• DocumentCode
    3766978
  • Title

    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm

  • Author

    Dhiaa Halboot Muhsen;Abu Bakar Ghazali;Tamer Khatib

  • Author_Institution
    Department of EC Engineering, University of Tenaga, Nasional, Malaysia
  • fYear
    2015
  • Firstpage
    533
  • Lastpage
    538
  • Abstract
    This paper proposes a new method for extracting parameters of double diode model of photovoltaic module, based on differential evolution with adaptive mutation per iteration (DEAM) algorithm. The proposed method combined the mutation mechanism of electromagnetism-like algorithm with conventional version of different evolution (DE) algorithm to enhance the performance of DE. Furthermore, a new formula to adjust the mutation scaling factor and crossover rate for each generation is proposed. The performance of DEAM has been evaluated using experimental data and other previous methods in literature. According to the results, the proposed method offers better performance than other methods in terms of accuracy and convergence. Furthermore, the feasibility of proposed methods is validated by comparing the obtained results with other previous methods using various statistical errors.
  • Keywords
    "Sociology","Statistics","Integrated circuit modeling","Convergence","Numerical models","Genetic algorithms","Linear programming"
  • Publisher
    ieee
  • Conference_Titel
    Research and Development (SCOReD), 2015 IEEE Student Conference on
  • Type

    conf

  • DOI
    10.1109/SCORED.2015.7449393
  • Filename
    7449393