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Planning of Reserve Storage to Compensate for Forecast Errors

Author

Listed:
  • Julian Koch

    (Institute of Electric Power Systems, Leibniz Universität Hannover, 30167 Hanover, Germany)

  • Astrid Bensmann

    (Institute of Electric Power Systems, Leibniz Universität Hannover, 30167 Hanover, Germany)

  • Christoph Eckert

    (Institute of Electric Power Systems, Leibniz Universität Hannover, 30167 Hanover, Germany)

  • Michael Rath

    (Department of Civil and Environmental Engineering, Hochschule Bochum—Bochum University of Applied Sciences, 44801 Bochum, Germany
    Fraunhofer Institution for Energy Infrastructures and Geothermal Systems IEG, 44801 Bochum, Germany
    On Leave of GASAG Solution Plus GmbH, 10829 Berlin, Germany.)

  • Richard Hanke-Rauschenbach

    (Institute of Electric Power Systems, Leibniz Universität Hannover, 30167 Hanover, Germany)

Abstract

Forecasts and their corresponding optimized operation plans for energy plants never match perfectly, especially if they have a horizon of several days. In this paper, we suggest a concept to cope with uncertain load forecasts by reserving a share of the energy storage system for short-term balancing. Depending on the amount of uncertainty in the load forecasts, we schedule the energy system with a specific reduced storage capacity at the day-ahead market. For the day of delivery, we examine the optimal thresholds when the remaining capacity should be used to balance differences between forecast and reality at the intraday market. With the help of a case study for a simple sector-coupled energy system with a demand for cooling, it is shown that the energy costs could be reduced by up to 10% using the optimal reserve share. The optimal reserve share depends on the forecast quality and the time series of loads and prices. Generally, the trends and qualitative results can be transferred to other systems. However, of course, an individual evaluation before the realization is recommended.

Suggested Citation

  • Julian Koch & Astrid Bensmann & Christoph Eckert & Michael Rath & Richard Hanke-Rauschenbach, 2024. "Planning of Reserve Storage to Compensate for Forecast Errors," Energies, MDPI, vol. 17(3), pages 1-16, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:3:p:720-:d:1332302
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    References listed on IDEAS

    as
    1. Chen, Jun & Garcia, Humberto E., 2016. "Economic optimization of operations for hybrid energy systems under variable markets," Applied Energy, Elsevier, vol. 177(C), pages 11-24.
    2. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
    3. Zia, Muhammad Fahad & Elbouchikhi, Elhoussin & Benbouzid, Mohamed, 2018. "Microgrids energy management systems: A critical review on methods, solutions, and prospects," Applied Energy, Elsevier, vol. 222(C), pages 1033-1055.
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