4.8 Article

An Improved Sparse-Measurement-Based Fault Location Technology for Distribution Networks

Journal

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 17, Issue 3, Pages 1712-1720

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.2995997

Keywords

Fault location; Estimation; Meters; Voltage measurement; Impedance; Informatics; Resource management; Distribution networks; fault location; sparse-measurement based; voltage magnitude

Funding

  1. National Key Research and Development Program of China [2018YFB0904104]
  2. Science and Technology Project of State Grid [SGHB0000KXJS1800685]

Ask authors/readers for more resources

This article proposes a sparse-measurement-based fault location method for all fault types in distribution networks, requiring voltage samplings at a few buses before and during the fault. The theoretical deduction of the sparse meter allocation principles contributes to the good performance and feasibility of the method.
In this article, a sparse-measurement-based fault location method for all fault types in the distribution networks with/without the distributed generators access is proposed. The pre- and during-fault voltage samplings at a few buses are needful to estimate the fault position via a compressed sensing algorithm. Besides, the principles of the sparse meter allocation are theoretically deduced, which are of directive significance for the practical implementation of the proposed method. Furthermore, the method possesses feasibility for the fault resistance of smaller than 50 omega and metering noise of lower than 1%. The performance of the method is tested on a 12.66 kV, 69-bus distribution network model established in the real-time digital simulator. Simulation results verified that the proposed method is of a good performance for various scenarios.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available