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Stacked revenues for energy storage participating in energy and reserve markets with an optimal frequency regulation modeling

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  • Mohamed, Ahmed
  • Rigo-Mariani, Rémy
  • Debusschere, Vincent
  • Pin, Lionel

Abstract

This paper investigates the opportunity for a Battery Energy Storage System (BESS) to participate in multiple energy markets. The study proposes an offline assessment to calculate the maximum annual revenues to reach the optimum stack of services through deterministic simulations. The markets include wholesale energy markets (day-ahead and intraday), ancillary services (frequency regulation and reserve), and the capacity mechanism. The study case performed on the French markets shows that frequency services overperform the other markets, where the long-term capacity market has the least potential. Moreover, providing multiple services maximizes the battery's revenues, for example, participating in joint energy and reserve markets showed a 76% increase in annual profits. Furthermore, a novel operation approach was proposed to enhance the performance of these joint markets, by indirectly utilizing energy products as frequency reserves. The results demonstrate that the proposed formulation allows a revenue increase of ∼23% compared to the conventional framework for the provision of frequency regulation with BESSs. Additionally, the joint markets have been shown to be economically viable with 6.2 years payback period after considering battery degradation and depreciation cost.

Suggested Citation

  • Mohamed, Ahmed & Rigo-Mariani, Rémy & Debusschere, Vincent & Pin, Lionel, 2023. "Stacked revenues for energy storage participating in energy and reserve markets with an optimal frequency regulation modeling," Applied Energy, Elsevier, vol. 350(C).
  • Handle: RePEc:eee:appene:v:350:y:2023:i:c:s0306261923010851
    DOI: 10.1016/j.apenergy.2023.121721
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    Cited by:

    1. Sun, Xiaotian & Xie, Haipeng & Qiu, Dawei & Xiao, Yunpeng & Bie, Zhaohong & Strbac, Goran, 2023. "Decentralized frequency regulation service provision for virtual power plants: A best response potential game approach," Applied Energy, Elsevier, vol. 352(C).

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