• DocumentCode
    149687
  • Title

    Data-driven method for providing feedback to households on electricity consumption

  • Author

    Mononen, Matti ; Saarenpaa, Jukka ; Johansson, Mikael ; Niska, Harri

  • Author_Institution
    Dept. of Environ. Sci., Univ. of Eastern Finland, Kuopio, Finland
  • fYear
    2014
  • fDate
    21-24 April 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The building sector is a major energy consumer and CO2 emitter, being responsible for approximately 40% of the total consumption in the EU. Active demand side participation of electricity customers is seen as crucial in the management and reduction of the building sector´s CO2 emissions. However, today´s electricity markets are often lacking strong incentives for active demand side participation. Understandable customer specific comparison information and easy-to-use energy displays can be used to influence customer behaviour and encourage customer participation. This paper presents a data-driven method for producing household level comparison information, based on hourly interval smart meter data and additional household information. Firstly, the customers are segmented by the heating system and the type of housing, followed by weighted clustering that is used to refine the comparison group. In the weighted clustering, normalized load profiles together with properties of the dwelling and the residents are considered, and weights are assigned to the properties according to how much they contribute to the electricity consumption. In this paper, the initial experimental results are presented and discussed, and future development ideas are laid out. The method is under development and testing as a part of the Finnish SGEM-project.
  • Keywords
    carbon compounds; consumer behaviour; demand side management; feedback; incentive schemes; power consumption; smart meters; smart power grids; CO2; Finnish SGEM project; active demand side participation; building sector; customer behaviour; customer participation; customer specific comparison information; data driven method; electricity consumption; electricity markets; energy displays; heating system; household level comparison information; smart meter data; weighted clustering; Electricity; Heat pumps; Resistance heating; Temperature distribution; Vectors; customer behaviour; demand side management; energy displays; energy efficiency; load profiling; smart grid; smart metering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2014 IEEE Ninth International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4799-2842-2
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2014.6827661
  • Filename
    6827661