• DocumentCode
    3253326
  • Title

    NaS technology allocation for improving reliability of DG-enhanced distribution networks

  • Author

    Naderi, Ehsan ; Kiaei, Iman ; Haghifam, M.-R.

  • Author_Institution
    Fac. of Electr. & Comput. Eng., Tarbiat Modares Univ., Tehran, Iran
  • fYear
    2010
  • fDate
    14-17 June 2010
  • Firstpage
    148
  • Lastpage
    153
  • Abstract
    Reliability calculation is the most important concern in designing and planning of distribution systems, which is considered, in terms of the economical concerns, with minimal interruption of customers. Storage devices are usually used for storing the electric energy while the electric price is low, and deliver their reserved energy when it has financial profit. Also, it could be effective for decreasing the average duration and frequency of outages in load points. In this paper, a method for evaluation of average annual energy not supplied (ENS) for a radial distribution system with DG units and storage devices is presented. Besides, the genetic algorithm (GA) is used to find the optimal capacity and the best location for storage device in order to minimize ENS and installation cost simultaneously. The effectiveness of this method is examined on a real distribution network.
  • Keywords
    distributed power generation; genetic algorithms; power distribution economics; power distribution planning; power distribution reliability; DG-enhanced distribution networks; NaS technology allocation; average annual energy not supplied; distribution system design; distribution system planning; genetic algorithm; radial distribution system; reliability calculation; Cables; Computer network reliability; Costs; Distributed computing; Energy storage; Frequency; Genetic algorithms; Power generation economics; Power system economics; Power system reliability; Distributed Generation; Distribution Systems; Energy Not Supplied; Genetic Algorithm; Reliability Assessment; Restoration Time; Storage Devices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5720-5
  • Type

    conf

  • DOI
    10.1109/PMAPS.2010.5528990
  • Filename
    5528990