Understanding the exact fault location in the post-event analysis is the key to improving the accuracy of outage management. Unfortunately, the fault location is not generally well documented during the restoration process, creating a big challenge for post-event analysis. By utilizing various data source systems, including outage management system (OMS) data, asset geospatial information system (GIS) data, and vehicle location data, this paper creates a novel method to pinpoint the outage location accurately to create additional insights for distribution operations and performance teams during the post-event analysis.
@article{arxiv.2410.12056,
title = {Utilizing Spatiotemporal Data Analytics to Pinpoint Outage Location},
author = {Reddy Mandati and Po-Chen Chen and Vladyslav Anderson and Bishwa Sapkota and Michael Jarrell Warren and Bobby Besharati and Ankush Agarwal and Samuel Johnston},
journal= {arXiv preprint arXiv:2410.12056},
year = {2024}
}