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DSP-Based Hands-On Laboratory Experiments for Photovoltaic Power Systems

Bibliographic Data

ID20297695
AuthorsPolycarp I Muoka (University of Tasmania), Md Enamul Haque (0000-0002-6195-0160, University of Tasmania), Ameen Gargoom (0000-0002-4635-4993, University of Tasmania), Michael Negnevitsky (0000-0002-5130-419X, University of Tasmania)
Year2015
Volume58
Issue1
Pages39-47
Publication date2015-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Education (JOURNAL)
Journal identifiersISSN: 0018-9359 • E-ISSN: 1557-9638
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/te.2014.2323937
OpenAlexW2046908375
LanguageEN
Citations received3
References cited13

This paper presents a new photovoltaic (PV) power systems laboratory module that was developed to experimentally reinforce students' understanding of design principles, operation, and control of photovoltaic power conversion systems. The laboratory module is project-based and is designed to support a renewable energy course. By using MATLAB real-time software tools in combination with digital signal processor (DSP) hardware tools, the module enables students to: 1) design and build dc–dc and dc–ac power converters; 2) design and implement control algorithms for maximum power point tracking (MPPT) and voltage and current regulation; and 3) design and fabricate a printed circuit board for voltage and current sensing, isolation, and gate driving. In these hands-on experiments, by designing and building their hardware and software integrated systems themselves, students learn by doing and experience the engineering transformative process of building a product out of an idea. This paper is motivated by the dearth of literature on the application of project-based learning methodology to PV systems. The module description, the pedagogical and evaluation methodologies adopted, and reflections on the implementations are discussed

Converters · Digital signal processing · Electrical engineering · Electronic engineering · Inverter · Maximum power point tracking · Photovoltaic system · Voltage · Computer Science · Engineering · Experimental Learning in Engineering · Photovoltaic System Optimization Techniques · Software · solar cell performance optimization

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Unique citing works3
Citations per year0.3
Citation span2016 - 2019 (4)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 2

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