• DocumentCode
    623928
  • Title

    Sustainable energy consumption monitoring in residential settings

  • Author

    Nambi, Akshay Uttama S. N. ; Papaioannou, Thanasis G. ; Chakraborty, Debasis ; Aberer, Karl

  • Author_Institution
    Sch. of Comput. & Commun. Sci, Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland
  • fYear
    2013
  • fDate
    14-19 April 2013
  • Firstpage
    3177
  • Lastpage
    3182
  • Abstract
    The continuous growth of energy needs and the fact that unpredictable energy demand is mostly served by unsustainable (i.e. fossil-fuel) power generators have given rise to the development of Demand Response (DR) mechanisms for flattening energy demand. Building effective DR mechanisms and user awareness on power consumption can significantly benefit from fine-grained monitoring of user consumption at the appliance level. However, installing and maintaining such a monitoring infrastructure in residential settings can be quite expensive. In this paper, we study the problem of fine-grained appliance power-consumption monitoring based on one house-level meter and few plug-level meters. We explore the trade-off between monitoring accuracy and cost, and exhaustively find the minimum subset of plug-level meters that maximize accuracy. As exhaustive search is time- and resource-consuming, we define a heuristic approach that finds the optimal set of plug-level meters without utilizing any other sets of plug-level meters. Based on experiments with real data, we found that few plug-level meters - when appropriately placed - can very accurately disaggregate the total real power consumption of a residential setting and verified the effectiveness of our heuristic approach.
  • Keywords
    demand side management; heuristic programming; power consumption; sustainable development; demand response mechanisms; energy demand; energy needs; fine-grained appliance; heuristic approach; house-level meter; plug-level meters; residential settings; sustainable energy consumption monitoring; Accuracy; Energy consumption; Heuristic algorithms; Hidden Markov models; Home appliances; Monitoring; Power demand; Energy disaggregation; FHMM; Hidden Markov Models; NILM; plug-level meter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INFOCOM, 2013 Proceedings IEEE
  • Conference_Location
    Turin
  • ISSN
    0743-166X
  • Print_ISBN
    978-1-4673-5944-3
  • Type

    conf

  • DOI
    10.1109/INFCOM.2013.6567134
  • Filename
    6567134