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Electricity Rate Planning for the Current Consumer Market Scenario Through Segmentation of Consumption Time Series

  • Alfredo VellidoEmail author
  • David L. García
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10423)

Abstract

The current European legislation requires households the installation of smart metering systems. These will eventually allow electric utilities to gather richly detailed data of consumption. In this scenario, the implementation of data mining procedures for actionable knowledge extraction could be the key to competitive advantage. These may take the form of market segmentation using clustering techniques for the identification of customer behaviour patterns of electricity consumption that could justify the definition of tailored tariffs. In this brief paper, we show that the combination of a standard clustering algorithm with a similarity measure specifically defined for non-i.i.d. data, namely Dynamic Time Warping, can reveal an actionable segmentation of a real consumer market, combining business criteria and quantitative evaluation.

Keywords

Time series Dynamic Time Warping x-Means k-Shape Electric utility Load curves Tariff personalization 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversitat Politècnica de CatalunyaBarcelonaSpain

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