Title: Analysis of data mining method for short-term wind measurement of wind farm based on multi-technology fusion
Authors: Jianfeng Che; Bo Wang; Shitao Chen
Addresses: China Electric Power Research Institute, Haidian District, Beijing 100192, China ' China Electric Power Research Institute, Haidian District, Beijing 100192, China ' Guangzhou Maxkwh Information Technology Co., Ltd., Guangzhou, Guangdong 514000, China
Abstract: Aiming at the problems of poor noise reduction effect of current methods for short-term wind measurement data, poor fitting between wind measurement values and real values, and long running time of the methods, a data mining method for short-term wind measurement of wind farm based on multi-technology fusion is proposed. The anomaly points in the short-term wind data are found and corrected. The short-term wind data are de-noised by wavelet decomposition and normalised. The short-term wind speed measurement of wind farms at each time is carried out, and the short-term wind measurement data mining of wind farms is finally realised. The experimental results show that the proposed method has better noise reduction effect for short-term wind measurement data, the fitting degree between wind measurement value and real value is higher, and the running time of the method is shorter. All the above results verify the effectiveness of the proposed method.
Keywords: multi-technology fusion; wind farm; short-term wind measurement; data mining.
International Journal of Information and Communication Technology, 2020 Vol.17 No.3, pp.211 - 225
Received: 05 Jun 2019
Accepted: 30 Jul 2019
Published online: 04 Aug 2020 *