Distribution Network Fault Prediction Utilising Protection Relay Disturbance Recordings And Machine Learning
Signal Processing
2023-06-23 v1
Abstract
As society becomes increasingly reliant on electricity, the reliability requirements for electricity supply continue to rise. In response, transmission/distribution system operators (T/DSOs) must improve their networks and operational practices to reduce the number of interruptions and enhance their fault localization, isolation, and supply restoration processes to minimize fault duration. This paper proposes a machine learning based fault prediction method that aims to predict incipient faults, allowing T/DSOs to take action before the fault occurs and prevent customer outages.
Keywords
Cite
@article{arxiv.2306.12724,
title = {Distribution Network Fault Prediction Utilising Protection Relay Disturbance Recordings And Machine Learning},
author = {Ebrahim Balouji and Karl Bäckström and Viktor Olsson and Petri Hovila and Henry Niveri and Anna Kulmala and Ari Salo},
journal= {arXiv preprint arXiv:2306.12724},
year = {2023}
}