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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Veröffentlicht in:	Journal of energy storage Jg. 103; S. 114096
Hauptverfasser:	Favaro, Pietro, Gobert, Maxime, Toubeau, Jean-François
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.12.2024 Elsevier
Schlagworte:	Computer Science Electricity markets Engineering Sciences Machine Learning Mixed-integer linear programming Multi-fidelity optimization Operations Research Pumped hydro energy storage Statistics Surrogate-based optimization algorithms Multi-fidelity optimization 90C26 Pumped hydro energy storage Surrogate-based optimization algorithms Electricity markets Mixed-integer linear programming
ISSN:	2352-152X, 2352-1538
Online-Zugang:	Volltext
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