TY - GEN
T1 - Correlating Power Outage Spread with Infrastructure Interdependencies During Hurricanes
AU - Bose, Avishek
AU - Lee, Sangkeun
AU - Bhusal, Narayan
AU - Chinthavali, Supriya
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Power outages caused by extreme weather events, such as hurricanes, can significantly disrupt essential services and delay recovery efforts, underscoring the importance of enhancing our infrastructure's resilience. This study investigates the spread of power outages during hurricanes by analyzing the correlation between the network of critical infrastructure and outage propagation. We leveraged datasets from Hurricanemapping.com, the North American Energy Resilience Model Interdependency Analysis (NAERM-IA), and historical power outage data from the Oak Ridge National Laboratory (ORNL)'s EAGLE-I system. Our analysis reveals a consistent positive correlation between the extent of critical infrastructure components accessible within a certain number of steps (k-hop distance) from initial impact areas and the occurrence of power outages in broader regions. This insight suggests that understanding the interconnectedness among critical infrastructure elements is key to identifying areas indirectly affected by extreme weather events.
AB - Power outages caused by extreme weather events, such as hurricanes, can significantly disrupt essential services and delay recovery efforts, underscoring the importance of enhancing our infrastructure's resilience. This study investigates the spread of power outages during hurricanes by analyzing the correlation between the network of critical infrastructure and outage propagation. We leveraged datasets from Hurricanemapping.com, the North American Energy Resilience Model Interdependency Analysis (NAERM-IA), and historical power outage data from the Oak Ridge National Laboratory (ORNL)'s EAGLE-I system. Our analysis reveals a consistent positive correlation between the extent of critical infrastructure components accessible within a certain number of steps (k-hop distance) from initial impact areas and the occurrence of power outages in broader regions. This insight suggests that understanding the interconnectedness among critical infrastructure elements is key to identifying areas indirectly affected by extreme weather events.
KW - Correlation
KW - Critical infrastructure
KW - EAGLE-I
KW - Interdependency analysis
KW - Power out-age
UR - http://www.scopus.com/inward/record.url?scp=85207829395&partnerID=8YFLogxK
U2 - 10.1109/IRI62200.2024.00028
DO - 10.1109/IRI62200.2024.00028
M3 - Conference contribution
AN - SCOPUS:85207829395
T3 - Proceedings - 2024 IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2024
SP - 82
EP - 83
BT - Proceedings - 2024 IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2024
Y2 - 7 August 2024 through 9 August 2024
ER -