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

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.

[1]  Bidyadhar Subudhi,et al.  A Comparative Study on Maximum Power Point Tracking Techniques for Photovoltaic Power Systems , 2013, IEEE Transactions on Sustainable Energy.

[2]  P.L. Chapman,et al.  Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques , 2007, IEEE Transactions on Energy Conversion.

[3]  Jubaer Ahmed,et al.  The application of soft computing methods for MPPT of PV system: A technological and status review , 2013 .

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

[5]  Kit Po Wong,et al.  Evolutionary programming based optimal power flow algorithm , 1999 .

[6]  Mariano Sidrach-de-Cardona,et al.  Theoretical assessment of the maximum power point tracking efficiency of photovoltaic facilities with different converter topologies , 2007 .

[7]  Kashif Ishaque,et al.  Simple, fast and accurate two-diode model for photovoltaic modules , 2011 .

[8]  Andres Barrado,et al.  Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems , 2006 .

[9]  Ismail Musirin,et al.  Assessment of evolutionary programming models for single-objective optimization , 2013, 2013 IEEE 7th International Power Engineering and Optimization Conference (PEOCO).

[10]  P. K. Chattopadhyay,et al.  Evolutionary programming techniques for economic load dispatch , 2003, IEEE Trans. Evol. Comput..

[11]  Rajesh Kumar Nema,et al.  Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications , 2013 .

[12]  Syafaruddin,et al.  Modeling and simulation of photovoltaic (PV) system during partial shading based on a two-diode model , 2011, Simul. Model. Pract. Theory.

[13]  M. E. Ropp,et al.  Comparative study of maximum power point tracking algorithms , 2003 .

[14]  Syafaruddin,et al.  A comprehensive MATLAB Simulink PV system simulator with partial shading capability based on two-diode model , 2011 .

[15]  Mohamed Azab,et al.  Optimal power point tracking for stand-alone PV system using particle swarm optimization , 2010, 2010 IEEE International Symposium on Industrial Electronics.

[16]  Chee Kiong Soh,et al.  An evolutionary programming algorithm for continuous global optimization , 2006, Eur. J. Oper. Res..

[17]  I. Musirin,et al.  Design of grid-connected photovoltaic system using evolutionary programming , 2010, 2010 IEEE International Conference on Power and Energy.

[18]  D. Fogel Applying evolutionary programming to selected traveling salesman problems , 1993 .