Fast Model-Based Fault Detection in Single-Phase Photovoltaic Systems

Simon Mayr, Gernot Grabmair, Johann Reger

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

2 Zitate (Scopus)

Abstract

We present a model-based approach for the instant detection of faults on the DC side of photovoltaic (PV) systems. The algorithm does not identify the faults itself, but estimates the nominal PV system behavior, i.e. system parameters, using simple PV and line models. Sudden deviations from the expected model behavior serve as an indicator for the ignition of a fault. To ensure that the PV model parameters can be estimated, an identifiability analysis has to be performed. The performance of the algorithm is demonstrated exemplarily by the detection of serial electric arcs in PV systems. Measurement results show that all series arc faults are successfully detected. There are no false detections due to maximum power point tracking (MPPT) operations or environmental influences like shading, changes in solar irradiation, etc. The main advantages of the presented method are less computational effort, resulting in very fast detection times, and its flexible integration into existing systems.

OriginalspracheEnglisch
TitelIECON
UntertitelIECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
Herausgeber (Verlag)IEEE Computer Society
Seiten4615-4622
Seitenumfang8
ISBN (elektronisch)9781728148786
DOIs
PublikationsstatusVeröffentlicht - Okt. 2019
Veranstaltung45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 - Lisbon, Portugal
Dauer: 14 Okt. 201917 Okt. 2019

Publikationsreihe

NameIECON Proceedings (Industrial Electronics Conference)
Band2019-October

Konferenz

Konferenz45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019
Land/GebietPortugal
OrtLisbon
Zeitraum14.10.201917.10.2019

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