DocumentCode :
553522
Title :
Genetic algorithms for maximum power point tracking in photovoltaic systems
Author :
Hadji, Seddik ; Gaubert, Jean-Paul ; Krim, Fateh
Author_Institution :
Dept. Genie Electr., Univ. de Bejaia, Bejaia, Algeria
fYear :
2011
fDate :
Aug. 30 2011-Sept. 1 2011
Firstpage :
1
Lastpage :
9
Abstract :
This paper presents a novel genetic algorithm to carry out the maximum power point tracking based on the photovoltaic cell model. For that it is necessary to measure the open circuit voltage (Voc) and short circuit current (Isc), then the proposed algorithm gives directly and rapidly the optimal voltage (Vop) so the converter duty cycle can be adjusted. The simulation results are obtained by changing Isc and Voc values. The proposed technique permits to verify the linearity between Vop and Voc and between optimal current (Iop) and Isc. We also give a comparison with the conventional Perturb and Observe (P&O) and Incremental Conductance (IncCond) algorithms.
Keywords :
genetic algorithms; maximum power point trackers; solar cells; converter duty cycle; genetic algorithms; incremental conductance algorithms; maximum power point tracking; observe algorithms; open circuit voltage; optimal voltage; perturb algorithms; photovoltaic cell model; photovoltaic systems; short circuit current; Atmospheric measurements; Atmospheric modeling; Convergence; Genetic algorithms; Integrated circuit modeling; Temperature measurement; Voltage measurement; Genetic algorithms (GAs); Maximum power tracking (MPPT); Photovoltaic; Renewable energy systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics and Applications (EPE 2011), Proceedings of the 2011-14th European Conference on
Conference_Location :
Birmingham
Print_ISBN :
978-1-61284-167-0
Electronic_ISBN :
978-90-75815-15-3
Type :
conf
Filename :
6020380
Link To Document :
بازگشت