Wind power probability interval prediction based on Bootstrap quantile regression method

The study of the uncertainty of wind power is very important for power system planning and operation decision. This paper presents a method of wind power probability interval prediction based on Bootstrap quantile regression method. Due to the large difference in wind power data, the method first divides the power at equal intervals. And then use the Bootstrap method to extract the data in different power intervals to form the pseudo samples. Then use the quantile method to obtain the upper and lower limits of the confidence interval of each power interval. Finally, the upper and lower limits of the confidence intervals of multiple power intervals are combined by using the quantile regression method to obtain the probabilistic prediction interval of wind power. Let the interval coverage and average bandwidth as evaluation index. Let the interval coverage rate and average bandwidth as evaluation index. Through the Bootstrap quantile regression method, the interval coverage rate of wind power probability interval prediction is higher, the average bandwidth is narrower, the precision is higher and the effect is better.