LQG control for hydrodynamic compensation on large floating wind turbines. (March 2023)

• Record Type: Journal Article
• Authors: Hawari, Qusay; Kim, Taeseong; Ward, Christopher; Fleming, James
• Is Part Of: Renewable energy. Volume 205(2023)
• Page Start: 1
• Page End: 9
• Publication Date: 2023-03
• Subjects: Collective pitch control -- Floating Wind Turbine (FWT) -- OpenFAST -- Hydrodynamics -- Kalman filter -- Linear Quadratic Gaussian (LQG); Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2023.01.067
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: This work proposes a novel Linear Quadratic Gaussian (LQG)-based blade pitch control method for floating offshore wind turbines, in which a state-space model of the turbine and water hydrodynamics is included in the LQG design. The actuation considered is collective blade pitch control with the objective of generator power stabilisation and platform motion reduction. A linear Kalman filter is used to estimate un-measurable states relating to wave excitation and radiation through measurements of generator speed, platform pitch, and wind disturbance. Controller design models were validated with the full order nonlinear model under various testing conditions. The new controller design is tested on a nonlinear high-fidelity simulation model of the 15 Mega-Watt (MW) floating semi-submersible wind turbine. In simulations with realistic stochastic wind and wave disturbances, the new controller achieves 32% lower generator speed Root Mean Square Error (RMSE) and 16% lower platform pitch RMSE compared to a standard LQG controller that does not include hydrodynamic states, for equivalent levels of pitch actuation and with a 2 ° /sec rate limit on pitch. The inclusion of hydrodynamics in the controller design not only reduced platform pitching fluctuation, but also had a strong effect of hub-height factors such as the generator speed. Highlights: Evaluate LQG controllers on the recently released IEA 15 MW floating wind turbine. Incorporate wave excitation and radiation state space approximations in LQG control. Estimate non-measurable states for control of hydrodynamics using Kalman filters. Test controllers on stochastic wind and wave elevation cases in OpenFAST.