Research on variable pitch control strategy of direct-driven offshore wind turbine using KELM wind speed soft sensor

Abstract

This study proposes a modeling method of soft measurement of offshore wind speed using Kernal Extreme Learning Machine (KELM). The soft measurement model of offshore wind speed is presented based on the data-driven method and kernel function extreme learning machine. An improved gray Wolf optimization algorithm is applied to optimize its parameters to enhance the measurement accuracy. Finally, based on the established offshore wind speed measurement model, a feedforward and feedback variable rotor controller is designed and verified by simulation, which proves the effectiveness of the research in this study.