Behavior pattern recognition in electric power consumption series using data mining tools

Authors:
Alynne C. S. de Queiroz;José Alfredo F. Costa
Affiliations:
Department of Electrical Engineering, Universidade Federal do Rio Grande do Norte, Natal, RN, Brasil;Department of Electrical Engineering, Universidade Federal do Rio Grande do Norte, Natal, RN, Brasil
Venue:
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Year:
2012

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Abstract

The behavioral patterns identification is very important for time series analysis of energy consumption to assist planning activities and decision making, as well to seek improvements in service quality and financial benefits. In this paper we used a methodology based on data mining tools, including cluster analysis and time series representation. The Time Series Knowledge Mining [1] was adapted to the treatment of consumption electricity series. Results are shown in a case study with hourly consumption measurements of eight power substations.