• DocumentCode
    142496
  • Title

    Research of Multi-objective optimal dispatching for microgrid based on improved Genetic Algorithm

  • Author

    Daogang Peng ; Haiwei Qiu ; Hao Zhang ; Hui Li

  • Author_Institution
    Coll. of Autom. Eng., Shanghai Univ. of Electr. Power, Shanghai, China
  • fYear
    2014
  • fDate
    7-9 April 2014
  • Firstpage
    69
  • Lastpage
    73
  • Abstract
    According to the microgrid which contains a variety of distributed generations, a Multi-objective optimal dispatching model for microgrid is proposed. These objectives include the operation cost, sewage treatment cost and the comprehensive benefit cost. The multi-objective is converted into a nonlinear single objective optimization problem through the maximum fuzzy membership. Considering the influence of the distributed generation characteristics on the optimal dispatching of microgrid and according to a certain control strategy, the economic operation of the optimum scheme was obtained by Adaptive Simulated Annealing Genetic Algorithm (ASAGA).
  • Keywords
    distributed power generation; genetic algorithms; load dispatching; simulated annealing; adaptive simulated annealing genetic algorithm; comprehensive benefit cost; control strategy; distributed generation; improved genetic algorithm; maximum fuzzy membership; microgrid; multiobjective optimal dispatching; nonlinear single objective optimization problem; operation cost; sewage treatment cost; Annealing; Dispatching; Genetics; Iron; Microgrids; Turbines; ASAGA; Multi-objective; microgrid; optimal dispatching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control (ICNSC), 2014 IEEE 11th International Conference on
  • Conference_Location
    Miami, FL
  • Type

    conf

  • DOI
    10.1109/ICNSC.2014.6819602
  • Filename
    6819602