Robust Non-Intrusive Load Monitoring (NILM) with unknown loads

Shirantha Welikala, Chinthaka Dinesh, Roshan Indika Godaliyadda, Mervyn Parakrama B. Ekanayake, Janaka Ekanayake

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

A Non-Intrusive Load Monitoring (NILM) method, robust even in the presence of unlearned or unknown appliances (UUAs) is presented in this paper. In the absence of such UUAs, this NILM algorithm is capable of accurately identifying each of the turned-ON appliances as well as their energy levels. However, when there is an UUA or set of UUAs are turned-ON during a particular time window, proposed NILM method detects their presence. This enables the operator to detect presence of anomalies or unlearned appliances in a household. This quality increases the reliability of the NILM strategy and makes it more robust compared to existing NILM methods. The proposed Robust NILM strategy (RNILM) works accurately with a single active power measurement taken at a low sampling rate as low as one sample per second. Here first, a unique set of features for each appliance was extracted through decomposing their active power signal traces into uncorrelated subspace components (SCs) via a high-resolution implementation of the Karhunen-Loeve (KLE). Next, in the appliance identification stage, through considering power levels of the SCs, the number of possible appliance combinations were rapidly reduced. Finally, through a Maximum a Posteriori (MAP) estimation, the turned-ON appliance combination and/or the presence of UUA was determined. The proposed RNILM method was validated using real data from two public databases: Reference Energy Disaggregation Dataset (REDD) and Tracebase. The presented results demonstrate the capability of the proposed RNILM method to identify, the turned-ON appliance combinations, their energy level disaggregation as well as the presence of UUAs accurately in real households.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Information and Automation for Sustainability
Subtitle of host publicationInteroperable Sustainable Smart Systems for Next Generation, ICIAfS 2016
ISBN (Electronic)9781509061327
DOIs
StatePublished - 2 Jul 2016
Event8th IEEE International Conference on Information and Automation for Sustainability, ICIAfS 2016 - Galle, Sri Lanka
Duration: 16 Dec 201619 Dec 2016

Publication series

Name2016 IEEE International Conference on Information and Automation for Sustainability: Interoperable Sustainable Smart Systems for Next Generation, ICIAfS 2016

Conference

Conference8th IEEE International Conference on Information and Automation for Sustainability, ICIAfS 2016
Country/TerritorySri Lanka
CityGalle
Period16/12/1619/12/16

Keywords

  • Appliance Identification
  • Demand Side Management (DSM)
  • Non-Intrusive Load Monitoring (NILM)
  • Smart Grid
  • Smart Meters
  • Unknown Appliances
  • User side

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