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Communication Dans Un Congrès Année : 2021

Artificial aggregation of domestic appliance currents for NILM evaluation

Résumé

Dedicated Nonintrusive Load Monitoring (NILM) datasets are needed to test any new NILM process. This, however, introduces limitation, since datasets can be lacking in terms of load diversity and multi-load signals. The first problem can be solved by acquiring data from other datasets. The second one requires real measurements of said signals. With the intention of solving the second limitation, we present a new method to create artificial multi-load signals using real individual load signals. The method is able to place the signals at any position relative to one another. Its performance is tested by comparing the resulting artificial signal with the real signal. The results shows strong similarities between the real and artificial signals. An application in ON-OFF transition counts is introduced showing the usefulness of the proposed artificial aggregation approach for any deep evaluation of event detectors in NILM.
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Dates et versions

hal-03513298 , version 1 (05-01-2022)

Identifiants

  • HAL Id : hal-03513298 , version 1

Citer

Mohamad Nour, Yves Raingeaud, Philippe Ravier, Guy Lamarque, Jean-Charles Le Bunetel. Artificial aggregation of domestic appliance currents for NILM evaluation. EEEIC INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING, Sep 2021, BARI, Italy. ⟨hal-03513298⟩
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