• DocumentCode
    3100936
  • Title

    Optimal Distributed Generation Parameters for Reducing Losses with Economic Consideration

  • Author

    Le, An D T ; Kashem, M.A. ; Negnevitsky, M. ; Ledwich, G.

  • Author_Institution
    Sch. of Eng., Tasmania Univ., Hobart, TAS
  • fYear
    2007
  • fDate
    24-28 June 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Distributed generation (DG) represents a reliable option for solving current major problems of distribution companies, such as load growth, overloaded lines, quality of supply and reliability. Moreover, it has been proven that the additional benefits brought by DG could be substantial if properly used. This paper addresses the issue of optimizing DG planning in term of DG size and location to reduce the amount of line losses in the distribution networks. The optimization methodology, which is based on the sequential quadratic programming (SQP) algorithm, firstly assesses the compatibility of different generation schemes upon the level of power loss reduction and DG cost. The solutions obtained are finally validated with the constraints of maximum number and size of DG, as well as voltage violation and DG penetration. The proposed method is tested on IEEE 33 bus system, proving that the technique is effective and applicable.
  • Keywords
    distributed power generation; power generation planning; quadratic programming; DG planning; IEEE 33 bus system; SQP algorithm; optimal distributed generation parameters; optimization methodology; power loss reduction; sequential quadratic programming algorithm; Australia; Cost function; Distributed control; Environmental economics; Investments; Power engineering and energy; Power generation; Power generation economics; Voltage; Wind turbines; Distributed Generation; Distribution System; Loss Reduction; Optimal Location; Optimal Size; Voltage Limit;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2007. IEEE
  • Conference_Location
    Tampa, FL
  • ISSN
    1932-5517
  • Print_ISBN
    1-4244-1296-X
  • Electronic_ISBN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PES.2007.386058
  • Filename
    4275824