A comparative study of low sampling non intrusive load dis-aggregation | Zendy

Kaustav Basu | Zendy; Ahmad Hably | Zendy; Vincent Debusschere | Zendy; Seddik Bacha | Zendy; Geert Jan Driven | Zendy; Andres Ovalle | Zendy

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A comparative study of low sampling non intrusive load dis-aggregation

Author(s) -

Kaustav Basu,

Ahmad Hably,

Vincent Debusschere,

Seddik Bacha,

Geert Jan Driven,

Andres Ovalle

Publication year - 2016

Publication title -

iecon 2016 - 42nd annual conference of the ieee industrial electronics society

Language(s) - English

Resource type - Conference proceedings

ISBN - 978-1-5090-3474-1

DOI - 10.1109/iecon.2016.7793294

Subject(s) - communication, networking and broadcast technologies , components, circuits, devices and systems , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Non-intrusive load monitoring (NILM) deals with the identification and subsequent energy estimation of the individual appliances from the smart meter data. The state of the art applications typically runs once per day and reports the detected appliances. In this work, data driven models are implemented for two different sampling rates (10 seconds and 15 minutes). The models are trained for 20 houses in the Netherlands and tested for a period of 4-weeks. The results indicate that the disaggregation methods is applicable for both sampling cases but with different use-case.

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