• DocumentCode
    2291191
  • Title

    An optimal scheduling problem in distribution networks considering V2G

  • Author

    Soares, João ; Sousa, Tiago ; Morais, Hugo ; Vale, Zita ; Faria, Pedro

  • Author_Institution
    GECAD - Knowledge Eng. & Decision Support Res. Center, ISEP / IPP - Inst. of Eng. - Polytech. of Porto, Porto, Portugal
  • fYear
    2011
  • fDate
    11-15 April 2011
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper addresses the problem of energy resource scheduling. An aggregator will manage all distributed resources connected to its distribution network, including distributed generation based on renewable energy resources, demand response, storage systems, and electrical gridable vehicles. The use of gridable vehicles will have a significant impact on power systems management, especially in distribution networks. Therefore, the inclusion of vehicles in the optimal scheduling problem will be very important in future network management. The proposed particle swarm optimization approach is compared with a reference methodology based on mixed integer non-linear programming, implemented in GAMS, to evaluate the effectiveness of the proposed methodology. The paper includes a case study that consider a 32 bus distribution network with 66 distributed generators, 32 loads and 50 electric vehicles.
  • Keywords
    distributed power generation; distribution networks; electric vehicles; integer programming; linear programming; particle swarm optimisation; power grids; power system management; scheduling; 32-bus distribution network; GAMS; V2G; aggregator; demand response; distributed generation; distributed resources; distribution networks; electrical gridable vehicles; energy resource scheduling; mixed integer nonlinear programming; optimal scheduling problem; particle swarm optimization approach; power system management; reference methodology; renewable energy resources; storage systems; Batteries; Discharges; Generators; Load flow; Optimal scheduling; Vehicles; Distributed Generation; Energy Resources Management; Optimal Scheduling; Particle Swarm Optimization; Plug-in Hybrid Vehicle; Vehicle to Grid;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence Applications In Smart Grid (CIASG), 2011 IEEE Symposium on
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-4244-9893-2
  • Type

    conf

  • DOI
    10.1109/CIASG.2011.5953342
  • Filename
    5953342