Quantifying Cascading Impacts of Natural Hazards on Power-Communication Interdependent Networks

Extreme weather events increasingly threaten critical infrastructure (CI) systems, particularly power and telecommunication networks, leading to cascading failures. This paper proposes a novel resilience assessment framework that explicitly models spatial interdependencies between electricity and telecommunication networks using a graph-based approach. Sectorspecific metrics, including Demand Not Served (DNS), power line failure rates, and affected population estimates, quantify the impact of windstorm-induced disruptions. A spatiotemporal hazard scenario generator simulates realistic storm events, dynamically propagating failures through the coupled networks. A key innovation is the integration of a telecommunication signal propagation model-combining Extended Hata, Rapport models, and a binary search algorithm-to estimate coverage loss within the resilience framework. The framework is validated in Cyprus using real-world and synthetic data, identifying vulnerable regions and informing disaster response strategies.

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Publication Details

Published
2025-08-04
DOI
https://doi.org/10.1109/csr64739.2025.11130092
Citations
2
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
2.65

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article

Quantifying Cascading Impacts of Natural Hazards on Power-Communication Interdependent Networks

Mathaios Panteli, Christos Laoudias, Balaji V. Venkatasubramanian
2 citations
Complex Network Analysis Techniques
2.65
article

Quantifying Cascading Impacts of Natural Hazards on Power-Communication Interdependent Networks

Mathaios Panteli, Christos Laoudias, Balaji V. Venkatasubramanian
article en
2 citations

Abstract

Extreme weather events increasingly threaten critical infrastructure (CI) systems, particularly power and telecommunication networks, leading to cascading failures. This paper proposes a novel resilience assessment framework that explicitly models spatial interdependencies between electricity and telecommunication networks using a graph-based approach. Sectorspecific metrics, including Demand Not Served (DNS), power line failure rates, and affected population estimates, quantify the impact of windstorm-induced disruptions. A spatiotemporal hazard scenario generator simulates realistic storm events, dynamically propagating failures through the coupled networks. A key innovation is the integration of a telecommunication signal propagation model-combining Extended Hata, Rapport models, and a binary search algorithm-to estimate coverage loss within the resilience framework. The framework is validated in Cyprus using real-world and synthetic data, identifying vulnerable regions and informing disaster response strategies.

University of Cyprus (CY)
HORIZON EUROPE Framework Programme
Climate action
Openalex Percentile: Top 9%
Complex Network Analysis Techniques
2.65
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