With large scale wind farms integrating into electric power systems

the risks caused by the wind power ramp continuously increases. Accurate wind power ramp forecasting is of great importance for the secure and economic operation of power systems. A regional wind power forecasting method during the ramp periods is proposed by using meteorological measurement field data. The wind speed matrix extracted from the measurement field is decomposed into various spatial modes and principal components through empirical orthogonal function (EOF) decomposition

which encodes regional wind speed field dynamics during ramp periods. The mapping between the decomposed principal components and regional wind power is constructed by using multiple variable nonlinear regression method. To address wind speed prediction error

the interval EOF decomposition is used

adapting the proposed forecasting method to the uncertainty of measurement data. The forecasting results from a region with multiple wind farms demonstrate that the proposed method significantly improves the precision of regional wind power forecasting during ramp periods

and shows strong robustness against wind speed prediction error. This work is supported by National Natural Science Foundation of China (No. 51207082

No. 51177093) and National High Technology Research and Development Program of China (863 Program) (No. 2011AA05A101).