Tool for optimization of sale and storage of energy in wind farms
![Thumbnail](/xmlui/bitstream/handle/10234/205204/86667.pdf.jpg?sequence=4&isAllowed=y)
Ver/ Abrir
Impacto
![Google Scholar](/xmlui/themes/Mirage2/images/uji/logo_google.png)
![Microsoft Academico](/xmlui/themes/Mirage2/images/uji/logo_microsoft.png)
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7034
comunitat-uji-handle3:10234/8619
comunitat-uji-handle4:
INVESTIGACIONMetadatos
Título
Tool for optimization of sale and storage of energy in wind farmsFecha de publicación
2023Editor
ElsevierCita bibliográfica
E. Celades, E. Perez, N. Aparicio et al., Tool for optimization of sale and storage of energy in wind farms, Mathematics and Computers in Simulation (2023), ´ https://doi.org/10.1016/j.matcom.2023.03.010.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.sciencedirect.com/science/article/pii/S0378475423001167Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
In this work we address the problem of energy management in a wind farm supported by an Energy Storage System (ESS) that operates in an electricity market with six intraday sessions and with penalty policies for ... [+]
In this work we address the problem of energy management in a wind farm supported by an Energy Storage System (ESS) that operates in an electricity market with six intraday sessions and with penalty policies for imbalances between commitments and the energy really injected. We face it through a cascade of model predictive controllers that also require the design of predictors for wind and electricity market price forecasts. The master controller is executed synchronously with the market sessions and decides the commitments. The slave controller is executed each hour and decides the energy that should be sold to minimize the economical penalties if the commitment is not achievable. Finally, a real-time controller decides how to manage the energy storage in the ESS to sell the desired energy when possible. We use historical real data for the design and validation of the approach and show its benefits. The results show that the cascade structure helps to adequately adapt the energy committed in the intraday market. We also obtain the necessary prices on batteries so that their use is profitable. [-]
Publicado en
Mathematics and Computers in Simulation, 2023Entidad financiadora
Agencia Estatal de Investigación | Universitat Jaume I
Código del proyecto o subvención
PID2020-112943RB-I00 | PID2021-125634OB-I00 | TED2021-130120B-C22 | ERDF | EU | UJI-B2021-35
Derechos de acceso
info:eu-repo/semantics/openAccess
Aparece en las colecciones
- ESID_Articles [477]
Excepto si se señala otra cosa, la licencia del ítem se describe como: 0378-4754/© 2023 The Author(s). Published by Elsevier B.V. on behalf of International Association for Mathematics and Computers in
Simulation (IMACS). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).