DocumentCode :
3561678
Title :
Electricity consumer classification using artificial intelligence
Author :
Lo, K.L. ; Zakaria, Zuhaina
Author_Institution :
Strathclyde Univ., Glasgow, UK
Volume :
1
fYear :
2004
Firstpage :
443
Abstract :
In a deregulated energy environment, consumers can purchase electricity from any provider regardless of size and location. As a result, there is a growing interest in understanding the nature of variations in consumer consumption. This information can be used to facilitate an electricity supplier in their marketing strategy. Thus, it is essential to have typical load profiles of different groups of consumers. Many techniques for consumer classification have been reported in the past. The techniques include applications of statistics, unsupervised clustering technique and methods based on frequency domain approach. This paper examines the capability of artificial intelligent techniques to classify electricity consumers by their pattern of consumption. Fuzzy clustering and an artificial neural network (ANN) have been employed in this study. The results obtained demonstrate the ability of the proposed method in classifying consumers by their energy consumption.
Keywords :
consumer behaviour; fuzzy set theory; load forecasting; marketing data processing; neural nets; pattern clustering; power consumption; power system analysis computing; ANN; artificial intelligence; artificial neural network; consumption pattern; deregulated energy environment; electricity consumer classification; fuzzy clustering; load profiles; marketing strategy; Artificial intelligence; Artificial neural networks; Electricity supply industry; Electricity supply industry deregulation; Energy consumption; Frequency domain analysis; Fuzzy neural networks; Power generation; Power industry; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Universities Power Engineering Conference, 2004. UPEC 2004. 39th International
Print_ISBN :
1-86043-365-0
Type :
conf
Filename :
1492043
Link To Document :
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