• DocumentCode
    2052051
  • Title

    Optimal allocation of renewable DG for reliability improvement and losses reduction

  • Author

    Shaaban, M.F. ; El-Saadany, E.F.

  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper presents a methodology to evaluate the cost of energy losses and the cost of interruption in distribution networks with renewable distributed generation (DG) connections. Moreover, it presents a renewable DG allocation planning algorithm to determine the optimum locations and sizes of DG units in distribution network for reliability improvement and energy losses reduction. The proposed approach takes into consideration customers´ sectors, load variation, stochastic nature of renewable DG, and variable hourly cost of energy. The allocation planning problem is defined as mixed integer nonlinear programming problem, where genetic algorithm (GA) is utilized. Using the proposed approach, the distribution companies can determine optimum sizes and locations of DG units in their systems; besides, the expected reduction in the energy losses and outages costs.
  • Keywords
    distributed power generation; genetic algorithms; integer programming; nonlinear programming; power distribution planning; power distribution reliability; power generation planning; power generation reliability; DG units; distribution networks; energy losses reduction; genetic algorithm; load variation; mixed integer nonlinear programming problem; reliability improvement; renewable DG power allocation planning algorithm; renewable distributed generation; Biological system modeling; Energy loss; Interrupters; Load modeling; Reliability; Resource management; Wind speed; Monte-Carlo simulation; cost damage function; distributed generation; distribution system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6345054
  • Filename
    6345054