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Identifying power outage hotspots to support risk management planning
Kaia Stødle1, Roger Flage1, Seth D Guikema2
1Department of Safety, Economics and Planning, University of Stavanger, Stavanger, Norway.
Summary
This study introduces a method to identify power outage hotspots using spatial statistics. This helps power utilities focus resources on problem areas for improved grid reliability.
Area of Science:
- Electrical Engineering
- Spatial Statistics
- Risk Management
Background:
- Reliable power systems are crucial for society and the economy.
- Existing research often focuses on predicting weather-related outages, neglecting recurring outage locations.
- Identifying power outage hotspots is essential for effective utility risk management.
Purpose of the Study:
- To adapt existing spatial statistics for identifying power outage hotspots.
- To provide a practical method for power utilities to pinpoint high-frequency outage locations.
- To support data-driven decisions for prioritizing grid maintenance and reinforcement.
Main Methods:
- Utilized Moran's I spatial statistic, specifically the local Moran's I.
- Calculated the statistic on a grid cell level for granular analysis.
- Applied a set of criteria to filter and confirm identified hotspot grid cells.
Main Results:
- Successfully adapted Moran's I to identify power outage hotspots using practical utility data.
- Demonstrated a method for pinpointing grid cells with statistically significant clusters of outages.
- Provided a clear, actionable approach for utilities to locate problematic system areas.
Conclusions:
- The adapted Moran's I statistic offers an accessible and effective tool for power outage hotspot identification.
- This method enables utilities to allocate resources more efficiently to critical areas.
- Prioritizing inspection and reinforcement of identified hotspots can enhance overall power system reliability and resilience.
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