Using pattern recognition to identify habitual behavior in residential electricity consumption



Recognizing habitualbehavior and providing feedback in context are key to empower individuals to take control over residential electricity consumption. Yet, it is a challenge to change habitualbehavior, embedded in everyday routines. This paper intends to discover whether habitualbehavior can be identified by patternrecognition techniques. The data source is an experiment similar to a utility led advanced metering infrastructure implementation.

The analysis discovers: (1) persistent daily routines and (2) patterns of consumption or baselines typical of specific weather and daily conditions. Approximately 80% of household electricity use can be explained within these two patterns, with several applicable “profiles” for this population, including: unoccupied baseline, hot working days, temperate working days, cold working days, and cold weekend days.

The proposed methodology demonstrates that it is possible to use patternrecognition methodologies to recognize habitual electricity consumption behavior given the intrinsic characteristics of the family. This approach could be useful to improve small scale forecast, and as a mechanism to enable the provision of tailor-made information to the families.


Pattern recognition, electricity consumption, energy profiling, behaviour modeling


Pattern recognition

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Energy and Buildings, Vol. 49, pp. 479-487, March 2012

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Year 2012 : 3 citations

 Christian Beckel, Leyna Sadamori, Silvia Santini. "Towards Automatic Classification of Private Households
Using Electricity Consumption Data". Buildsys’12, November 6, 2012, Toronto, ON, Canada.

 Snezana Tilovska, Aristotel Tentov, Power consumption analyzes with mathematical models into the overall electrical network, International Journal of Electrical Power & Energy Systems, Volume 44, Issue 1, January 2013, Pages 798-809, ISSN 0142-0615, 10.1016/j.ijepes.2012.08.042.

 Henrique Pombeiro, André Pina, Carlos Silva. " Analyzing Residential Electricity Consumption Patterns
Based on Consumer’s Segmentation". Proceedings of IT4ENERGY 2012. International Workshop on Information Technology for Energy Applications, September 6-7th, Lisbon, Portugal