DocumentCode :
138972
Title :
Optimization of photovoltaic module electrical characteristics using genetic algorithm (a comparative study between simulation and data sheet of PV Module)
Author :
Irwanto, M. ; Badlishah, R. ; Masri, M. ; Irwan, Y.M. ; Gomesh, N.
Author_Institution :
Sch. of Electr. Syst. Eng., Univ. Malaysia Perlis, Arau, Malaysia
fYear :
2014
fDate :
24-25 March 2014
Firstpage :
532
Lastpage :
536
Abstract :
This paper presents the optimization of PV module electrical characteristics using genetic algorithm (GA). A mathematical modeling was used to characterize the electrical characteristics of PV module. A 180 W, 30 V, Sharp mono-crystal silicon PV module (NUS0E3E) was used in this paper. This PV module consists of 48 solar cells configured in series strings. Under constant temperature and different solar irradiance were tested to the PV module using GA, its electrical characteristics shown in curves and compared to the data sheet and a reference and also 3-dimensional diagram as function of both solar irradiance and temperature shown and discussed. The result shows that the comparison of simulation results using GA with data sheet of current-voltage and power-voltage curve illustrates a good correlation, if the temperature constant and solar irradiance increase will cause the short circuit current, open circuit voltage, maximum power and efficiency increase.
Keywords :
elemental semiconductors; genetic algorithms; photovoltaic cells; photovoltaic power systems; short-circuit currents; silicon compounds; solar cells; 3D diagram; NUS0E3E; constant temperature; current-voltage curve; data sheet; genetic algorithm; mathematical modeling; open circuit voltage; photovoltaic module electrical characteristics optimization; power 180 W; power-voltage curve; sharp monocrystal silicon PV module; short circuit current; solar cells; solar irradiance; voltage 30 V; Genetic algorithms; Optimization; Photovoltaic systems; Short-circuit currents; Temperature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering and Optimization Conference (PEOCO), 2014 IEEE 8th International
Conference_Location :
Langkawi
Print_ISBN :
978-1-4799-2421-9
Type :
conf
DOI :
10.1109/PEOCO.2014.6814486
Filename :
6814486
Link To Document :
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