DocumentCode :
619951
Title :
Studies on wind farms ultra-short term NWP wind speed correction methods
Author :
Lei Dong ; Liang Ren ; Shuang Gao ; Yang Gao ; Xiaozhong Liao
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
fYear :
2013
fDate :
25-27 May 2013
Firstpage :
1576
Lastpage :
1579
Abstract :
Ultra-short term wind speed forecast for wind farm is of great significance to the real-time scheduling of wind power system. In this paper, NWP (Numerical Weather Prediction) wind speed time series and measured wind speed time series were decomposed into different bands by wavelet multi-resolution analysis. Pearson product-moment correlation coefficient was used to verify the correction premise. Then the linear correction method was used to correct the low frequency stationary NWP wind speed. To test the approach, the data from Yilan wind farm of Heilongjiang province were used. The results show that when a strong correlation exists in the system deviation of training periods and testing periods, the prediction accuracy of ultra-short term wind speed will be significantly improved.
Keywords :
correlation methods; load forecasting; power generation scheduling; power system measurement; time series; wavelet transforms; weather forecasting; wind power plants; Heilongjiang province; Pearson product-moment correlation coefficient; Yilan wind farm; linear correction method; low frequency stationary NWP wind speed; numerical weather prediction; real-time scheduling; ultrashort term wind speed forecasting; wavelet multiresolution analysis; wind power system; wind speed correction method; wind speed time series measurement; Correlation coefficient; Forecasting; Predictive models; Time series analysis; Wind farms; Wind forecasting; Wind speed; NWP; Ultra-short Term Prediction; Wavelet theory; Wind Farm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
Type :
conf
DOI :
10.1109/CCDC.2013.6561180
Filename :
6561180
Link To Document :
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