MULTI-STEP WIND SPEED PREDICTION METHOD BASED ON WIND SPEED SPATIAL-TIME CORRELATION

Pan Chao; Li Runyu; Wang Dian; Cai Guowei; Zhang Yonghui

doi:10.19912/j.0254-0096.tynxb.2020-0410

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (2) : 458-464. DOI: 10.19912/j.0254-0096.tynxb.2020-0410

MULTI-STEP WIND SPEED PREDICTION METHOD BASED ON WIND SPEED SPATIAL-TIME CORRELATION

Pan Chao¹, Li Runyu¹, Wang Dian¹, Cai Guowei¹, Zhang Yonghui²

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Abstract

Ultra-short-term prediction for considering the spatial correlation of wind speed is a research hotspot for large-scale wind power grid connection. This paper proposes a new multi-position and multi-step combined wind speed prediction method based on the spatial correlation of wind speed. The grey correlation analysis on each wind turbine in the wind farm is carried out, and then the pity beetle algorithm is adopted to perform optimal and reconstruct to obtain the target wind turbine and its adjacent space information. The convolutional neural network is used to extract the spatial features of the reconstructed matrix, which are input the long-short-term memory networks for multi-step prediction. Finally, the method in this paper is applied to different wind farms for wind speed prediction. The prediction accuracy and generalization ability of the proposed method are verified through comparative analysis.

Key words

multi-step wind speed prediction / grey correlation analysis / long-short-term memory networks / convolutional neural network / spatial-temporal correlation

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Pan Chao, Li Runyu, Wang Dian, Cai Guowei, Zhang Yonghui. MULTI-STEP WIND SPEED PREDICTION METHOD BASED ON WIND SPEED SPATIAL-TIME CORRELATION[J]. Acta Energiae Solaris Sinica. 2022, 43(2): 458-464 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0410

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