Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Journal of Applied Sciences
Year: 2014  |  Volume: 14  |  Issue: 16  |  Page No.: 1858 - 1864

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    

Abstract: 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.

Cited References   |    Fulltext    |   Related Articles   |   Back
  Related Articles

Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility