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Publication

Spatiotemporal Variability of Electric System Reliability Metrics

by Nagendra Singh, Olufemi A Omitaomu
Publication Type
Conference Paper
Book Title
UrbanAI '23: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI
Publication Date
Page Numbers
81 to 84
Issue
Urban-AI
Publisher Location
New York, New York, United States of America
Conference Name
UrbanAI '23: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI
Conference Location
Hamburg, Germany
Conference Sponsor
Apple
Conference Date
-

As urbanization continues to grow, urban density also rises, placing significant stress on critical infrastructure. Cities often face challenges in investing in new infrastructure or upgrading existing ones. One area of infrastructure that has come under strain is the electric grid, leading to prolonged power outages. According to data from the U.S. Energy Information Administration, the average duration of power outages has steadily doubled from 2013 to 2021, primarily due to extreme weather events. The IEEE has developed a series of reliability metrics to assess the reliability of the electric system. However, these metrics are only applied at the utility level, making it challenging to comprehend the variations in these indices at finer spatial resolutions and, consequently, evaluate reliability at the non-utility level. In this study, we leveraged electric outage data collected at 15-minute intervals at the county level to estimate electric system reliability over a six-year period using a novel data analysis approach. Our findings reveal a gradual decline in reliability in the U.S. Southwest compared to national averages. Furthermore, the duration of outages per customer per event has significantly decreased in large portions of California and Florida. These discoveries can be valuable for utility companies as they seek to pinpoint regional anomalies and plan for prioritized remediation efforts.