Stratification-based wind power forecasting in a high penetration wind power system using a hybrid model with charged system search algorithm

摘要

This work proposes a novel stratification-based wind power forecasting method, and develops a hybrid forecasting model at different stratifications by using charged system search algorithm. The proposed model applies the concept of segmentation from the theory of optimal stratification to forecast short-term wind power outputs. Additionally, the proposed method elucidates different weighting values of each individual model at different segmentation blocks. Based on the forecasting results, the proposed stratification-based hybrid model outperforms traditional stand-alone models and un-stratified hybrid models in terms of forecasting accuracy, which verifies the proposed forecasting model for accurate wind power forecasting.