• DocumentCode
    138784
  • Title

    Maximum Power Point Tracking for stand-alone Photovoltaic system using Evolutionary Programming

  • Author

    Hashim, Noramiza ; Salam, Z. ; Ayob, S.M.

  • Author_Institution
    Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
  • fYear
    2014
  • fDate
    24-25 March 2014
  • Firstpage
    7
  • Lastpage
    12
  • Abstract
    This paper presents Maximum Power Point Tracking (MPPT) algorithm for stand-alone Photovoltaic (PV) system using Evolutionary Programming (EP) method. The EP has not been used for this system before, thus this work can be considered as new. The basic idea of applying EP for stand-alone PV System based MPPT is given. Simulation of PV system is carried out using Matlab/Simulink environment. In particular, the partial shading condition is addressed. To evaluate the accuracy of the algorithm, two statistical analysis namely; mean absolute error (MAE) and standard deviation (STD) have been carried out. The results are compared with MPPT using the Genetic Algorithm (GA). It was found that EP has a much better convergence speed, tracking accuracy and higher robustness compared to GA.
  • Keywords
    convergence; genetic algorithms; mathematics computing; maximum power point trackers; photovoltaic power systems; statistical analysis; EP method; GA; MAE; MPPT algorithm; Matlab-Simulink environment; STD; convergence speed; evolutionary programming method; genetic algorithm; maximum power point tracking algorithm; mean absolute error; partial shading condition; stand-alone PV System; stand-alone photovoltaic system; standard deviation; statistical analysis; tracking accuracy; Arrays; Convergence; Genetic algorithms; Maximum power point trackers; Sociology; Statistics; EP; GA; Photovoltaic system; maximum power point tracking; partial shading condition; soft computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering and Optimization Conference (PEOCO), 2014 IEEE 8th International
  • Conference_Location
    Langkawi
  • Print_ISBN
    978-1-4799-2421-9
  • Type

    conf

  • DOI
    10.1109/PEOCO.2014.6814390
  • Filename
    6814390