Subscribe Now Subscribe Today
Science Alert
 
Blue
   
Curve Top
Journal of Applied Sciences
  Year: 2014 | Volume: 14 | Issue: 16 | Page No.: 1858-1864
DOI: 10.3923/jas.2014.1858.1864
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

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.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    Design and Simulation of UPQC to Improve Power Quality and Transfer Wind Energy to Grid
  •    Combined Operation of Unified Power Quality Conditioner and Photovoltaic Array
  •    A Review of Designing, Installing and Evaluating Standalone Photovoltaic Power Systems
  •    Deign of Photovoltaic Water Pumping Systems at Minimum Cost for Palestine: A Review
How to cite this article:

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

COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 

Curve Bottom