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This content will become publicly available on June 22, 2026

Title: Spatiotemporal Multiplex Network Model for Predicting Forced Outage Severity in Distribution Grids
Weather-related power disruptions present significant challenges to public infrastructure, societal well-being, and the distribution grid. Predicting outage durations in distribution grids is another challenge compared to transmission line outage durations due to distribution networks’ complexity and finer granularity. While forecasting forced power outages is crucial, accurately estimating their duration is essential for timely response and mitigation measures. This study introduces the Spatiotemporal Multiplex Network (SMN-WVF), a methodology designed to predict power outage durations across varying lead times, tackling the difficulties posed by small, high-complexity spaces within distribution grids. SMN-WVF employs multiplex networks that incorporate multi-modal data across both time and space, including layers such as power outages, weather conditions, weather forecasts, vegetation, and distances between substations. We demonstrate the importance of incorporating additional layers of data sources as they are shown to help the model’s predictions through gradual improvement in the macro F1 score performance.  more » « less
Award ID(s):
2125985
PAR ID:
10625005
Author(s) / Creator(s):
; ; ; ; ;
Editor(s):
Iliadis, L; Maglogiannis, I; Kyriacou, E; Jayne, C
Publisher / Repository:
Springer Verlag
Date Published:
ISSN:
1860-9503
ISBN:
978-3-031-96198-4
Format(s):
Medium: X
Location:
the proceedings of the EAAAI / EANN 2025 conference
Sponsoring Org:
National Science Foundation
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