DocumentCode
1876875
Title
Forecasting of electricity consumption: a comparative analysis of regression and artificial neural network models
Author
Fung, Y.H. ; Tummala, V. M Rao
Author_Institution
Dept. of Electr. & Electron. Eng., Hong Kong Univ., Hong Kong
fYear
1993
fDate
7-10 Dec 1993
Firstpage
782
Abstract
Several authors have formulated regression models to forecast electricity consumption. Also, more recently, several authors have attempted to formulate artificial neural network models to forecast electricity consumption. The authors have attempted in this paper to formulate and estimate both regression and artificial neural network models to forecast the electricity consumption for Hong Kong. They found that artificial neural network model forecasts are generally at least as good as those generated by the multiple linear regression model
Keywords
load forecasting; neural nets; power consumption; power system analysis computing; statistical analysis; Hong Kong; artificial neural network models; electricity consumption; load forecasting; multiple linear regression model;
fLanguage
English
Publisher
iet
Conference_Titel
Advances in Power System Control, Operation and Management, 1993. APSCOM-93., 2nd International Conference on
Conference_Location
IET
Print_ISBN
0-85296-569-9
Type
conf
Filename
292624
Link To Document