Adaptive Hybrid Maximum Power Point Tracking Method for a Photovoltaic System

Fan Zhang, Kary Thanapalan, Andrew Procter, Stephen Carr, Jon Maddy

Research output: Contribution to journalArticlepeer-review

Abstract

Recently, the importance of exploring the plausibility
of renewable energy has been progressively increased, not only because of concerns over the shortage of current fossil fuels but also the consideration of sustainable development and the negative environmental impact caused by large scale use of fossil fuels. Among renewable sources, solar energy seems to be one of the promising energy sources for widespread application. Due to its inherent intermittency and fluctuation, one of the important research interests is to harness the maximum power possible from the solar energy falling on a panel. To this end, an efficient maximum power point tracker to harvest as much energy as possible is a key to improving the system’s efficiency and performance. This paper presents a novel hybrid maximum power point tracking mechanism with adaptive perturbation size. The proposed method is implemented, analyzed, and evaluated in MATLAB/Simulink. Both numerical and experimental evaluation results prove that by using the proposed method, better tracking performance can be achieved and the power delivered at steady state can be increased by a factor of 7.31% compared with conventional methods.
Original languageEnglish
Pages (from-to)353 - 360
Number of pages8
JournalIEEE Transactions on Energy Conversion
Volume28
Issue number2
DOIs
Publication statusPublished - 15 Jun 2013

Fingerprint

Dive into the research topics of 'Adaptive Hybrid Maximum Power Point Tracking Method for a Photovoltaic System'. Together they form a unique fingerprint.

Cite this