13th International Conference on Motion and Vibration Control; 12th International Conference on Recent Advances in Structural Dynamics | |
Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation | |
Urata, Kengo^1 ; Inoue, Masaki^1 ; Murayama, Dai^2 ; Adachi, Shuichi^1 | |
Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Yokohama, Kohoku-ku | |
223-8522, Japan^1 | |
Toshiba Corporation Power Systems Company, 2-4 Suehiro-cho, Yokohama, Tsurumi-ku | |
230-0045, Japan^2 | |
关键词: Auto regressive models; Box Cox transformation; Cascade structures; Gaussian white noise; Output distribution; Prediction accuracy; Short term prediction; Statistical modeling; | |
Others : https://iopscience.iop.org/article/10.1088/1742-6596/744/1/012176/pdf DOI : 10.1088/1742-6596/744/1/012176 |
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来源: IOP | |
【 摘 要 】
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.
【 预 览 】
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Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation | 656KB | download |