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Trust Region Policy Optimization-based pitch control for Floating Offshore Wind Turbines in above-rated wind conditions

Author

Listed:
  • Didier, Flavie
  • Laghrouche, Salah
  • Depernet, Daniel

Abstract

The control of Floating Offshore Wind Turbines (FOWTs) in Region III is challenging due to complex aerodynamic, hydrodynamic, and structural interactions. This paper presents a fully data-driven, model-free Deep Reinforcement Learning (DRL) controller based on the Trust Region Policy Optimization (TRPO) algorithm to regulate the collective blade pitch of a 5 MW semi-submersible FOWT. The controller was trained in high-fidelity simulations and experimentally validated in a wave basin using a Software-In-the-Loop (SIL) approach. Results show improved generator speed regulation and platform stability compared to a baseline Gain-Scheduling Proportional–Integral (GSPI) controller. However, performance degradation with generator speed overshoots was observed under extreme wind conditions. This study highlights the potential of DRL for FOWT control and identifies future directions to enhance robustness in harsh environments.

Suggested Citation

  • Didier, Flavie & Laghrouche, Salah & Depernet, Daniel, 2026. "Trust Region Policy Optimization-based pitch control for Floating Offshore Wind Turbines in above-rated wind conditions," Renewable Energy, Elsevier, vol. 256(PA).
    • Handle: RePEc:eee:renene:v:256:y:2026:i:pa:s0960148125015575
    DOI: 10.1016/j.renene.2025.123893
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    References listed on IDEAS

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    1. Hedi Basbas & Yong-Chao Liu & Salah Laghrouche & Mickaël Hilairet & Franck Plestan, 2022. "Review on Floating Offshore Wind Turbine Models for Nonlinear Control Design," Energies, MDPI, vol. 15(15), pages 1-27, July.
    2. Yolanda Vidal & Leonardo Acho & Ningsu Luo & Mauricio Zapateiro & Francesc Pozo, 2012. "Power Control Design for Variable-Speed Wind Turbines," Energies, MDPI, vol. 5(8), pages 1-18, August.
    3. Wakui, Tetsuya & Nagamura, Atsushi & Yokoyama, Ryohei, 2021. "Stabilization of power output and platform motion of a floating offshore wind turbine-generator system using model predictive control based on previewed disturbances," Renewable Energy, Elsevier, vol. 173(C), pages 105-127.
    4. Chan Roh, 2022. "Deep-Learning-Based Pitch Controller for Floating Offshore Wind Turbine Systems with Compensation for Delay of Hydraulic Actuators," Energies, MDPI, vol. 15(9), pages 1-18, April.
    5. Arash E. Samani & Jeroen D. M. De Kooning & Nezmin Kayedpour & Narender Singh & Lieven Vandevelde, 2020. "The Impact of Pitch-To-Stall and Pitch-To-Feather Control on the Structural Loads and the Pitch Mechanism of a Wind Turbine," Energies, MDPI, vol. 13(17), pages 1-21, September.
    6. Cheng, Zhengshun & Madsen, Helge Aagaard & Chai, Wei & Gao, Zhen & Moan, Torgeir, 2017. "A comparison of extreme structural responses and fatigue damage of semi-submersible type floating horizontal and vertical axis wind turbines," Renewable Energy, Elsevier, vol. 108(C), pages 207-219.
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