FPA based approach for solar maximum power point tracking

Due to the regular availability, pollution free and eco-friendly nature, power generation from solar energy has gained considerable attention. Although, power generation from solar is attractive; the environmental factors such as irradiation and temperature makes it challenging. In particular, it is a demanding task to researchers to extract maximum power different shading conditions. However, to extract maximum power various MPPT techniques have been proposed in conventional method and Evolutionary algorithm implemented methods. In the paper, by considering the limitations of aforementioned methods, a new nature inspired flower pollination algorithm (FPA) is proposed. Compared to the inability in conventional methods under partial shaded conditions, the FPA yields very good performance. Further, different shading patterns are tested and the results are compared with P&O and HC (hill climbing) methods. The results of FPA acknowledges its potential in attaining good convergence, high efficiency and less complexity.

[1]  Xin-She Yang,et al.  Multi-Objective Flower Algorithm for Optimization , 2014, ICCS.

[2]  N. Rajasekar,et al.  Bacterial Foraging Algorithm based solar PV parameter estimation , 2013 .

[3]  S Ahmed,et al.  High-Performance Adaptive Perturb and Observe MPPT Technique for Photovoltaic-Based Microgrids , 2011, IEEE Transactions on Power Electronics.

[4]  N. Rajasekar,et al.  Application of Modified Particle Swarm Optimization for Maximum Power Point Tracking under Partial Shading Condition , 2014 .

[5]  M. Adly,et al.  Ant colony system based PI maximum power point tracking for stand alone photovoltaic system , 2012, 2012 IEEE International Conference on Industrial Technology.

[6]  Whei-Min Lin,et al.  Neural-Network-Based MPPT Control of a Stand-Alone Hybrid Power Generation System , 2011, IEEE Transactions on Power Electronics.

[7]  Mohammad A. S. Masoum,et al.  Closure on "Theoretical and experimental analyses of photovoltaic systems with voltage and current-based maximum power point tracking" , 2002 .

[8]  M. Masoum,et al.  Theoretical and Experimental Analyses of Photovoltaic Systems with Voltage and Current-Based Maximum Power Point Tracking , 2002, IEEE Power Engineering Review.

[9]  N. Rajasekar,et al.  Voltage band based improved particle swarm optimization technique for maximum power point tracking in solar photovoltaic system , 2016 .

[10]  Tomonobu Senjyu,et al.  Maximum power point tracking control of IDB converter supplied PV system , 2001 .

[11]  B N Alajmi,et al.  Fuzzy-Logic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System , 2011, IEEE Transactions on Power Electronics.

[12]  D. Petreus,et al.  A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading , 2014 .

[13]  Kashif Ishaque,et al.  A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition , 2013 .

[14]  Kenji Kobayashi,et al.  A study on a two stage maximum power point tracking control of a photovoltaic system under partially shaded insolation conditions , 2003, IEEE Power Engineering Society General Meeting.

[15]  Saad Mekhilef,et al.  Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter , 2011, IEEE Transactions on Industrial Electronics.

[16]  R. Ramaprabha,et al.  Maximum power point tracking of partially shaded solar PV system using modified Fibonacci search method with fuzzy controller , 2012 .

[17]  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..