Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12229
Title: Model based rapid maximum power point tracking for photovoltaic systems
Authors: Tsang, KM 
Chan, WL 
Keywords: Maximum power point tracking
Photovoltaic system
Polynomial model
Issue Date: 2013
Publisher: Pergamon Press
Source: Energy conversion and management, 2013, v. 70, p. 83-89 How to cite?
Journal: Energy conversion and management 
Abstract: This paper presents a novel approach for tracking the maximum power point of photovoltaic (PV) systems so as to extract maximum available power from PV modules. Unlike conventional methods, a very fast tracking response with virtually no steady state oscillations is able to obtain in tracking the maximum power point. To apply the proposed method, firstly, output voltages, output currents under different conditions and temperatures of a PV module are collected for the fitting of environmental invariant nonlinear model for the PV system. Orthogonal least squares estimation algorithm coupled with the forward searching algorithm is applied to sort through all possible candidate terms resulted from the expansion of a polynomial model and to come up with a parsimonious model for the PV system. It is not necessary to test all PV modules as the resultant model is valid for other modules. The power delivered by the PV system can be derived from the fitted model and the maximum power point for the PV system at any working conditions can be obtained from the fitted model. Consequently, rapid maximum power point tracking could be achieved. Experimental results are included to demonstrate the effectiveness of the fitted model in maximum power point tracking.
URI: http://hdl.handle.net/10397/12229
ISSN: 0196-8904
EISSN: 1879-2227
DOI: 10.1016/j.enconman.2013.02.018
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

25
Last Week
0
Last month
2
Citations as of Aug 13, 2017

WEB OF SCIENCETM
Citations

21
Last Week
0
Last month
1
Citations as of Aug 12, 2017

Page view(s)

33
Last Week
3
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.