Prediction of wind power ramp events is important to the stability operation of power system, it is realized by combining wind power prediction of several continuous units for long-term power prediction, then using detecting algorithms to extract ramps. A prediction unit is a prediction time window. Its size impacts the accuracy of predicting ramps, and an optimization model is proposed to select the suitable window size. First, a swinging door algorithm is applied to extract ramp events from historical data. A model for optimizing the time window size is established based on the minimum non-ramp data in a ramp window. The solution of the proposed model is discussed, including the selection of variables, constraints and algorithm. The model presented in this paper is tested, and performance of selected time window is discussed. Computational analysis demonstrates the validity of the model. (C) 2017 Elsevier Ltd. All rights reserved.