Title :
Optimization of solar power by azimuthal angle and neural network control of a PV module
Author :
Dubey, Richa ; Joshi, Devashree
Author_Institution :
Electr. Eng., NIT Kurukshetra, Kurukshetra, India
Abstract :
In recent year´s renewable energy sources have become a useful alternative for the power generation. Moreover conventional sources cause the pollution and global warming. In this work, the sun tracking algorithm is developed to track sun position to receive maximum radiation. DC power from solar panel is fed to the buck-boost converter for the adjustment of voltage at load end. The mathematical modeling of system component is done in MATLAB code. For maximum power point tracking artificial intelligent tools such as artificial neural network (ANN) is used. In this proposed system two control algorithms is applied simultaneously to get maximum power at output end. The complete system efficiency is obtained. System analysis is done in Kurukshetra India, so the latitude angle is taken accordingly.
Keywords :
global warming; mathematics computing; maximum power point trackers; neural nets; neurocontrollers; photovoltaic power systems; power convertors; power generation control; renewable energy sources; solar power stations; ANN; DC power; Kurukshetra India; Matlab code; PV module; artificial neural network; azimuthal angle; buck-boost converter; global warming; maximum power point tracking artificial intelligent tools; neural network control; power generation; solar power optimization; sun tracking algorithm; Artificial neural networks; Earth; Fuzzy logic; Mathematical model; Sun; Temperature; PV module; Sun position tracking; artificial neural network; dc-dc converter;
Conference_Titel :
Power Electronics (IICPE), 2012 IEEE 5th India International Conference on
Conference_Location :
Delhi
Print_ISBN :
978-1-4673-0931-8
DOI :
10.1109/IICPE.2012.6450497