Deducing Energy Consumer Behavior from Smart Meter Data

Publikation: Forskning - peer reviewTidsskriftartikel



  • Emad Samuel Malki Ebeid
    Emad Samuel Malki EbeidSyddansk Universitet
  • Rune Heick
    Rune HeickDepartment of Engineering, Aarhus University
  • Rune Hylsberg Jacobsen
The ongoing upgrade of electricity meters to smart ones has opened a new market of intelligent services to analyze the recorded meter data. This paper introduces an open architecture and a unified framework for deducing user behavior from its smart main electricity meter data and presenting the results in a natural language. The framework allows a fast exploration and integration of a variety of machine learning algorithms combined with data recovery mechanisms for improving the recognition’s accuracy. Consequently, the framework generates natural language reports of the user’s behavior from the recognized home appliances. The framework uses open standard interfaces for exchanging data. The framework has been validated through comprehensive experiments that are related to an European Smart Grid project.
TidsskriftFuture Internet
Sider (fra-til)1-25
Antal sider25
StatusUdgivet - 6 jul. 2017

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