DocumentCode
775994
Title
Fuzzy neural network and fuzzy expert system for load forecasting
Author
Dash, P.K. ; Liew, A.C. ; Rahman, S.
Author_Institution
Dept. of Electr. Eng., Regional Eng. Coll., Rourkela, India
Volume
143
Issue
1
fYear
1996
fDate
1/1/1996 12:00:00 AM
Firstpage
106
Lastpage
114
Abstract
A hybrid neural network fuzzy expert system is developed to forecast short-term electric load accurately. The fuzzy membership values of the load and other weather variables are the inputs to the neural network, and the output comprises the membership values of the predicted load. An adaptive fuzzy correction scheme is used to forecast the final load by using a fuzzy rule base and fuzzy inference mechanism. Extensive studies have been performed for all seasons, and a few examples are presented in the paper, average, peak and hourly load forecasts
Keywords
expert systems; fuzzy neural nets; inference mechanisms; learning (artificial intelligence); load forecasting; power system analysis computing; adaptive fuzzy correction scheme; fuzzy inference mechanism; fuzzy membership values; fuzzy rule base; hourly load forecasts; load forecasting; neural network fuzzy expert system; peak load forecasts; short-term electric load; weather variables;
fLanguage
English
Journal_Title
Generation, Transmission and Distribution, IEE Proceedings-
Publisher
iet
ISSN
1350-2360
Type
jour
DOI
10.1049/ip-gtd:19960314
Filename
488069
Link To Document