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- W4385788825 abstract "In order to better characterize the power characteristics of wind power and improve the dispatching capacity of wind power farms, this paper proposes a wind power interval prediction model based on WA-KDEP. Firstly, on the basis of point prediction, the historical data is divided into multiple error intervals. Secondly, the accuracy of kernel density estimation method is improved, and the error of nonparametric kernel density estimation method is corrected by pseudo data method; At the same time, in order to improve the local adaptability of the model, the adaptive window width is adopted, and the gray wolf optimization algorithm is introduced to optimize the kernel density window width parameters to obtain the final prediction confidence interval. Experimental results show that the proposed method can give a suitable wind power interval, which can effectively help the actual scheduling decision-making." @default.
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- W4385788825 date "2023-01-01" @default.
- W4385788825 modified "2023-09-27" @default.
- W4385788825 title "Short-Term Wind Power Interval Prediction Based on WA-KDEP Algorithm Methodology Study" @default.
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- W4385788825 doi "https://doi.org/10.1007/978-981-99-3404-1_27" @default.
- W4385788825 hasPublicationYear "2023" @default.
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