• DocumentCode
    3249039
  • Title

    Resolution enhancement of input parameters in a demand side management model

  • Author

    Imbert, P. ; Kariniotakis, G. ; Blanc, P. ; Neirac, F.P.

  • Author_Institution
    Geo Simulation for Energy, Eur. Inst. for Energy Res. - EIFER, Karlsruhe, Germany
  • fYear
    2010
  • fDate
    14-17 June 2010
  • Firstpage
    734
  • Lastpage
    740
  • Abstract
    Demand side management (DSM) and distributed generation (DG) introduce into power systems new dynamics and behaviors which must be taken into account in the planning and operation of the system. This paper presents a model that aims to simulate the spread out effects of DSM actions in a region. This model is suitable designed to represent the territorial or local specificities of each studied area where the DSM actions apply. The model involves a large number of input data. The main question is what should be the optimal level of detail this data has to be collected in terms of spatial resolution so that meaningful results are obtained. The paper presents a method to define the input data which are critical to collect with a higher spatial resolution. Results for a case study in France are presented. Demand-side management, territorial energy planning, input parameter selection, sensitivity analysis, ranking based correlation method, Monte Carlo simulation.
  • Keywords
    Monte Carlo methods; demand side management; distributed power generation; power distribution planning; DSM; France; Monte Carlo simulation; demand side management model; distributed generation; power system operation; power system planning; Correlation; Distributed control; Energy management; Power system dynamics; Power system management; Power system modeling; Power system planning; Power system simulation; Sensitivity analysis; Spatial resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5720-5
  • Type

    conf

  • DOI
    10.1109/PMAPS.2010.5528403
  • Filename
    5528403