• DocumentCode
    3258862
  • Title

    Short term generation scheduling of a Microgrid

  • Author

    Logenthiran, T. ; Srinivasan, Dipti

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2009
  • fDate
    23-26 Jan. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Microgrids are low voltage intelligent distribution networks comprising various distributed generators, storage devices and controllable loads which can be operated as interconnected or as islanded system. The optimal generation scheduling is one of the important functions for the Microgrid operation. This paper describes a three-step efficient method for the optimal generation scheduling of a Microgrid in island operation. The first step of the method is to set up an initial feasible solution for thermal unit commitment and the next step is to solve the thermal unit commitment problem. The final step is to optimize the renewable-thermal dispatch based on thermal unit commitment results. Solving the thermal unit commitment problem has more opportunity to minimize the operating cost. Therefore, few algorithms such as Lagrangian relaxation, genetic algorithm and a hybrid algorithm of Lagrangian relaxation and genetic algorithm have been used to find the least operating cost. Microgrid which is considered in the case study, consists of a PV system, a wind plant, 10 thermal units and a battery bank.
  • Keywords
    genetic algorithms; power generation scheduling; power grids; power system simulation; Lagrangian relaxation; genetic algorithm; low voltage intelligent distribution networks; microgrid; optimal generation scheduling; renewable-thermal dispatch; short term generation scheduling; thermal unit commitment; three-step efficient method; Costs; Distributed power generation; Genetic algorithms; Intelligent networks; Job shop scheduling; Lagrangian functions; Low voltage; Power generation; Power generation economics; Processor scheduling; Distributed Energy Resource; Genetic Algorithm; Lagrangian Relaxation; Microgrid; Optimal Generation Scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2009 - 2009 IEEE Region 10 Conference
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-4546-2
  • Electronic_ISBN
    978-1-4244-4547-9
  • Type

    conf

  • DOI
    10.1109/TENCON.2009.5396184
  • Filename
    5396184