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

Volume

2

fYear

2011

fDate

25-28 July 2011

Firstpage

1119

Lastpage

1123

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4577-0813-8

Type

conf

DOI

10.1109/ICICIP.2011.6008428

Filename

6008428