Wind Energy Science
Wind Energy Science
WES
Articles | Volume 10, issue 3
Articles | Volume 10, issue 3
https://doi.org/10.5194/wes-10-559-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-10-559-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 3
Research article
 | 
19 Mar 2025
Research article |  | 19 Mar 2025

Enabling efficient sizing of hybrid power plants: a surrogate-based approach to energy management system modeling

Charbel Assaad, Juan Pablo Murcia Leon, Julian Quick, Tuhfe Göçmen, Sami Ghazouani, and Kaushik Das

Viewed

Total article views: 1,674 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
686 184 804 1,674 50 73
  • HTML: 686
  • PDF: 184
  • XML: 804
  • Total: 1,674
  • BibTeX: 50
  • EndNote: 73
Views and downloads (calculated since 12 Aug 2024)
Cumulative views and downloads (calculated since 12 Aug 2024)

Viewed (geographical distribution)

Total article views: 1,674 (including HTML, PDF, and XML) Thereof 1,637 with geography defined and 37 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 07 Aug 2025
Download
Short summary
This research develops a new method for assessing hybrid power plant (HPP) profitability, combining wind and battery systems. It addresses the need for an efficient, accurate, and comprehensive operational model by approximating a state-of-the-art energy management system (EMS) for spot market power bidding using machine learning. The approach significantly reduces computational demands while maintaining high accuracy. It thus opens new possibilities in terms of optimizing the design of HPPs.
Read more
Share
Altmetrics
Final-revised paper
Preprint