Abstract Wind power output has a high degree of randomness, so it is difficult to describe accurately with some typical probability distribution. The extreme values influence the sample’s general non-parametric kernel density estimation method, and estimated results are relatively conservative. A wind interval prediction method based on robust proposed improve compactness accuracy prediction. I...

The preliminary unit root test has been found to be a useful tool for improving the accuracy of a one-step-ahead predictor and prediction interval for the first-order autoregressive process when an autoregressive coefficient is close to one. This paper applies the aforementioned concepts of the preliminary unit root test in order to improve the efficiency of prediction intervals for the Gaussia...