STUDY ON MUTI-PARAMETER MODEL OF WIND TURBINE BLADE ICING DETECTION AND WARNING

Liu Qingchao; Guo Peng; Zhang Wei; Zhang Yinlong; Zhang Yongming

doi:10.19912/j.0254-0096.tynxb.2020-0292

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (2) : 402-407. DOI: 10.19912/j.0254-0096.tynxb.2020-0292

STUDY ON MUTI-PARAMETER MODEL OF WIND TURBINE BLADE ICING DETECTION AND WARNING

Liu Qingchao¹, Guo Peng², Zhang Wei¹, Zhang Yinlong¹, Zhang Yongming¹

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Abstract

This paper detailed analyzes the influences of the ice accretion on wind turbine performance and parameters. Output power, rotor speed and ambient temperature are selected as monitoring variables for blade ice accretion. Models are constructed using Gaussian Process Regression （GPR） to timely monitor output power and rotor speed parameters. Sequential Probability Ratio Test （SPRT） is introduced to analyze the predicting residual in order to detect the output power and rotor speed abnormalities. If three conditions including power abnormality, rotor speed abnormality, and ambient temperature near zero Celsius degree occur coincidence, blade icing alarm is triggered. The effectiveness of the proposed method is verified by taking the actual data of blade icing in a plateau wind farm in Yunnan as an example.

Key words

wind turbines / blades / condition monitoring / icing / multi-parameter model

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Liu Qingchao, Guo Peng, Zhang Wei, Zhang Yinlong, Zhang Yongming. STUDY ON MUTI-PARAMETER MODEL OF WIND TURBINE BLADE ICING DETECTION AND WARNING[J]. Acta Energiae Solaris Sinica. 2022, 43(2): 402-407 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0292

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