Using pattern recognition to identify habitual behavior in residential electricity consumption

Authors

Abstract

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.

Keywords

Pattern recognition, electricity consumption, energy profiling, behaviour modeling

Subject

Pattern recognition

Related Project

iTEAM

Journal

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

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