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Impact of modeling assumptions on the economic performance assessment of a storage participating in energy and reserve markets

Author

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  • Ahmed Mohamed

    (G2Elab-SYREL - G2Elab-SYstèmes et Réseaux ELectriques - G2ELab - Laboratoire de Génie Electrique de Grenoble - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes)

  • Rémy Rigo-Mariani

    (G2Elab-SYREL - G2Elab-SYstèmes et Réseaux ELectriques - G2ELab - Laboratoire de Génie Electrique de Grenoble - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, G2ELab - Laboratoire de Génie Electrique de Grenoble - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes)

  • Vincent Debusschere

    (Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes)

Abstract

This paper investigates the impact of key modeling assumptions for the sizing of a Battery Energy Storage Systems (BESSs) participating in energy and reserve markets. Most of the related studies in the literature assume oversimplifications of the operating conditions when computing the expected BESS revenues at the design stage. These considerations oftentimes consist of (i) constant operating efficiency of the BESS, (ii) neglected profit loss due to uncertainties in the operating phase, and (iii) degradation effects that are usually computed in a posteriori analysis. This paper then proposes to successively assess the impact of those modeling assumptions, deriving from a baseline scenario that embeds oversimplifications. At first, results are analyzed in terms of expected revenue decrease compared to the baseline for different BESS sizes, and with the participation in Day-Ahead (DA) and Frequency Containment Reserve (FCR) markets. The analysis reveals that up to 30 % overestimation (more than 60 % in the worst cases) of the profit along the project lifetime could be done in case where the key modeling assumption are simplified. Finally, a sensitivity analysis conducted with different trade-offs between BESS usage (i.e. degradation) and profits shows that the systems displaying power-to-energy ratios of 1 or 0.5 were the most profitable under the markets investigated.

Suggested Citation

  • Ahmed Mohamed & Rémy Rigo-Mariani & Vincent Debusschere, 2025. "Impact of modeling assumptions on the economic performance assessment of a storage participating in energy and reserve markets," Post-Print hal-05212162, HAL.
  • Handle: RePEc:hal:journl:hal-05212162
    DOI: 10.1016/j.est.2025.117998
    Note: View the original document on HAL open archive server: https://hal.science/hal-05212162v1
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    References listed on IDEAS

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    1. Ahmed Mohamed & Rémy Rigo-Mariani & Vincent Debusschere & Lionel Pin, 2024. "Operational Planning Strategies to Mitigate Price Uncertainty in Day-Ahead Market for a Battery Energy System," Post-Print hal-04628352, HAL.
    2. 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).
    3. Rigo-Mariani, Rémy & Chea Wae, Sean Ooi & Mazzoni, Stefano & Romagnoli, Alessandro, 2020. "Comparison of optimization frameworks for the design of a multi-energy microgrid," Applied Energy, Elsevier, vol. 257(C).
    4. Ahmed Mohamed & Rémy Rigo-Mariani & Vincent Debusschere & Lionel Pin, 2023. "Stacked Revenues for Energy Storage Participating in Energy and Reserve Markets with an Optimal Frequency Regulation Modeling," Post-Print hal-04182119, HAL.
    5. Rigo-Mariani, Rémy & Sareni, Bruno & Roboam, Xavier & Turpin, Christophe, 2014. "Optimal power dispatching strategies in smart-microgrids with storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 649-658.
    6. Seger, Pedro V.H. & Rigo-Mariani, Rémy & Thivel, Pierre-Xavier & Riu, Delphine, 2023. "A storage degradation model of Li-ion batteries to integrate ageing effects in the optimal management and design of an isolated microgrid," Applied Energy, Elsevier, vol. 333(C).
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