• DocumentCode
    1993118
  • Title

    The development of demand elasticity model for demand response in the retail market environment

  • Author

    Babar, M. ; Nguyen, P.H. ; Cuk, V. ; Kamphuis, I.G.

  • Author_Institution
    Eindhoven University of Technology, Department of Electrical Engineering, Electrical Energy Systems, 5600 MB, the Netherlands
  • fYear
    2015
  • fDate
    June 29 2015-July 2 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In the context of liberalized energy market, increase in distributed generation, storage and demand response has expanded the price elasticity of demand, thus causing the addition of uncertainty to the supply-demand chain of power system. In order to cope with the challenges of demand uncertainty under the unbundled electricity market, the concept of Market-based Control Mechanism (MCM) in retail market environment has been emerging. This paper presents the concept considering demand elasticity as an opportunity in retail market environment for inventing a new bid mechanism. This work formulates demand elasticity model as a Markov decision problem and implements pursuit algorithm as a machine learning technique to evaluate the price elasticity of demand by predicting the price. The performance of the algorithm is compared with the numerical calculation of price elasticity of demand for the given simulation settings.
  • Keywords
    Elasticity; Electricity supply industry; Machine learning algorithms; Markov processes; Numerical models; Pursuit algorithms; Smart homes; Demand Elasticity; Demand Response; Electricity Market; Pursuit Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech, 2015 IEEE Eindhoven
  • Conference_Location
    Eindhoven, Netherlands
  • Type

    conf

  • DOI
    10.1109/PTC.2015.7232789
  • Filename
    7232789