• DocumentCode
    47921
  • Title

    DG allocation for benefit maximization in distribution networks

  • Author

    Shaaban, Mostafa F. ; Atwa, Yasser M. ; El-Saadany, Ehab F.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
  • Volume
    28
  • Issue
    2
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    639
  • Lastpage
    649
  • Abstract
    This paper proposes a method to evaluate the worth of installing renewable distributed generation (DG) in distribution networks. Moreover, the work optimally allocates these DG units in the distribution network to maximize the worth of the connection to the local distribution company (LDC), as well as the customers connected to the system. The proposed methodology helps the LDC to better assess the benefits of the renewable DG units´ proposed connections and to identify the optimal buses on which to connect these DG units. The benefits considered in this paper are deferral of upgrade investments, reduction of the cost of energy losses, and reliability improvement, which is represented by the interruption cost reduction. The proposed methodology takes into consideration the uncertainty and variability associated with the output power of renewable DG as well as the load variability. The planning problem of determining the optimal location and sizes of DG units is defined as multi-objective mixed integer programming.
  • Keywords
    distributed power generation; distribution networks; integer programming; investment; optimisation; power distribution reliability; power generation reliability; LDC; distributed generation allocation; distribution networks; energy loss; interruption cost reduction; investments; local distribution company; maximization; multiobjective mixed integer programming; optimal bus; reliability; renewable distributed generation; Distributed power generation; Energy loss; Load modeling; Resource management; Substations; Distributed generation; Monte Carlo methods; distribution system; probability density function;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2012.2213309
  • Filename
    6313961