• DocumentCode
    2117334
  • Title

    Transmission Congestion Management Using Distributed Generation Considering Load Uncertainty

  • Author

    Afkousi-Paqaleh, M. ; Noory, A.R. ; Abbaspour, A. T F ; Rashidinejad, M.

  • Author_Institution
    Dep. of Electr. Eng., Sharif Univ. Of Technol., Tehran, Iran
  • fYear
    2010
  • fDate
    28-31 March 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This Paper presents a model for optimal locating and sizing of Distributed Generation (DG) for congestion management in deregulated electricity market. For reducing the solution space a priority list of candidate buses is formed and then optimal placement and sizing of DG in potential buses is discussed. In order to incorporate stochastic nature of power system in this study, Monte-Carlo method is used to simulate the effect of uncertainty of loads and system on the optimal location and size of the DGs in the network. The proposed method is applied to IEEE Reliability Test System (RTS). The impacts of load uncertainty on optimum DG size and location are studied.
  • Keywords
    IEEE standards; Monte Carlo methods; distributed power generation; power distribution economics; power distribution reliability; power markets; power system management; power transmission reliability; IEEE reliability test system; Monte Carlo method; deregulated electricity market; distributed generation; load uncertainty; transmission congestion management; Distributed control; Electricity supply industry; Electricity supply industry deregulation; Energy management; Power system management; Power system modeling; Power system reliability; Power system simulation; Stochastic systems; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-4812-8
  • Electronic_ISBN
    978-1-4244-4813-5
  • Type

    conf

  • DOI
    10.1109/APPEEC.2010.5449393
  • Filename
    5449393