• DocumentCode
    1388123
  • Title

    Probabilistic approach for optimal allocation of wind-based distributed generation in distribution systems

  • Author

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

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
  • Volume
    5
  • Issue
    1
  • fYear
    2011
  • fDate
    1/1/2011 12:00:00 AM
  • Firstpage
    79
  • Lastpage
    88
  • Abstract
    Recent development in small renewable/clean generation technologies such as wind turbines, photovoltaic, fuel cells, microturbines and so on has drawn distribution utilities´ attention to possible changes in the distribution system infrastructure and policy by deploying distributed generation (DG) in distribution systems. In this study, a methodology has been proposed for optimally allocating wind-based DG units in the distribution system so as to minimise annual energy loss. The methodology is based on generating a probabilistic generation´load model that combines all possible operating conditions of the wind-based DG units and load levels with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer non-linear programming (MINLP), with an objective function for the system´s annual energy losses minimise. The constraints include voltage limits at different buses (slack and load buses) of the system, feeder capacity, discrete size of the DG units, maximum investment on each bus, and maximum penetration limit of DG units. This proposed technique is applied to a typical rural distribution system and compared to the traditional planning technique (constant output power of DG units and constant peak load profile).
  • Keywords
    distributed power generation; integer programming; nonlinear programming; power generation planning; probability; wind power plants; MINLP; deterministic planning problem; distribution systems; mixed integer non-linear programming; optimal allocation; probabilistic generation-load model; wind turbines; wind-based distributed generation;
  • fLanguage
    English
  • Journal_Title
    Renewable Power Generation, IET
  • Publisher
    iet
  • ISSN
    1752-1416
  • Type

    jour

  • DOI
    10.1049/iet-rpg.2009.0011
  • Filename
    5644824