Unbalanced Underground Distribution Systems Fault Detection and Section Estimation

  • Authors:

  • Karen Rezende Oliveira;Rodrigo Hartstein Salim;André Darós Filomena;Mariana Resener;Arturo Suman Bretas

  • Affiliations:

  • Electric Engineering Department, Federal University of Rio Grande do Sul, Av. Osvaldo Aranha, 103, Porto Alegre, 90035-190, Brazil;Electric Engineering Department, Federal University of Rio Grande do Sul, Av. Osvaldo Aranha, 103, Porto Alegre, 90035-190, Brazil;Electric Engineering Department, Federal University of Rio Grande do Sul, Av. Osvaldo Aranha, 103, Porto Alegre, 90035-190, Brazil;Electric Engineering Department, Federal University of Rio Grande do Sul, Av. Osvaldo Aranha, 103, Porto Alegre, 90035-190, Brazil;Electric Engineering Department, Federal University of Rio Grande do Sul, Av. Osvaldo Aranha, 103, Porto Alegre, 90035-190, Brazil

  • Venue:
  • ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents a novel fault detection and section estimation method for unbalanced underground distribution systems (UDS). The method proposed is based on artificial neural networks (ANNs) and wavelet transforms (WTs). The majority of UDS are characterized by having several single/double phase laterals and non-symmetrical lines. Also, Digital Fourier Transforms (DFT), used in the majority of traditional protection relays, supplies a low level of robustness to the fault diagnosis process due to its inversely proportional time-frequency characteristic. These characteristics compromise the traditional fault diagnosis methods performance. ANNs are capable of learning and generalizing, whereas WTs are robust tools capable of evaluating a signal's frequency range that can characterize the fault phenomenon. This paper describes the proposed diagnosis method and discusses the results obtained from simulated implementation. The obtained results demonstrate the capability and robustness of the technique indicating its potential for on-line applications.