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Wind Power Prediction Based on Nonlinear Partial Least Square
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Wind power prediction is important for the smart grid safe operation and scheduling, and it can improve the economic and technical penetration of wind energy.
The intermittent and the randomness of wind would affect the accuracy of prediction.
According to the sequence correlation between wind speed and wind power data, we propose a method for short-term wind power prediction.
The proposed method adopts the wind speed in every sliding data window to obtain the continuous prediction of wind power.
Then, the nonlinear partial least square is adopted to map the wind speed under the time series to wind power.
The model carries the neural network as the nonlinear function to describe the inner relation, and the outputs of hidden layer nodes are the extension term of the original independent input matrix to partial least squares regression.
To verify the effectiveness of the proposed algorithm, the real data of wind power with different working conditions are adopted in experiments.
The proposed method, backpropagation neural network, radial basis function neural network, support vector machine, and partial least square are performed on the real data and their effectiveness is compared.
The experimental results show that the proposed algorithm has higher precision, and the real power running curves also verify that the proposed method can predict the wind power in short-term effectively.
American Psychological Association (APA)
Wang, Qian& Lei, Yang& Cao, Hui. 2018. Wind Power Prediction Based on Nonlinear Partial Least Square. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1208577
Modern Language Association (MLA)
Wang, Qian…[et al.]. Wind Power Prediction Based on Nonlinear Partial Least Square. Mathematical Problems in Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1208577
American Medical Association (AMA)
Wang, Qian& Lei, Yang& Cao, Hui. Wind Power Prediction Based on Nonlinear Partial Least Square. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1208577
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208577