Photovoltaic array fault detection by automatic reconfiguration
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Article number | 699 |
Journal / Publication | Energies |
Volume | 10 |
Issue number | 5 |
Publication status | Published - 2017 |
Externally published | Yes |
Link(s)
DOI | DOI |
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Attachment(s) | Documents
Publisher's Copyright Statement
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85036627341&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(d49d5128-e7a5-4ac8-8669-5c2a369c18c3).html |
Abstract
Photovoltaic (PV) system output electricity is related to PV cells' conditions, with the PV faults decreasing the efficiency of the PV system and even causing a possible source of fire. In industrial production, PV fault detection is typically laborious manual work. In this paper, we present a method that can automatically detect PV faults. Based on the observation that different faults will have different impacts on a PV system, we propose a method that systematically and iteratively reconfigures the PV array until the faults are located based on the specific current-voltage (I-V) curve of the (sub-)array. Our method can detect several main types of faults including open-circuit faults, mismatch faults, short circuit faults, etc. We evaluate our methods by Matlab/Simulink-based simulation. The results show that the proposed methods can accurately detect and classify the different faults occurring in a PV system.
Research Area(s)
- Fault detection, I-V curve, Photovoltaic, Reconfiguration, TCT
Bibliographic Note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
Citation Format(s)
Photovoltaic array fault detection by automatic reconfiguration. / Ji, Dong; Zhang, Cai; Lv, Mingsong et al.
In: Energies, Vol. 10, No. 5, 699, 2017.
In: Energies, Vol. 10, No. 5, 699, 2017.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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