Multi-fidelity optimization for the day-ahead scheduling of Pumped Hydro Energy Storage
Optimizing the operation of Pumped-Hydro Energy Storage (PHES) requires accurately representing nonlinearities, such as reservoir geometry and water-power conversion efficiency. While traditional methods like Mixed-Integer Linear Programming (MILP) offer theoretical guarantees, they rely on approxim...
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| Vydané v: | Journal of energy storage Ročník 103; s. 114096 |
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| Hlavní autori: | , , |
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| Jazyk: | English |
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Elsevier Ltd
01.12.2024
Elsevier |
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| ISSN: | 2352-152X, 2352-1538 |
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| Abstract | Optimizing the operation of Pumped-Hydro Energy Storage (PHES) requires accurately representing nonlinearities, such as reservoir geometry and water-power conversion efficiency. While traditional methods like Mixed-Integer Linear Programming (MILP) offer theoretical guarantees, they rely on approximations that can lead to suboptimal decisions and costly redispatch or penalties. Because of its inherent approximations, MILP is a low-fidelity optimization model. In this paper, we propose a multi-fidelity approach that combines MILP with a Surrogate-Based Optimization Algorithm (SBOA). MILP solutions are used as warm-starts for the SBOA, which refines the solutions using a high-fidelity simulator of PHES dynamics and redispatch costs. This allows the SBOA to handle nonlinearities and improve the initial MILP solution by exploring areas with higher expected value. Our approach is tested on a PHES unit that participates in the energy and reserve markets in Belgium. The results show that, despite the extensive efforts made in MILP modeling, decisions can still be improved through smart integration with SBOAs.
•Exact optimization is augmented with global search methods.•The method is applied to the scheduling of Pumped Hydro Energy Storage.•MILP’s fast results are used as warm-start for higher-fidelity optimization search.•We find the best trade-off regarding the resources allocated to each method.•Multi-fidelity can strongly reduce the gap between ex-ante and ex-post profits. |
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| AbstractList | Optimizing the operation of Pumped-Hydro Energy Storage (PHES) requires accurately representing nonlinearities, such as reservoir geometry and water-power conversion efficiency. While traditional methods like Mixed-Integer Linear Programming (MILP) offer theoretical guarantees, they rely on approximations that can lead to suboptimal decisions and costly redispatch or penalties. Because of its inherent approximations, MILP is a low-fidelity optimization model. In this paper, we propose a multi-fidelity approach that combines MILP with a Surrogate-Based Optimization Algorithm (SBOA). MILP solutions are used as warm-starts for the SBOA, which refines the solutions using a high-fidelity simulator of PHES dynamics and redispatch costs. This allows the SBOA to handle nonlinearities and improve the initial MILP solution by exploring areas with higher expected value. Our approach is tested on a PHES unit that participates in the energy and reserve markets in Belgium. The results show that, despite the extensive efforts made in MILP modeling, decisions can still be improved through smart integration with SBOAs.
•Exact optimization is augmented with global search methods.•The method is applied to the scheduling of Pumped Hydro Energy Storage.•MILP’s fast results are used as warm-start for higher-fidelity optimization search.•We find the best trade-off regarding the resources allocated to each method.•Multi-fidelity can strongly reduce the gap between ex-ante and ex-post profits. |
| ArticleNumber | 114096 |
| Author | Gobert, Maxime Favaro, Pietro Toubeau, Jean-François |
| Author_xml | – sequence: 1 givenname: Pietro orcidid: 0009-0002-0782-4494 surname: Favaro fullname: Favaro, Pietro email: pietro.favaro@umons.ac.be organization: Power System and Market Research Group (PSMR), University of Mons, Boulevard Dolez 31, Mons, 7000, Wallonia, Belgium – sequence: 2 givenname: Maxime orcidid: 0000-0003-4925-4995 surname: Gobert fullname: Gobert, Maxime organization: Mathematics and Operational Research, Rue de Houdain 9, Mons, 7000, Wallonia, Belgium – sequence: 3 givenname: Jean-François orcidid: 0000-0001-9853-2694 surname: Toubeau fullname: Toubeau, Jean-François organization: Power System and Market Research Group (PSMR), University of Mons, Boulevard Dolez 31, Mons, 7000, Wallonia, Belgium |
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| Keywords | Multi-fidelity optimization 90C26 Pumped hydro energy storage Surrogate-based optimization algorithms Electricity markets Mixed-integer linear programming |
| Language | English |
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| Title | Multi-fidelity optimization for the day-ahead scheduling of Pumped Hydro Energy Storage |
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