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A MILP Model for Revenue Optimization of a Compressed Air Energy Storage Plant with Electrolysis

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  • Ann-Kathrin Klaas

    (Institute of Electrical Power Engineering and Energy Systems, Clausthal University of Technology, Leibnizstraße 28, 38678 Clausthal-Zellerfeld, Germany)

  • Hans-Peter Beck

    (Institute of Electrical Power Engineering and Energy Systems, Clausthal University of Technology, Leibnizstraße 28, 38678 Clausthal-Zellerfeld, Germany)

Abstract

Energy storage, both short- and long-term, will play a vital role in the energy system of the future. One storage technology that provides high power and capacity and that can be operated without carbon emissions is compressed air energy storage (CAES). However, it is widely assumed that CAES plants are not economically feasible. In this context, a mixed-integer linear programming (MILP) model of the Huntorf CAES plant was developed for revenue maximization when participating in the day-ahead market and the minute-reserve market in Germany. The plant model included various plant variations (increased power and storage capacity, recuperation) and a water electrolyzer to produce hydrogen to be used in the combustion chamber of the CAES plant. The MILP model was applied to four use cases that represent a market-orientated operation of the plant. The objective was the maximization of revenue with regard to price spreads and operating costs. To simulate forecast uncertainties of the market prices, a rolling horizon approach was implemented. The resulting revenues ranged between EUR 0.5 Mio and EUR 7 Mio per year and suggested that an economically sound operation of the storage plant is possible.

Suggested Citation

  • Ann-Kathrin Klaas & Hans-Peter Beck, 2021. "A MILP Model for Revenue Optimization of a Compressed Air Energy Storage Plant with Electrolysis," Energies, MDPI, vol. 14(20), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6803-:d:659139
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    Cited by:

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    2. Nikita Dmitrievich Senchilo & Denis Anatolievich Ustinov, 2021. "Method for Determining the Optimal Capacity of Energy Storage Systems with a Long-Term Forecast of Power Consumption," Energies, MDPI, vol. 14(21), pages 1-25, October.
    3. Jakub Ochmann & Michał Jurczyk & Krzysztof Rusin & Sebastian Rulik & Łukasz Bartela & Wojciech Uchman, 2024. "Solution for Post-Mining Sites: Thermo-Economic Analysis of a Large-Scale Integrated Energy Storage System," Energies, MDPI, vol. 17(8), pages 1-21, April.

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