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Scheduling power-intensive operations of Battery Energy Storage Systems and application to hybrid hydropower plants

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  • Cassano, Stefano
  • Sossan, Fabrizio

Abstract

This paper proposes a novel set of power constraints for Battery Energy Storage Systems (BESSs), referred to as Dynamic Power Constraints (DPCs), that account for the voltage and current limits of the BESS as a function of its State of Charge (SOC). These constraints are formulated for integration into optimization-based BESS scheduling problems, providing a significant improvement over traditional static constraints. It is shown that, under mild assumptions typically verified during practical operations, DPCs can be expressed as a linear function of the BESS power, thus making it possible to retrofit existing scheduling problems without altering their tractability property (i.e., convexity). The DCPs unify voltage and current constraints into a single framework, filling a gap between simplified models used in BESS schedulers and more advanced models in real-time controllers and Battery Management Systems (BMSs). By improving the representation of the BESS’s power capability, the proposed constraints enable schedulers to make more reliable and feasible decision, especially in power-intensive applications where the BESS operates near its rated power. To demonstrate the effectiveness of the DPCs, a simulation-based performance evaluation is conducted using a hybrid system comprising a 230 MW Hydropower Plant (HPP) and a 750 kVA/500 kWh BESS. Compared to state-of-the-art formulations such as static power constraints and DPC formulations without voltage constraints the proposed method reduces BESS constraint violations by 93% during real-time operations.

Suggested Citation

  • Cassano, Stefano & Sossan, Fabrizio, 2025. "Scheduling power-intensive operations of Battery Energy Storage Systems and application to hybrid hydropower plants," Applied Energy, Elsevier, vol. 386(C).
  • Handle: RePEc:eee:appene:v:386:y:2025:i:c:s0306261925002892
    DOI: 10.1016/j.apenergy.2025.125559
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    References listed on IDEAS

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    1. Zhang, Dong & Shafiullah, G.M. & Das, Choton K. & Wong, Kok Wai, 2025. "Optimal allocation of battery energy storage systems to improve system reliability and voltage and frequency stability in weak grids," Applied Energy, Elsevier, vol. 377(PB).
    2. Bennett, Christopher J. & Stewart, Rodney A. & Lu, Jun Wei, 2015. "Development of a three-phase battery energy storage scheduling and operation system for low voltage distribution networks," Applied Energy, Elsevier, vol. 146(C), pages 122-134.
    3. Giacomo Talluri & Gabriele Maria Lozito & Francesco Grasso & Carlos Iturrino Garcia & Antonio Luchetta, 2021. "Optimal Battery Energy Storage System Scheduling within Renewable Energy Communities," Energies, MDPI, vol. 14(24), pages 1-23, December.
    4. Sun, Fengchun & Xiong, Rui & He, Hongwen & Li, Weiqing & Aussems, Johan Eric Emmanuel, 2012. "Model-based dynamic multi-parameter method for peak power estimation of lithium–ion batteries," Applied Energy, Elsevier, vol. 96(C), pages 378-386.
    5. Gupta, Rahul & Sossan, Fabrizio, 2023. "Optimal sizing and siting of energy storage systems considering curtailable photovoltaic generation in power distribution networks," Applied Energy, Elsevier, vol. 339(C).
    6. 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).
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