• DocumentCode
    2340714
  • Title

    The application of combinatorial optimization by Genetic Algorithm and Neural Network

  • Author

    Zhou, Shiqiong ; Kang, Longyun ; Guo, Guifang ; Zhang, Yanning ; Cao, Jianbo ; Cao, Binggang

  • Author_Institution
    Sch. of Mech. Eng., Xi´´an Jiaotong Univ., Xi´´an
  • fYear
    2008
  • fDate
    3-5 June 2008
  • Firstpage
    227
  • Lastpage
    231
  • Abstract
    A optimization model of sizing the storage section in a renewable power generation system was set up, and two methods were used to solve the model: genetic algorithm or combinatorial optimization by genetic algorithm and neural network. The system includes the photovoltaic arrays, the lead-acid battery and a flywheel. The optimal sizing can be considered as a constrained optimization problem: minimization the total capacity of energy storage system, subject to the main constraint of the loss of power supply probability (LPSP). Both of the two optimal algorithm got good results. We can see that, combinatorial optimization by genetic algorithm and neural network can lessen the calculation time, with the results change little.
  • Keywords
    combinatorial mathematics; electric power generation; energy storage; flywheels; genetic algorithms; lead acid batteries; neural nets; renewable energy sources; solar cell arrays; combinatorial optimization; energy storage system capacity; flywheel; genetic algorithm; lead-acid battery; neural network; photovoltaic arrays; power supply probability loss; renewable power generation methods system; Batteries; Capacity planning; Constraint optimization; Flywheels; Genetic algorithms; Neural networks; Optimization methods; Photovoltaic systems; Power system modeling; Solar power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-1717-9
  • Electronic_ISBN
    978-1-4244-1718-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2008.4582512
  • Filename
    4582512