Method for predicating interval probability of short-term wind power

The invention discloses a method for predicating interval probability of short-term wind power. The method comprises the following steps: acquiring a number of historical wind power from a wind power plant as a sample set; establishing optimization criteria according to the prediction interval coverage probability, the prediction interval bandwidth mean square root and the prediction interval average offset; establishing the interval predicating model of the short-term wind power based on an artificial bee colony nerve network, optimizing and updating a nerve network weight threshold to the optimization criteria through an artificial bee colony algorithm; according to the optimal weight threshold, establishing a nerve network and performing interval predication to the wind power to be predicated; performing state division to the historical wind power, establishing a Markov chain prediction model, and calculating the transition probability of each status; predicating the wind power interval according to the Markov chain status transition probability and the interval predication, and calculating the probability of the numerical point in the predication interval. When the short-term wind power interval predication is executed, the probability distribution of the numerical point in the interval is considered, thus the method can provide the basis to an optimization system.