The invention discloses a wind power non-parametric probability interval ultra-short-term prediction method. The method is based on adaptive LASSO and an extreme learning machine. Firstly, nonlinear quantile regression is carried out on a wind power sequence to obtain self-adaptive adjustment parameters; an optimal quantile regression model output coefficient is calculated based on an extreme learning machine by utilizing quantile regression based on adaptive LASSO and an improved Bayesian information criterion; and finally, a wind power time sequence is input to obtain an ultra-short-term prediction value. According to the quantile regression prediction model constructed through the method, the interval score is obviously superior to that of a traditional prediction model based on quantile regression, the prediction precision and interval width comprehensive indexes are good, and the reliability of wind power prediction is greatly improved.