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Wind power prediction using time-series analysis base on rough sets

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4 Author(s)
Gao Shuang ; School of Automation, Beijing Institute of Technology, China ; Dong Lei ; Tian Chengwei ; Liao Xiaozhong

In long-term prediction, dealing with the relevant factors correctly is the key point to improve the wind power prediction accuracy. The key factors that affect the wind power prediction are identified by rough set theory and then the additional inputs of the prediction model are determined. To test the approach, the weather data from Beijing area are used for this study. The prediction results are presented and compared to the chaos neural network model and persistence model. The results show that rough set method will be a useful tool in longterm prediction of wind power.

Published in:

Electric Information and Control Engineering (ICEICE), 2011 International Conference on

Date of Conference:

15-17 April 2011