Studies on wind farms ultra-short term NWP wind speed correction methods

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.