RESEARCH ON MEDIUM AND LONG TERM WIND SPEED FORECASTING AND CORRECTION BASED ON WRF MODEL

Zhang Fuqiang; Jin Chunwei; Zhou Hu; Lu Yanyan; Yang Shufeng; Nie Gaozhen

doi:10.19912/j.0254-0096.tynxb.2024-1591

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (1) : 585-592. DOI: 10.19912/j.0254-0096.tynxb.2024-1591

RESEARCH ON MEDIUM AND LONG TERM WIND SPEED FORECASTING AND CORRECTION BASED ON WRF MODEL

Zhang Fuqiang¹, Jin Chunwei², Zhou Hu², Lu Yanyan², Yang Shufeng³, Nie Gaozhen⁴

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Abstract

The mid-long term prediction of wind speed plays an important support for wind power generation and dispatching. Due to the highly variable and gusty characteristics of wind speed, exploring methods to improve wind speed forecasts has important practical significance. In this research, five parameterization schemes were used to predict the 10 m wind speed in spring and summer in the coastal areas of eastern China. A random-forest-based correction model was constructed based on the wind speed predicted by the optimal scheme and the corresponding observed wind speed. The results show that the performance of each WRF experiment on predicting the 10 m wind speed are close, and the simulated wind speed is greater than the observed wind speed. The P5 parameterization scheme yields the best performance for the 10 m wind speed prediction over the study area, with the highest wind speed prediction accuracy of 38%. After corrected by the random forest model, the wind speed prediction accuracy is increased to 53%, indicating that the correction effect is significant. Moreover, the correction improves more over the inland regions than over the offshore areas.

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wind farm / wind speed / forecasting / numerical simulation / random forests / correction / mid-long term / accuracy evaluation

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Zhang Fuqiang, Jin Chunwei, Zhou Hu, Lu Yanyan, Yang Shufeng, Nie Gaozhen. RESEARCH ON MEDIUM AND LONG TERM WIND SPEED FORECASTING AND CORRECTION BASED ON WRF MODEL[J]. Acta Energiae Solaris Sinica. 2026, 47(1): 585-592 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1591

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