Dhimish, M, Holmes, V, Dales, M et al. (4 more authors) (2017) Fault Detection Algorithm for Multiple GCPV Array Configurations. In: 2017 IEEE Manchester PowerTech. PowerTech 2017, 18-22 Jun 2017, Manchester, UK. IEEE ISBN 978-1-5090-4237-1
Abstract
In this paper, a fault detection algorithm for multiple grid-connected photovoltaic (GCPV) array configurations is introduced. For a given set of conditions such as solar irradiance and photovoltaic module temperature, a number of attributes such as power, voltage and current are calculated using a mathematical simulation model. Virtual instrumentation (VI) LabVIEW software is used to monitor the performance of the GCPV system and to simulate the theoretical I-V and P-V curves of the examined system. The fault detection algorithm is evaluated on multiple GCPV array configurations such as series, parallel and series-parallel array configuration. The fault detection algorithm has been validated using 1.98 kWp GCPV system installed at the University of Huddersfield. The results indicates that the algorithm is capable to detect multiple faults in the examined GCPV plant and can therefore be used in large GCPV installations.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Copyright IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Photovoltaic (PV); Fault detection algorithm; GCPV multiple array configurations; VI LabVIEW software; Fault detection, Voltage measurement, Algorithm design and analysis, Power measurement, Circuit faults, Arrays, Software algorithms |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Feb 2018 12:43 |
Last Modified: | 13 May 2019 07:57 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/PTC.2017.7980825 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:127730 |