Transmission Line Fault using Line Voltages and Currents as Features

Citation Author(s):: Paul Michael Custodio (Department of IT Convergence Engineering, Kumoh National Institute of Technology)

Dong-Seong Kim (Department of IT Convergence Engineering, Kumoh National Institute of Technology)

Jae-Min Lee (Department of IT Convergence Engineering, Kumoh National Institute of Technology)
Submitted by:: Paul Michael Custodio
Last updated:: Tue, 03/26/2024 - 10:02
DOI:: 10.21227/6rmd-f728
Data Format:: *.csv ; *.xlsx
Research Article Link:: TLFed: Federated Learning-based 1D-CNN-LSTM Transmission Line Fault Location an…

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Categories:

Keywords:

Power System

Transmission Line Fault

fault classification

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Abstract

Different faults are experienced by a power system, particulary in transmission lines. In this dataset, the IEEE 5-Bus Model was used to different types of transmission line faults.

Indication of the label of the faults come from the time that the fault has been induced in the simulation.

This dataset aims to be utilized for machine learning algorithms, particularly in multi-class classification of the transmission line fault. In this simulation, each fault was induced at each transmission line one instance at a time during a certain period.

The features of this data set are the line voltages (Va, Vb, Vc) and line currents (Ia, Ib, Ic) of each phase of each transmission line. Forming a total of forty-two (42) features, having two output targets: Type of Fault and Fault Location.

Fault Types are labeled as follows: No fault, L-L-L, L-L-L-G, DLG, L-L, SLG, Line fault

Fault Location are as follows: No fault, L12, L13, L23, L24, L25, L34, L45