• DocumentCode
    229747
  • Title

    An improved particle swarm optimization MPPT algorithm based on voltage window restrictions

  • Author

    Zhu Qing ; Zhang Xing ; Liu Chun ; Li Shan Shou ; Chen Xiaojing

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Hefei Univ. of Technol., Hefei, China
  • fYear
    2014
  • fDate
    22-25 Oct. 2014
  • Firstpage
    795
  • Lastpage
    799
  • Abstract
    There are several maximum power points tracking algorithm using for the multi-peak MPPT algorithm optimization of photovoltaic cell array, such as the emergence of a global particle swarm algorithm. But particle swarm MPPT algorithm has less stable, larger voltage and power fluctuations, lower energy efficiency. To solve this problem, this paper propose a novel particle swarm optimization algorithm based on voltage window limits, by limiting the voltage range of particle swarm algorithm, a substantial increase the convergence speed, decrease the power fluctuations and reduce energy consumption. Simulation and experimental results show that the optimized algorithm has better performance in the global maximum power point tracking. This paper also create the conditions for the application of global maximum power point tracking algorithm.
  • Keywords
    energy consumption; maximum power point trackers; particle swarm optimisation; solar cell arrays; convergence speed; energy consumption reduction; energy efficiency; maximum power point tracking algorithm; multipeak MPPT algorithm optimisation; particle swarm optimization algorithm; photovoltaic cell array; power fluctuation; voltage window restriction; Algorithm design and analysis; Arrays; Fluctuations; Lighting; Maximum power point trackers; Particle swarm optimization; Photovoltaic systems; multi-peak; optimization; particle swarm MPPT; photovoltaic power generation; voltage window;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines and Systems (ICEMS), 2014 17th International Conference on
  • Conference_Location
    Hangzhou
  • Type

    conf

  • DOI
    10.1109/ICEMS.2014.7013593
  • Filename
    7013593