Deducing Energy Consumer Behavior from Smart Meter Data

Emad Samuel Malki Ebeid, Rune Heick, Rune Hylsberg Jacobsen

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Resumé

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.
OriginalsprogEngelsk
Artikelnummer29
TidsskriftFuture Internet
Vol/bind9
Udgave nummer3
ISSN1999-5903
DOI
StatusUdgivet - 2017

Fingeraftryk

Smart meters
Consumer behavior
Electricity
Domestic appliances
Learning algorithms
Learning systems
Recovery
Experiments

Citer dette

Ebeid, Emad Samuel Malki ; Heick, Rune ; Jacobsen, Rune Hylsberg. / Deducing Energy Consumer Behavior from Smart Meter Data. I: Future Internet. 2017 ; Bind 9, Nr. 3.
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Deducing Energy Consumer Behavior from Smart Meter Data. / Ebeid, Emad Samuel Malki; Heick, Rune; Jacobsen, Rune Hylsberg.

I: Future Internet, Bind 9, Nr. 3, 29, 2017.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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