Title :
Electric power supply and demand early warning based on PCA and SVM method
Author :
Jinchao, Li ; Jinying, Li
Author_Institution :
Sch. of Econ. & Manage., North China Electr. Power Univ., Beijing, China
Abstract :
The risk of electric power supply and demand is becoming more and more outstanding. So in order to avoid electric power supply and demand risks, we should set up the electric power supply and demand early warning management system. In this paper, the influencing factors of electric power supply and demand are analyzed, and then the principal component analysis method is used to reduce factors, then the support vector machine method is used to realize the early warning of the electric power supply and demand. At last, it is validated that the results by this method is feasible for early warning.
Keywords :
power engineering computing; power supply quality; principal component analysis; support vector machines; PCA; SVM; demand early warning management system; demand risks; electric power supply; principal component analysis; support vector machine; Indexes; Industries; Power systems; Principal component analysis; Supply and demand; Support vector machines; Training;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-0813-8
DOI :
10.1109/ICICIP.2011.6008428
