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Electric Load Profile Non-intrusive Analysis to Guide Energy Efficient Behavior for Residential Clients

Abstract : In the context of the energy transition with ambitious goals about reducing electric energy use, residential energy consumption is a large part of total energy use and has a high potential for energy savings. Recently, deployment of smart meters have enabled residential load profile data to be more easily accessible. Therefore, services are emerging to better inform residential customers about their energy use. These services have been highly effective to reduce energy use when feedback is given about appliance specific energy use. This paper presents a simple and effective algorithm to use non-intrusive load monitoring analysis combined with a questionnaire to provide quick appliance specific energy use feedback to residential customers. The algorithm is only based on the historical energy use, does not require significant computational capacity, respects the confidentiality of clients with no data sharing involved and can be deployed offline if the client does not have access to internet. This makes this type of algorithm widely applicable and informative for residential customers.
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Contributor : Etta Grover-Silva <>
Submitted on : Monday, May 25, 2020 - 2:10:17 PM
Last modification on : Wednesday, April 28, 2021 - 6:46:59 PM

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Etta Grover-Silva, Elena Magliaro, Johanna Le Conte. Electric Load Profile Non-intrusive Analysis to Guide Energy Efficient Behavior for Residential Clients. 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Sep 2019, Bucharest, Romania. pp.1-5, ⟨10.1109/ISGTEurope.2019.8905431⟩. ⟨hal-02618225⟩

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