DocumentCode
2171153
Title
Application of adaptive network-based fuzzy inference system in short term load forecasting
Author
Saha, A.K. ; Chowdhury, S.P. ; Chowdhury, S.
Author_Institution
Jadavpur Univ., Kolkata
fYear
2007
fDate
20-22 Dec. 2007
Firstpage
168
Lastpage
174
Abstract
A number of computing models based on adaptive network- based fuzzy inference system (ANFIS) are proposed in this paper to forecast peak load demands of an electric power utility. The models are capable of forecasting the peak demands both week-days and weekend-days i.e. Sundays and holidays as well. At the same time the models possess adaptability to the changing data pattern which may occur in case the load demand pattern changes or the weather parameters change. The paper involves forecasting models with zero order and first order Sugeno model of ANFIS with various types of membership functions and optimization method combinations. The proposed models are validated using load demand data of a real power utility to forecast its peak demand.
Keywords
fuzzy set theory; inference mechanisms; load forecasting; adaptive network-based fuzzy inference system; electric power utility; first order Sugeno model; optimization method combinations; short term load forecasting; zero order forecasting models; Adaptive network; Sugeno models; adaptive neuro fuzzy inference system (ANFIS); artificial neural network (ANN); short-term load forecasting;
fLanguage
English
Publisher
iet
Conference_Titel
Information and Communication Technology in Electrical Sciences (ICTES 2007), 2007. ICTES. IET-UK International Conference on
Conference_Location
Tamil Nadu
ISSN
0537-9989
Type
conf
Filename
4735789
Link To Document