Research Article

Maximum Power Point Tracking of Photovoltaic Generation System using Artificial Neural Network with Improved Tracking Factor

K. Arthishri, R. Balasubramanian, Parkavi Kathirvelu, Sishaj P. Simon and Rengarajan Amirtharajan

This study presents an analysis of neural network scheme for tracking Maximum Power Point (MPP) of the PV panel. The performance in terms of energy conversion efficiency is compared with the most commonly used P and O algorithm. The method used for MPP Tracking (MPPT) is tuned for giving its best efficiency using a planned calibration procedure. The non linearity of the PV panel is replicated considering the mathematical equations of the solar cell. MATLAB/Simulink is used to simulate the PV panel model along with a conventional DC-DC boost converter for MPPT.

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K. Arthishri, R. Balasubramanian, Parkavi Kathirvelu, Sishaj P. Simon and Rengarajan Amirtharajan, 2014. Maximum Power Point Tracking of Photovoltaic Generation System using Artificial Neural Network with Improved Tracking Factor. Journal of Applied Sciences, 14: 1858-1864.

DOI: 10.3923/jas.2014.1858.1864

URL: https://scialert.net/abstract/?doi=jas.2014.1858.1864

Journal of Applied Sciences

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Authors

K. Arthishri

R. Balasubramanian

Parkavi Kathirvelu

Sishaj P. Simon

Rengarajan Amirtharajan

Keywords

Research Article

Maximum Power Point Tracking of Photovoltaic Generation System using Artificial Neural Network with Improved Tracking Factor

How to cite this article

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