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

Lin Pan, Yong Xiong, Ze Zhu and Leichong Wang

Renewable Energy, 2022, vol. 184, issue C, 1002-1017

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.

Keywords: Offshore wind speed soft sensor; Kernal extreme learning machine(KELM); Improved gray worf algorithm; Pitch control; Offshore wind turbine (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:184:y:2022:i:c:p:1002-1017

DOI: 10.1016/j.renene.2021.11.104

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