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
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;
Conference_Titel :
Power Engineering and Optimization Conference (PEOCO), 2014 IEEE 8th International
Conference_Location :
Langkawi
Print_ISBN :
978-1-4799-2421-9
DOI :
10.1109/PEOCO.2014.6814390