A Comprehensive Review on Advanced Control Methods for Floating Offshore Wind Turbine Systems above the Rated Wind Speed

Flavie Didier, Yong-Chao Liu (), Salah Laghrouche and Daniel Depernet
Additional contact information
Flavie Didier: Energy Department, FEMTO-ST Institute (UMR 6174), Université de Franche-Comté, UTBM, CNRS, 90010 Belfort, France
Yong-Chao Liu: Energy Department, FEMTO-ST Institute (UMR 6174), Université de Franche-Comté, UTBM, CNRS, 90010 Belfort, France
Salah Laghrouche: Energy Department, FEMTO-ST Institute (UMR 6174), Université de Franche-Comté, UTBM, CNRS, 90010 Belfort, France
Daniel Depernet: Energy Department, FEMTO-ST Institute (UMR 6174), Université de Franche-Comté, UTBM, CNRS, 90010 Belfort, France

Energies, 2024, vol. 17, issue 10, 1-33

Abstract: This paper presents a comprehensive review of advanced control methods specifically designed for floating offshore wind turbines (FOWTs) above the rated wind speed. Focusing on primary control objectives, including power regulation at rated values, platform pitch mitigation, and structural load reduction, this paper begins by outlining the requirements and challenges inherent in FOWT control systems. It delves into the fundamental aspects of the FOWT system control framework, thereby highlighting challenges, control objectives, and conventional methods derived from bottom-fixed wind turbines. Our review then categorizes advanced control methods above the rated wind speed into three distinct approaches: model-based control, data-driven model-based control, and data-driven model-free control. Each approach is examined in terms of its specific strengths and weaknesses in practical application. The insights provided in this review contribute to a deeper understanding of the dynamic landscape of control strategies for FOWTs, thus offering guidance for researchers and practitioners in the field.

Keywords: floating offshore wind turbine; advanced control methods; data-driven control; artificial intelligence (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/10/2257/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/10/2257/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:10:p:2257-:d:1390316

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().