Non-intrusive load disaggregation using graph signal processing

Research output: Contribution to journalArticle

72 Citations (Scopus)
524 Downloads (Pure)


With the large-scale roll-out of smart metering worldwide, there is a growing need to account for the individual contribution of appliances to the load demand. In this paper, we design a Graph signal processing (GSP)-based approach for non-intrusive appliance load monitoring (NILM), i.e., disaggregation of total energy consumption down to individual appliances used. Leveraging piecewise smoothness of the power load signal, two GSP-based NILM approaches are proposed. The first approach, based on total graph variation minimization, searches for a smooth graph signal under known label constraints. The second approach uses the total graph variation minimizer as a starting point for further refinement via simulated annealing. The proposed GSP-based NILM approach aims to address the large training overhead and associated complexity of conventional graph-based methods through a novel event-based graph approach. Simulation results using two datasets of real house measurements demonstrate the competitive performance of the GSP-based approaches with respect to traditionally used Hidden Markov Model-based and Decision Tree-based approaches.
Original languageEnglish
Pages (from-to)1739-1747
Number of pages9
JournalIEEE Transactions on Smart Grid
Issue number3
Early online date9 Aug 2016
Publication statusPublished - 31 May 2018


  • energy disaggregation
  • graph signal processing
  • energy feedback
  • smart metering
  • appliances
  • load demand
  • energy consumption

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    Research Output

    • 72 Citations
    • 1 Article
    Open Access
  • 63 Citations (Scopus)
    225 Downloads (Pure)


    • 3 Invited talk

    Graph Signal Processing Classification with Applications

    Vladimir Stankovic (Speaker)

    26 Nov 2018

    Activity: Talk or presentation typesInvited talk

    Graph Signal Processing with Applications to Smart Homes

    Vladimir Stankovic (Speaker)

    Jun 2018

    Activity: Talk or presentation typesInvited talk

    Unlocking the potential of smart meter data via energy analytics

    Lina Stankovic (Invited speaker) & Vladimir Stankovic (Invited speaker)

    3 Jun 2018

    Activity: Talk or presentation typesInvited talk

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