 2023. "PID-based CNN-LSTM for accuracy-boosted virtual sensor in battery thermal management system," Applied Energy, Elsevier, vol. 331(C).
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    4. Zhang, Mingze & Li, Weidong & Yu, Samson Shenglong & Wang, Haixia & Ba, Yu, 2024. "Optimal day-ahead large-scale battery dispatch model for multi-regulation participation considering full timescale uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    5. Bhatti, Bilal Ahmad & Hanif, Sarmad & Alam, Jan & Mitra, Bhaskar & Kini, Roshan & Wu, Di, 2023. "Using energy storage systems to extend the life of hydropower plants," Applied Energy, Elsevier, vol. 337(C).
    6. Zhi, Yuan & Yang, Xudong, 2023. "Scenario-based multi-objective optimization strategy for rural PV-battery systems," Applied Energy, Elsevier, vol. 345(C).

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