Wind Power Correction Prediction Considering Similar Wind Power Climbing Events

In response to the issues of wind turbine ramp events affecting the safe and stable operation of power systems and the accuracy of wind power prediction, a wind power correction prediction method is proposed considering similar ramp events. The Whale Optimization Algorithm (WOA) is utilized to optimize the parameters of the Least Squares Support Vector Machine (LSSVM) for initial wind power prediction. Extracting ramp events by using the wind power ramp identification method based on extremum point extraction from the predicted results. To cope with the variable time windows of the identified ramp events, the Dynamic Time Warping (DTW) method is employed to identify similar ramp events from historical data. Finally, a second prediction is conducted based on similar historical ramp events to obtain the corrected wind power prediction. Experimental results show that the proposed method can improve the short-term prediction accuracy of wind power effectively.