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Non-intrusive Residential Electrical Consumption Traces

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Ambient Intelligence - Software and Applications

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 92))

Abstract

An active trend of research consists of understanding how electricity is used, namely for energy efficiency enforcement and in-home activity tracking. The obvious and cheapest solution is to use an inconspicuous monitoring system. Through the use of non-intrusive load monitoring systems, the signal from the aggregate consumption is captured, electrical significant features are extracted and classified and the appliances that were consuming are identified. In order to obtain a precise identification of the device, the main requirements are an electrical signature for each device and a proper classification method. The information thus obtained identifies appliance’s usage and specific consumptions. This paper describes an on-going research aiming at the development and simplification of techniques and algorithms for non-intrusive load monitoring systems (NILM). The first steps in the implementation of a NILM system were already addressed, namely we are performing an extensive study on the characterization of the appliance’s electrical signature. The proposed parameters for defining an efficient electrical signature are the step-changes in the active and reactive power and the power factor.

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Figueiredo, M., de Almeida, A., Ribeiro, B. (2011). Non-intrusive Residential Electrical Consumption Traces. In: Novais, P., Preuveneers, D., Corchado, J.M. (eds) Ambient Intelligence - Software and Applications. Advances in Intelligent and Soft Computing, vol 92. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19937-0_7

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  • DOI: https://doi.org/10.1007/978-3-642-19937-0_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19936-3

  • Online ISBN: 978-3-642-19937-0

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