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Risk-management and risk-analysis-based decision tools for attacks on electric power.
Jeffrey S Simonoff1, Carlos E Restrepo, Rae Zimmerman
1Leonard N. Stern School of Business, New York University, New York, NY, USA.
Summary
Analyzing electric power grid disruptions from 1990-2004 using NERC data reveals patterns in outage frequency and duration. This informs risk management strategies for energy sector resilience against various threats, including terrorism.
Area of Science:
- Electrical Engineering
- Energy Systems Analysis
- Risk Management
Background:
- Electric power grid disruptions pose significant risks to energy sector stability and national security.
- Understanding historical incident data is crucial for developing effective risk management policies.
- The Disturbance Analysis Working Group (DAWG) database provides valuable insights into power system disturbances.
Purpose of the Study:
- To analyze historical electric power grid incident data from 1990-2004 in the US and Canada.
- To identify temporal and seasonal variations in power system disturbances.
- To investigate the relationship between outage characteristics (e.g., customer loss, duration) and disturbance factors.
Main Methods:
- Utilized the Disturbance Analysis Working Group (DAWG) database.
- Applied negative binomial regression, logistic regression, and weighted least squares regression.
- Analyzed incident data for trends over time and by season.
Main Results:
- Identified significant variations in power system disturbances over the 1990-2004 period.
- Quantified the relationship between outage characteristics and specific disturbance factors.
- Established a basis for understanding the dynamics of electric power outages.
Conclusions:
- Historical incident data offers critical inputs for energy sector risk management policies.
- The study provides a quantitative framework for assessing risks, consequences, and costs of power outages.
- Findings support the development of predictive models for estimating potential outcomes of grid disruptions.
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