LOAD PREDICTION METHOD FOR WIND TURBINES CONSIDERINGGRID VOLTAGE DISTURBANCES

Sun Yuyuan; Wang Xiaodong; Fu Deyi; Liu Yingming; Yang Bin

doi:10.19912/j.0254-0096.tynxb.2025-0370

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (7) : 144-152. DOI: 10.19912/j.0254-0096.tynxb.2025-0370

LOAD PREDICTION METHOD FOR WIND TURBINES CONSIDERINGGRID VOLTAGE DISTURBANCES

Sun Yuyuan¹, Wang Xiaodong¹, Fu Deyi², Liu Yingming¹, Yang Bin¹

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Abstract

In order to realize the rapid and convenient quantification of wind turbine load under voltage disturbance condition, this paper proposes a time series load prediction method for key parts of wind turbine driven by operation data based on TCN-iTransformer. Firstly, the correlation analysis of different measured quantities of load and power grid data and wind turbine operation data of key parts of the wind turbine is carried out to extract the key characteristic quantities. The outstanding local time series feature extraction ability of the temporal convolution network is used to capture the short-term dependencies in the time series data, and the iTransformer algorithm is used to model the nonlinear complex interaction between variables, so as to achieve accurate prediction of the load of key parts of the wind turbine. The analysis of the results based on the measured data shows that the prediction accuracy of the TCN-iTransformer model is significantly higher than that of the Transformer, iTransformer and other models.

Key words

wind turbines / load forecasting / prediction model / iTransformer algorithm / temporal convolutional networks / low voltage ride-through

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Sun Yuyuan, Wang Xiaodong, Fu Deyi, Liu Yingming, Yang Bin. LOAD PREDICTION METHOD FOR WIND TURBINES CONSIDERINGGRID VOLTAGE DISTURBANCES[J]. Acta Energiae Solaris Sinica. 2026, 47(7): 144-152 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0370

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