Design, simulation and implementation of an intelligent MPPT using a ZVCS resonant DCDC converter

Jafari, M; Malekjamshidi, Z; Jian Guo Zhu

Design, simulation and implementation of an intelligent MPPT using a ZVCS resonant DCDC converter

Jafari, M

Malekjamshidi, Z

Jian Guo Zhu

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Publication Type:: Conference Proceeding
Citation:: PECon 2012 - 2012 IEEE International Conference on Power and Energy, 2012, pp. 280 - 285
Issue Date:: 2012-12-01

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Field	Value	Language
dc.contributor.author	Jafari, M https://orcid.org/0000-0002-8521-8636	en_US
dc.contributor.author	Malekjamshidi, Z https://orcid.org/0000-0002-5951-620X	en_US
dc.contributor.author	Jian Guo Zhu https://orcid.org/0000-0002-9763-4047	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	PECon 2012 - 2012 IEEE International Conference on Power and Energy, 2012, pp. 280 - 285	en_US
dc.identifier.isbn	9781467350198	en_US
dc.identifier.uri	http://hdl.handle.net/10453/23098
dc.description.abstract	Maximum Power Point Trackers (MPPT) are widely used in PV applications. This is because the Maximum Power Point (MPP) of a solar panel varies with the irradiation and temperature so MPPT is required to adjust the PV power point on the maximum state. On the other hand a DC-DC converter should be used to overcome variations in PV panel output power and draw the maximum power. In this paper, an intelligent Maximum Power Point Tracker (MPPT) is designed on base of Artificial Neural Networks (ANN). The ANN controller receives temperature, voltage and current of PV panel and solar radiation as input signals. In the next step it estimates the optimum duty cycle of converter for maximum available power. To optimize efficiency of the system, a Full bridge Series-Parallel DC Converter was designed. Soft switching operation using Zero Current Switching (ZCS) and Zero Voltage Switching (ZVS) technologies is employed to decrease the losses and optimize the efficiency of converter. To evaluate the performances of proposed intelligent MPPT, a prototype is implemented and experimental results are presented. © 2012 IEEE.	en_US
dc.relation.ispartof	PECon 2012 - 2012 IEEE International Conference on Power and Energy	en_US
dc.relation.isbasedon	10.1109/PECon.2012.6450222	en_US
dc.title	Design, simulation and implementation of an intelligent MPPT using a ZVCS resonant DCDC converter	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
dc.location.activity	Kota kinabalu, Malaysia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Maximum Power Point Trackers (MPPT) are widely used in PV applications. This is because the Maximum Power Point (MPP) of a solar panel varies with the irradiation and temperature so MPPT is required to adjust the PV power point on the maximum state. On the other hand a DC-DC converter should be used to overcome variations in PV panel output power and draw the maximum power. In this paper, an intelligent Maximum Power Point Tracker (MPPT) is designed on base of Artificial Neural Networks (ANN). The ANN controller receives temperature, voltage and current of PV panel and solar radiation as input signals. In the next step it estimates the optimum duty cycle of converter for maximum available power. To optimize efficiency of the system, a Full bridge Series-Parallel DC Converter was designed. Soft switching operation using Zero Current Switching (ZCS) and Zero Voltage Switching (ZVS) technologies is employed to decrease the losses and optimize the efficiency of converter. To evaluate the performances of proposed intelligent MPPT, a prototype is implemented and experimental results are presented. © 2012 IEEE.

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http://hdl.handle.net/10453/23098