WIND TURBINE HEALTH STATE ASSESSMENT BASED ON STOCHASTIC COMBINATION WEIGHTING FUZZY EVALUATION

Li Jinyou; Li Yuan; Feng Bing; Xing Zuoxia; Xu Zengjin

doi:10.19912/j.0254-0096.tynxb.2020-1416

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (8) : 340-351. DOI: 10.19912/j.0254-0096.tynxb.2020-1416

WIND TURBINE HEALTH STATE ASSESSMENT BASED ON STOCHASTIC COMBINATION WEIGHTING FUZZY EVALUATION

Li Jinyou¹, Li Yuan¹, Feng Bing², Xing Zuoxia³, Xu Zengjin⁴

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Abstract

Since the randomness of health indicator weights will reduce the sensitivity of wind turbine states evaluation, this paper proposes a fuzzy evaluation method based on a random combination weight to evaluate the health state of wind turbines. Firstly, the supervisory control and data acquisition （SCADA） data of wind farms are analyzed through correlation, variance, skewness aspects. Combined with the IEC61400-1 standard, a health states evaluation indicator framework of wind turbines is established, and the weighting formula is obtained based on the optimal combination of random factors, by which to improve the weight accuracy of the evaluation indicator layer. Then, to fully cover the data deterioration of evaluation indicators, the membership calculation function of health indicator deterioration is established based on the ridge distribution function. Combined with the random combination weight and membership function, a fuzzy comprehensive evaluation mathematical model for wind turbine health state is established. Through hierarchical evaluation of wind turbine health state indicator framework, the health grade of the wind turbine is obtained, and fault warning is realized. Finally, multiple units in the Dalian Tuoshan wind farm are evaluated. The results show that, compared with the combined weighted cloud model, the sensitivity of the proposed method is enhanced by 1.85%, which can accurately evaluate the health state of wind turbines.

Key words

wind turbines / SCADA system / fuzzy comprehensive evaluation method / condition assessment / random factor / random combination weighting

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Li Jinyou, Li Yuan, Feng Bing, Xing Zuoxia, Xu Zengjin. WIND TURBINE HEALTH STATE ASSESSMENT BASED ON STOCHASTIC COMBINATION WEIGHTING FUZZY EVALUATION[J]. Acta Energiae Solaris Sinica. 2022, 43(8): 340-351 https://doi.org/10.19912/j.0254-0096.tynxb.2020-1416

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