Couple Matching Best Generation Algorithm for Partially Shaded Photovoltaic Systems

This paper proposes a new active electrical reconfiguration algorithm for the partially shaded Photovoltaic array systems. This algorithm can produce higher power compared to other methods which are proposed earlier. In the proposed method, total Photovoltaic array is split into two half, one is the male part and another is the female part. Each part is having equal rows and almost equal columns. The couple matching best generation algorithm is introduced in this paper, which uses short circuit current of each row and switching matrix circuit to extract maximum power. The short circuit current is used to find the weak and healthy rows of both male and female part and switching matrix circuit is used to couple the weaker with the healthier for the best power generation. This reconfiguration is simple, and easy for implementation. The proposed system extract maximum power compared to other existing methods. In this paper the proposed method is discussed with 3×4 array, which can also be extended for any type of array combinations. The simulation of the proposed method is performed in MATLAB software and the results are verified in hardware.

[1]  Miroslav Krstic,et al.  Multivariable maximum power point tracking for photovoltaic micro-converters using extremum seeking , 2015 .

[2]  N. Rajasekar,et al.  Modified Particle Swarm Optimization technique based Maximum Power Point Tracking for uniform and under partial shading condition , 2015, Appl. Soft Comput..

[3]  Vivek Kaundal,et al.  Tracing of shading effect on underachieving SPV cell of an SPV grid using wireless sensor network , 2015 .

[4]  M. Arutchelvi,et al.  Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions , 2015 .

[5]  Daniel Hissel,et al.  Reconfiguration solution for shaded PV panels using switching control , 2015 .

[6]  Vincenzo d'Alessandro,et al.  An automated high-granularity tool for a fast evaluation of the yield of PV plants accounting for shading effects , 2015 .

[7]  Santi Agatino Rizzo,et al.  ANN based MPPT method for rapidly variable shading conditions , 2015 .

[8]  Shaowu Li,et al.  A maximum power point tracking control strategy with variable weather parameters for photovoltaic systems with DC bus , 2015 .

[9]  Wei Sun,et al.  Study on maximum power point tracking of photovoltaic array in irregular shadow , 2015 .

[10]  Ahmed Fathy,et al.  Reliable and efficient approach for mitigating the shading effect on photovoltaic module based on Modified Artificial Bee Colony algorithm , 2015 .

[11]  Saravana Ilango Ganesan,et al.  Positioning of PV panels for reduction in line losses and mismatch losses in PV array , 2015 .

[12]  Parimita Mohanty,et al.  MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions , 2014 .

[13]  Denise Wilson,et al.  Maximum power tracking in solar cell arrays using time-based reconfiguration , 2013 .

[14]  Koray Şener Parlak,et al.  PV array reconfiguration method under partial shading conditions , 2014 .

[15]  Lian Lian Jiang,et al.  A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics , 2015 .

[16]  Guihua Liu,et al.  An Advanced Universal Power Quality Conditioning System and MPPT method for grid integration of photovoltaic systems , 2015 .

[17]  George Papadakis,et al.  An Intelligent MPPT controller based on direct neural control for partially shaded PV system , 2015 .

[18]  Rui Melício,et al.  Effect of Shading on Series Solar Modules: Simulation and Experimental Results , 2014 .

[19]  M Mahendran,et al.  PERMANENT MISMATCH FAULT IDENTIFICATION OF PHOTOVOLTAIC CELLS USING ARDUINO , 2015 .

[20]  Z. Salam,et al.  An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency , 2015 .