DocumentCode :
2675107
Title :
Maximum power point tracking using GA-optimized artificial neural network for Solar PV system
Author :
Ramaprabha, R. ; Gothandaraman, V. ; Kanimozhi, K. ; Divya, R. ; Mathur, B.L.
Author_Institution :
Dept. of Electr. & Electron. Eng., SSN Coll. of Eng., Chennai, India
fYear :
2011
fDate :
3-5 Jan. 2011
Firstpage :
264
Lastpage :
268
Abstract :
Solar energy is a green energy which is not only perennial but also accessible to every strata of the world. An easy way to convert solar energy into electric energy is to use Solar Photovoltaic (SPV) system. Solar panel is a power source having nonlinear internal resistance. As the intensity of light falling on the panel varies, its voltage as well as its internal resistance varies. To extract maximum power from the panel, the load resistance should be equal to the internal resistance of the panel. For this purpose maximum power point trackers (MPPT) are used. This paper proposes a new MPPT controller. The proposed MPPT controller is based on genetic algorithm (GA) optimized artificial neural network (ANN). For the simulation purpose an improved model of SPV is used. The MPPT is simulated and studied using MATLAB software.
Keywords :
genetic algorithms; maximum power point trackers; neural nets; photovoltaic power systems; power engineering computing; solar cells; MATLAB software; MPPT controller; artificial neural network; electric energy; genetic algorithm; green energy; maximum power point tracking; nonlinear internal resistance; solar energy; solar panel; solar photovoltaic system; Artificial neural networks; Biological system modeling; Gallium; Integrated circuit modeling; Mathematical model; Photovoltaic systems; Resistance; ANN; GA; MATLAB; MPPT; Solar PV system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Energy Systems (ICEES), 2011 1st International Conference on
Conference_Location :
Newport Beach, CA
Print_ISBN :
978-1-4244-9732-4
Type :
conf
DOI :
10.1109/ICEES.2011.5725340
Filename :
5725340
Link To Document :
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