Real-Time Performance Analyses and Optimal Gain-Scheduling Control of Offshore Wind Turbine under Ice Creep Loads

Abstract

At high latitudes, offshore wind turbines often face unfavorable loads by severe ice-induced vibrations during winter season, which may endanger facilities available on the platforms and degrade operating performance of wind turbine. Hence, it is vital to analyze the influences caused by ice loads. In this paper, based on a real-Time simulation model, quantifiable analyses of performance losses due to ice creep loads are firstly studied deeply. Under ice creep loads, reliable pitch control is necessary to ensure safety and high-level power-Tracking capability of modern offshore wind turbine. However, uncertain influences of ice creep loads are coupled with wind turbine operation and make it a challenge for wind turbine pitch control using traditional Proportional-Integral (PI) controller from the view of industry. As a result, improved pitch control using optimal gain-scheduling strategy is proposed to alleviate impacts of ice loads where the support vector regression algorithm is adopted to represent the strong nonlinear relationship among PI parameters under different operation conditions. For each operation point, PI parameters are optimally tuned by the particle swarm optimization algorithm. Finally, the presented nonlinear optimal gain-scheduling PI (OGS-PI) controller is applied on regulating generation power and reducing tower top displacement caused by ice creep loads based on software of Fatigue, Aerodynamics, Structures, and Turbulence, a high-fidelity wind turbine simulator. Simulation results show that unfavorable influence of ice creep loads to wind turbine operation can be significantly alleviated by the OGS-PI controller, which performs much better than the traditional PI controller.