Electricity load prediction using hierarchical fuzzy logic systems

Authors:
Masoud Mohammadian;Ric Jentzsch
Affiliations:
School of Information Sciences and Engineering, University of Canberra, Canberra, Australia;School of Information Sciences and Engineering, University of Canberra, Canberra, Australia
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2005

Citing 2
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Abstract

Electricity load forecasting has been the subject of research over the past several years by researchers and practitioners in academia and industry. This is due to its very important role for effective and economic operation of power stations. In this paper an intelligent hierarchical fuzzy logic system using genetic algorithms for the prediction and modelling of electricity consumption is developed. A hierarchical fuzzy logic system is developed to model and predict daily electricity load fluctuations. The system is further trained to model and predict electricity consumption for daily peak.