Meysam Bayat - Shahid Sattari Aeronautical university of Science and Technology
Mahmoud Samkan - Shahid Sattari Aeronautical university of Science and Technology
Hossein Moeinpour - Shahid Sattari Aeronautical university of Science and Technology

A photovoltaic (PV) power generation system under partial shaded conditions (PSC) exhibits multiple power peaks in the power-voltage (P-V) characteristic curve and traditional optimization methods fail to detect the global maximum power point (GMPP). This paper proposes a hybrid intelligent to improve the maximum power point (MPP) tracking capability for PV system under partial shading condition. The key advantage of the proposed technique is the elimination of PI control loops using direct duty cycle control method. Furthermore, since the proposed method is based on optimized search method, it overcomes the common drawback of the conventional MPPT, i.e.   To   evaluate   the   idea,   the   algorithm   is  implemented  on  a  boost  converter  and  compared  to  the  conventional      MPPT   methods.   Simulation  results  indicate  that  the  proposed  method  outperforms  others  method   in   terms   of   global   peak   (GP)   tracking   speed   and  accuracy under various partial shading conditions. Furthermore,  it  is  tested  using  data  of  a  tropical  cloudy  day,  which includes rapid movement of the passing clouds and partial shading.

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