Short-term forecast method of wind power output based on multi-scale CNN-LSTM in extreme weather Article Swipe
Yan Zhang
,
Huaying Su
,
Rongrong Wang
,
Jiali Deng
,
Yin Wang
,
Wei Guo
,
Run Li
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.ijepes.2025.111191
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.ijepes.2025.111191
It is often difficult to accurately capture wind power variation rules under extreme weather conditions, resulting in large forecasting errors. Therefore, a short-term forecast method for wind power output based on multi-scale CNN-LSTM under extreme weather conditions was designed. The truncated normal distribution was used to model the impact intensity of extreme weather, the Kalman filter was applied to wind speed correction, and the prediction equation coefficient of the current moment was modified by real-time feedback of the prediction error of the previous moment. The XGBoost model was introduced to estimate the prediction error of the wind power output, and the prediction models of the multi-scale CNN and LSTM were combined. Power residuals were used as learning targets to predict the power to be corrected using convolution kernels of different sizes to extract features from different span temporal neighborhoods, and the final predicted power was obtained. The experimental results showed that the predicted power of the design method was consistent with the measured power. The predicted value of the predicted wind speed at all sample points is very close to the real value, and the relative frequency distribution of the error is more concentrated and close to zero, which can improve the accuracy of the prediction.
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- article
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- https://doi.org/10.1016/j.ijepes.2025.111191
- OA Status
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- 18
- OpenAlex ID
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https://openalex.org/W4415289830Canonical identifier for this work in OpenAlex
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https://doi.org/10.1016/j.ijepes.2025.111191Digital Object Identifier
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Short-term forecast method of wind power output based on multi-scale CNN-LSTM in extreme weatherWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-10-17Full publication date if available
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Yan Zhang, Huaying Su, Rongrong Wang, Jiali Deng, Yin Wang, Wei Guo, Run LiList of authors in order
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https://doi.org/10.1016/j.ijepes.2025.111191Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.ijepes.2025.111191Direct OA link when available
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18Number of works referenced by this work
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