• DocumentCode
    1944445
  • Title

    Activity based energy demand modeling for residential buildings

  • Author

    Subbiah, R. ; Lum, K. ; Marathe, A. ; Marathe, M.

  • Author_Institution
    Network Dynamics & Simulation Sci. Lab., Viginia Tech, Blacksburg, VA, USA
  • fYear
    2013
  • fDate
    24-27 Feb. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Statistics reveal that almost one-fourth of the overall power consumption in the US is by residential buildings; this number is only increasing. In order to manage the growing demand for energy, there is a need for energy system optimization, which would require a realistic, high resolution energy-demand model. To achieve this goal, we propose a modeling framework aimed at generating household energy demand profiles based on individual-level energy consuming activities. The model associates appliance usage for each household activity and calculates energy consumption based on the appliance energy rating and duration of activity. We use this information to generate a household level energy demand profile for roughly 63,000 households and discuss the possible uses of generating residential energy demand patterns. This paper provides a novel way to resolve correlational and consistency problems in the generation of individual-level and household-level “shared” activities which occur due to household members´ interactions.
  • Keywords
    building management systems; demand side management; domestic appliances; US; activity based energy demand modeling; appliance energy rating; energy system optimization; high resolution energy-demand model; household energy demand profiles; household members interactions; household-level shared activities; individual-level energy consuming activities; individual-level shared activities; power consumption; residential buildings; Biological system modeling; Data models; Energy consumption; Home appliances; Probability; Space heating; Water heating; Correlation Demand side management; Logistic regression; Poisson regression; Smart grid;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies (ISGT), 2013 IEEE PES
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4673-4894-2
  • Electronic_ISBN
    978-1-4673-4895-9
  • Type

    conf

  • DOI
    10.1109/ISGT.2013.6497822
  • Filename
    6497822