SHORT-TERM WIND POWER PREDICTION BASED ON BLACK-WINGED KITE ALGORITHM AND VMD

Zhou Jintao; He Shan; Wang Weiqing; Cheng Jing; Fang Zhong; Chen Jun

doi:10.19912/j.0254-0096.tynxb.2024-1145

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (12) : 762-773. DOI: 10.19912/j.0254-0096.tynxb.2024-1145

SHORT-TERM WIND POWER PREDICTION BASED ON BLACK-WINGED KITE ALGORITHM AND VMD

Zhou Jintao¹, He Shan^1,2, Wang Weiqing^1,2, Cheng Jing^1,2, Fang Zhong³, Chen Jun³

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Abstract

To improve short-term wind power forecasting accuracy, a predictive model based on the Black Kite Algorithm （BKA） and Variational Mode Decomposition （VMD） was been proposed. Initially, the BKA algorithm was used to determine the VMD parameters, allowing VMD to decompose the data into multiple subsequences, which helps reduce the complexity and volatility of wind power time series. Each subsequence was then combined with essential meteorological data, creating input components for the predictive model, which is a hybrid framework involving a Temporal Convolutional Network （TCN）, Bidirectional Gated Recurrent Units （BiGRU）, and an attention mechanism. This composite model independently forecasts each input component, after which BKA optimizes the model’s hyperparameters to obtain the best combination scheme. The final wind power forecast was produced by summing and reconstructing the individual predictions. This model was validated using real wind power data from a wind farm in Xinjiang, and its performance was compared with five other combined forecasting models. Experimental results indicate that the prediction effect of the proposed model is superior to that of other predicition models, effectively enhancing the accuracy of short-term wind power forecasting.

Key words

wind power / prediction model / variational modal decomposition / temporal convolutional network / hyperparameter search

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Zhou Jintao, He Shan, Wang Weiqing, Cheng Jing, Fang Zhong, Chen Jun. SHORT-TERM WIND POWER PREDICTION BASED ON BLACK-WINGED KITE ALGORITHM AND VMD[J]. Acta Energiae Solaris Sinica. 2025, 46(12): 762-773 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1145

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