Journal article
Diagnosis and mitigation of voltage and current sensors malfunctioning in a grid connected PV system
International Journal of Electrical Power & Energy Systems, Vol.115, pp.1-20
2020
Abstract
Accuracy of sensors measuring Photovoltaic (PV) array output voltage, current and the ac currents flowing between VSC and grid plays an indispensable role in efficient operation of a grid connected PV system. Erroneous measurements due to malfunctioning of aforementioned sensors can cause significant disruptions in the operation of a PV system, as the impact of erroneous measurements propagate through the controllers in a PV system. In this paper, malfunctioning of PV system sensors are regarded as sensor faults. This paper presents an approach for diagnosis and mitigation of sensor faults in a PV system. The fault diagnosis approach is based on the sliding mode observer (SMO)-based fault detection and identification theory, which is capable of accurately estimating faults in sensor measurements. Estimated faults are used by the fault mitigation technique in the proposed approach to rectify the sensor measurements. The rectified sensor measurements are used by the controllers in PV system, instead of possibly erroneous sensor measurements, which ensure fault resilient operation of the PV system. The efficacy of the proposed approach has been validated through rigorous simulation and experimental studies.
Details
- Title
- Diagnosis and mitigation of voltage and current sensors malfunctioning in a grid connected PV system
- Authors
- S Saha (Author) - Deakin UniversityM.E Haque (Author) - Deakin UniversityC.P Tan (Author) - Monash University MalaysiaM.A Mahmud (Author) - Deakin UniversityM.T Arif (Author) - Deakin UniversityS Lyden (Author) - University of TasmaniaN Mendis (Author) - DNVGL, Australia
- Publication details
- International Journal of Electrical Power & Energy Systems, Vol.115, pp.1-20
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.ijepes.2019.105381
- ISSN
- 1879-3517
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99532107702621
- Output Type
- Journal article
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