• DocumentCode
    45328
  • Title

    State-of-the-Art Techniques and Challenges Ahead for Distributed Generation Planning and Optimization

  • Author

    Keane, Andrew ; Ochoa, Luis F. ; Borges, Carmen L. T. ; Ault, Graham W. ; Alarcon-Rodriguez, Arturo D. ; Currie, Robert A. F. ; Pilo, F. ; Dent, Chris ; Harrison, G.P.

  • Volume
    28
  • Issue
    2
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    1493
  • Lastpage
    1502
  • Abstract
    It is difficult to estimate how much distributed generation (DG) capacity will be connected to distribution systems in the coming years; however, it is certain that increasing penetration levels require robust tools that help assess the capabilities and requirements of the networks in order to produce the best planning and control strategies. The work of this Task Force is focused on the numerous strategies and methods that have been developed in recent years to address DG integration and planning. This paper contains a critical review of the work in this field. Although there have been numerous publications in this area, widespread implementation of the methods has not taken place. The barriers to implementation of the advanced techniques are outlined, highlighting why network operators have been slow to pick up on the research to date. Furthermore, key challenges ahead which remain to be tackled are also described, many of which have come into clear focus with the current drive towards smarter distribution networks.
  • Keywords
    distributed power generation; power distribution control; power distribution planning; power generation control; power generation planning; DG integration; Task Force; control strategy; distributed generation capacity estimation; distributed generation optimization; distributed generation planning; distribution networks; distribution systems; network operators; penetration levels; robust tool; Biological system modeling; Genetic algorithms; Linear programming; Optimization; Planning; Probabilistic logic; Reliability; AC optimal power flow; active network management; distributed generation; distribution networks; linear programming; multi-objective programming; wind power generation;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2012.2214406
  • Filename
    6307952