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• W2527658627 abstract "We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon." @default.
• W2527658627 created "2016-10-07" @default.
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• W2527658627 date "2016-09-01" @default.
• W2527658627 modified "2023-10-17" @default.
• W2527658627 title "Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation" @default.
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• W2527658627 doi "https://doi.org/10.1088/1742-6596/744/1/012176" @default.
• W2527658627 hasPublicationYear "2016" @default.
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