Photovoltaic Battery Charging System Based on PIC16F877A Microcontroller
Zaki Majeed Abdu-Allah1, Omar Talal Mahmood2, Ahmed M. T. Ibraheem AL-Naib3
1Zaki Majeed Abdu-Allah, Dept. of Electrical Technologies, Foundation of Technical Education, Technical Institute Hawija, Kirkuk, Iraq.
2Omar Talal Mahmood, Dept. of Electrical Technologies, Foundation of Technical Education, Technical Institute Hawija, Kirkuk, Iraq.
3Ahmed M. T. Ibraheem AL, Dept. of Electrical Technologies, Foundation of Technical Education, Technical Institute Hawija, Kirkuk, Iraq.
Manuscript received on March 21, 2014. | Revised Manuscript received on April 10, 2014. | Manuscript published on April 30, 2014. | PP: 27-31 | Volume-3, Issue-4, April 2014. | Retrieval Number: D2782043414/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper represents a simulation and design of two types of Maximum Power Point Tracking (MPPT) algorithm methods is proposed. Here the PV system is composed to a boost converter which can perform with those algorithm methods. In this the algorithm methods are Perturb and Observe (P&O) and Probability of Neural Network (PNN). The probability of neural network which can be deals with the neurons and can be included the neural based Maximum Power Point Tracking. By using these different MPPT techniques we can maximize the PV array output which can be track continuously from the solar panel’s temperature and irradiation. These MPPT techniques can be explained by using the MATLAB.
Keywords: Solar Module, Maximum Power Point Tracking (MPPT), Perturb and Observe (P&O) and Probability of Neural Network (PNN).