Model-based fault detection and isolation of non-technical losses in electrical networks
Anna I. Pózna,
Attila Fodor and
Katalin M. Hangos
Mathematical and Computer Modelling of Dynamical Systems, 2019, vol. 25, issue 4, 397-428
Abstract:
A model-based diagnostic method is proposed for detecting and isolating non-technical losses (illegal loads) in low voltage electrical grids of one transformer area. The proposed method uses a simple static linear model of the network and it is based on analysing the differences between the measured and model-predicted voltages. As a preliminary off-line step of the diagnosis, a powerful electrical decomposition method is proposed, which breaks down the overall network to subsystems with one feeder layout enabling to make the computation efficient. The uncertainty in the model parameters together with the measurement uncertainties are also taken into account to make the approach applicable in real-world cases. The proposed method is able to detect and localize multiple illegal loads, and the amount of the illegal consumption can also be estimated. The operation and the diagnostic capabilities of the method are illustrated on a case study using the IEEE 2015 European Low Voltage Test Feeder.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/13873954.2019.1655066 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:nmcmxx:v:25:y:2019:i:4:p:397-428
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/NMCM20
DOI: 10.1080/13873954.2019.1655066
Access Statistics for this article
Mathematical and Computer Modelling of Dynamical Systems is currently edited by I. Troch
More articles in Mathematical and Computer Modelling of Dynamical Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().