• DocumentCode
    3245875
  • Title

    A Simulator for Self-Adaptive Energy Demand Management

  • Author

    Guo, Ying ; Li, Rongxin ; Poulton, Geoff ; Zeman, Astrid

  • Author_Institution
    Inf. & Commun. Technol. Centre, CSIRO, North Ryde, NSW
  • fYear
    2008
  • fDate
    20-24 Oct. 2008
  • Firstpage
    64
  • Lastpage
    73
  • Abstract
    A Demand-Side Program Simulation Tool is designed to predict the response from different deployment strategies of distributed domestic energy management. To date, there are several case studies of demand management and control projects from around the world. To achieve results with sufficient generality, case studies need to be conducted over long periods, with a reasonable number of diverse households. Such case studies require large capital to set up hardware and software.To bypass these financial and temporal investments, we have designed a simulator for energy suppliers to use in order to learn the likely performance of large-scale deployments. Of main interest is the prediction of not only the level and firmness of demand response in critical peak pricing trials, but also the householdpsilas comfortable level and satisfaction level. As an example of the power of the simulator we have used it to develop and test a new self-adaptive methodology to intelligently control the energy demand. The methodology is adaptive to global factors, such as the market energy price, as well as local conditions, such as the satisfaction level of households. This paper outlines self-adaptive methodologies used within the simulator. Experimental results show energy consumption under different control strategies and the improvement of system behavior through adaptive design. With the self-adaptive demand management strategy, the total energy consumed by one million householdspsila controllable loads has reduced dramatically while the satisfaction level of households is well maintained. This is one of the very first simulators that take into account both technical and human behavior aspects.
  • Keywords
    adaptive control; control system synthesis; demand side management; intelligent control; power markets; self-adjusting systems; adaptive design; control strategies; critical peak pricing trials; demand-side program simulation tool; distributed domestic energy management; market energy price; self-adaptive energy demand management; Automatic testing; Energy management; Hardware; Intelligent control; Investments; Large-scale systems; Load management; Predictive models; Pricing; Project management; Energy Demand Management; Genetic algorithm; Self-Adaptive Systems; Simulator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Self-Adaptive and Self-Organizing Systems, 2008. SASO '08. Second IEEE International Conference on
  • Conference_Location
    Venezia
  • Print_ISBN
    978-0-7695-3404-6
  • Type

    conf

  • DOI
    10.1109/SASO.2008.71
  • Filename
    4663411