Title :
Wind power combination prediction based on the maximum information entropy principle
Author :
Han, Shuang ; Liu, Yongqian ; Li, Jinshan
Author_Institution :
Renewable Energy School, North China Electric Power University, Beijing, China
Abstract :
Wind power prediction is of great importance for the safety and stabilization of grids. The most important and difficult problem now is to enhance the prediction precision. A combined wind power prediction model based on the maximum information entropy principle was built in this paper. The wind power series is non-gauss distribution, so the prediction model involved high central moment besides the second central moment. The prediction results showed that the proposed model can improve the prediction precision.
Keywords :
combination prediction; the maximum information entropy principle; wind power;
Conference_Titel :
World Automation Congress (WAC), 2012
Conference_Location :
Puerto Vallarta, Mexico
Print_ISBN :
978-1-4673-4497-5