High Impedance Fault Detection using LVQ Neural Networks
| Main Authors: | Abhishek Bansal, G. N. Pillai |
|---|---|
| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2007
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1076870 |
Daftar Isi:
- This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.