• DocumentCode
    570074
  • Title

    Optimal planning of distribution system considering distributed generators

  • Author

    Huishi Liang ; Sige Liu ; Jian Su

  • Author_Institution
    CEPRI, Beijing, China
  • fYear
    2012
  • fDate
    29-30 May 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents a methodology for substation optimal planning considering DG for peak shaving. Utility can take effective demand-side management (DSM) to encourage customer-owned DG to participate in peak load shaving, and it can also construct utility DG to meet the peak load demand. In this paper, the impact of DG on peak load shaving is analyzed, and DG is taken as a complement to T&D system to meet load demand, which is considered in the substation planning. Substations sizing and location and new-built utility DG capacity is optimized using Particle Swarm Optimization (PSO), in which supply area of each substation is obtained by Voronoi diagram method. Case study shows that planning result considering DG for peak shaving can defer T&D system expansion so that considerable investment can be saved. Especially for those areas with high cost of T&D system construction, constructing DG to meet peak load demand would be a more economic way.
  • Keywords
    computational geometry; demand side management; distributed power generation; electric generators; investment; particle swarm optimisation; power distribution planning; power generation planning; substations; DSM; PSO; T&D system construction; Voronoi diagram method; customer-owned DG; demand-side management; distributed generators; distribution system; new-built utility DG capacity; particle swarm optimization; peak load demand; peak load shaving; substation optimal planning; substations location; substations sizing; utility DG;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Integration of Renewables into the Distribution Grid, CIRED 2012 Workshop
  • Conference_Location
    Lisbon
  • Electronic_ISBN
    978-1--84919-628-4
  • Type

    conf

  • DOI
    10.1049/cp.2012.0792
  • Filename
    6302424