Model-based fault detection and isolation of non-technical losses in electrical networks

Anna I. Pózna, Attila Fodor, K. Hangos

Research output: Contribution to journalArticle

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.

Original languageEnglish
JournalMathematical and Computer Modelling of Dynamical Systems
DOIs
Publication statusAccepted/In press - Jan 1 2019

Fingerprint

Fault Detection and Isolation
Electrical Networks
Fault detection
Model-based
Low Voltage
Diagnostics
Electric potential
Measurement Uncertainty
Transformer
Decomposition Method
Breakdown
Layout
Linear Model
Subsystem
Voltage
Grid
Decomposition
Uncertainty
Line
Model

Keywords

  • electrical networks
  • Model-based fault detection and isolation
  • network decomposition

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Modelling and Simulation
  • Computer Science Applications
  • Applied Mathematics

Cite this

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