Comparative Analysis of Battery Degradation Models for Optimal Operation of a Hybrid Power Plant in the Day-Ahead Energy Market

Ghanaee, Elahe, Pérez Díaz, Juan Ignacio ORCID: https://orcid.org/0000-0003-0657-8527, Fernández Muñoz, Daniel ORCID: https://orcid.org/0000-0003-1789-3151, Nájera Álvarez, Jorge ORCID: https://orcid.org/0000-0002-3396-0062 and Chazarra Jover, Manuel Joaquín ORCID: https://orcid.org/0000-0003-2221-220X (2025). Comparative Analysis of Battery Degradation Models for Optimal Operation of a Hybrid Power Plant in the Day-Ahead Energy Market. En: "2025 IEEE Kiel PowerTech", 29 June - 3 July 2025, Kiel, Germany. ISBN 979-8-3315-4397-6. https://doi.org/10.1109/PowerTech59965.2025.11180334.

Descripción

Título: Comparative Analysis of Battery Degradation Models for Optimal Operation of a Hybrid Power Plant in the Day-Ahead Energy Market
Autor/es:
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 2025 IEEE Kiel PowerTech
Fechas del Evento: 29 June - 3 July 2025
Lugar del Evento: Kiel, Germany
Título del Libro: 2025 IEEE Kiel PowerTech. Conference Proceedings
Fecha: 6 Octubre 2025
ISBN: 979-8-3315-4397-6
Materias:
ODS:
Escuela: E.T.S.I. Caminos, Canales y Puertos (UPM)
Departamento: Ingeniería Civil: Hidráulica, Energía y Medio Ambiente
Licencias Creative Commons: Ninguna

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Resumen

Battery degradation significantly impacts the operational costs and profitability of hybrid power plants (HPPs) participating in the day-ahead (DA) energy market. This paper conducts a comparative analysis of the effectiveness of three battery degradation models. The models calculate the battery degradation as a function of the energy throughput (TP model), the discharge maneuvers (DM model) and based on the Rainflow cycle counting algorithm (RF model). A deterministic mixed-integer linear programming model is developed to maximize revenue of HPPs participating in the DA market considering battery degradation costs. Numerical results reveal that the TP model provides the highest profitability in the DA energy market with the lowest computational complexity, while the RF and DM models capture the battery aging with higher accuracy. This comparative analysis offers some insights useful for selecting appropriate degradation models for better operational performance and longer battery life.

Proyectos asociados

Tipo
Código
Acrónimo
Responsable
Título
Gobierno de España
TED2021-132794B-C21
HYBRIDHYDRO
Juan Ignacio Pérez Díaz
Sin especificar

Más información

ID de Registro: 92399
Identificador DC: https://oa.upm.es/92399/
Identificador OAI: oai:oa.upm.es:92399
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/10421209
Identificador DOI: 10.1109/PowerTech59965.2025.11180334
URL Oficial: https://ieeexplore.ieee.org/document/11180334
Depositado por: Juan Ignacio Pérez Díaz
Depositado el: 16 Dic 2025 15:01
Ultima Modificación: 16 Dic 2025 15:02