Master data

Title: Energy Dissagregation on a Raspberry Pi with YoMoPie-Extension
Subtitle:
Abstract:

Non-intrusive load monitoring (NILM) is emerging as a crucial technique for providing detailed and effective energy feedback, thereby facilitating the development of low-cost and low-energy management systems in the residential sector. However, achieving acceptable disaggregation results requires sampling frequencies that exceed the 15-minute intervals of commercial smart meters. State-of-the-art approaches require a measurement frequency of at least 1Hz. While technically possible, measurement devices that can provide measurements at such intervals increase the cost of the overall system. In addition, consumers may raise privacy concerns regarding these systems. To address these issues, we propose a low-cost single-device smart meter that provides direct feedback based on a local processing of the user's data. The proposed system leverages the Raspberry Pi and the YoMoPie Monitor to provide an efficient, compact, and accurate system. The system's performance was tested in a laboratory setting under two different scenarios, and promising results were obtained considering the disaggregation performance and computational complexity.

Keywords: NILM, Smart Metering, Energy Awareness
Publication type: Article in Proceedings (Authorship)
Publication date: 18.12.2023 (Online)
Published by: 2023 2nd International Conference on Power Systems and Electrical Technology (PSET)
2023 2nd International Conference on Power Systems and Electrical Technology (PSET) (2023)
to publication
 ( IEEE; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: -

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Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Vernetzte und Eingebettete Systeme
Universitätsstraße 65-67
9020 Klagenfurt am Wörthersee
Austria
  -993640
   kornelia.lienbacher@aau.at
https://nes.aau.at/
To organisation
Universitätsstraße 65-67
AT - 9020  Klagenfurt am Wörthersee

Categorisation

Subject areas
  • 102009 - Computer simulation
  • 202010 - Electric power engineering
  • 202022 - Information technology
  • 202041 - Computer engineering
Research Cluster
  • Energy management and technology
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: II)
Classification raster of the assigned organisational units:
working groups
  • Smart Grids Group

Cooperations

No partner organisations selected

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