The Basic Research Of Wind Power Spatial Correlation Prediction Based On Monsoon Characteristics

In recent years, wind power industry develops quickly in the world. But windpower generation mainly depends on the wind speed, so the wind speed predictionaccuracy contributes to the stable operation of power system, the best efficiency ofwind energy, which has very strong social value and economic value.The wind speed data obtained from wind field has a certain noise, its existenceaffects wind speed upper limit accurately. How to separate the noise from wind speeddata accurately, and study the correlation between wind speeds and how to forecastwind speed reasonably, are the focus of this paper.The contents of this paper are as follows:(1) A low order nonlinear transform—Square Root Transform (SRT) is studied tothe effect of wavelet threshold denoising. In this experiment, the standard signal plusoutliers and jumping point is tested, it proves when outlier value L [-0.7340,0.4314], after SRT, becomes L [-0.7376,0.48035], the interval length of L increases4.509%, the stability of wavelet threshold denoising effect is enhanced, and givereasonable theoretical interpretation.(2) Based on Statistical Principle-Difference together with the wavelet denoisingtheory, we respectively separate white noise from wind speed in the monsoon regionsof China during four periods, making a lot of experiments and analysis, The researchbelongs to prediction accuracy upper limit and forecast research of "mechanism+identification" prediction strategy.(3) Taking advantage of Pearson Product-Moment Correlation Coefficient（PMCC），we judge the degree of wind speed spatial correlation in monsoon region,and the "Fisher z transformation" is used to estimate the confidence interval ofPPMCC, providing the precondition for the partial least squares to predict wind speed.(4) We provide a new theory—Wind Power Automatic Prediction System basedon the Internet of Things, improving the accuracy of wind power forecasting further.