Analysis of Electrical Power and Oil and Gas Pipeline Failures
This paper examines the spatial and temporal distribution of failures in three critical infrastructure systems in the United States: the electrical power grid, hazardous liquids (including oil) pipelines, and natural gas pipelines. The analyses are carried out at the state level, though the analytical frameworks are applicable to other geographic areas and infrastructure types. The paper also discusses how understanding the spatial distribution of these failures can be used as an input into risk management policies to improve the performance of these systems, as well as for security and natural hazards mitigation.
Keywords: Electrical power, oil and gas pipelines, risk, count regression models
KeywordsPoisson Regression Model Poisson Random Variable Overhead Transmission Line Critical Infrastructure Protection Natural Hazard Mitigation
- Edison Electric Institute, Statistical Yearbook of the Electric Utility Indus- try, Edison Electric Institute, Washington, DC, 2003.Google Scholar
- North American Electric Reliability Council, Disturbance Analysis Work- ing Group (DAWG) Database, Princeton, New Jersey (www.nerc.com/dawg), 2006.
- Office of Pipeline Safety, Pipeline Statistics, Pipeline and Hazardous Material Safety Administration, U. S. Department of Transportation, Washington, DC (ops. dot. gov/stats/stats. htm), 2007.Google Scholar
- Pipeline and Hazardous Materials Safety Administration, Pipeline ba- sics, U. S. Department of Transportation, Washington, DC (primis. phmsa. dot. gov/comm/PipelineBasics. htm), 2006.Google Scholar
- C. Restrepo, J. Simonoff and R. Zimmerman, Unraveling geographic interdependencies in electric power infrastructure, Proceedings of the Thirty-Ninth Annual Hawaii International Conference on System Sciences, p. 248a, 2006.Google Scholar
- C. Restrepo, J. Simonoff and R. Zimmerman, Vulnerabilities in the oil and gas sector, presented at the First Annual IFIP WG 11. 10 International Conference on Critical Infrastructure Protection, 2007.Google Scholar
- J. Simonoff, Analyzing Categorical Data, Springer-Verlag, New York, 2003.  J. Simonoff, C. Restrepo and R. Zimmerman, Risk management and risk analysis-based decision tools for attacks on electric power, to appear in Risk Analysis, 2007.Google Scholar
- J. Simonoff, R. Zimmerman, C. Restrepo, N. Dooskin, R. Hartwell, J. Miller, W. Remington, L. Lave and R. Schuler, Electricity Case: Statistical Analysis of Electric Power Outages, Technical Report 05-013, Center for Risk and Economic Analysis of Terrorism Events, Los Angeles, California, 2005.Google Scholar
- U. S. Census Bureau, Table HS-1 -Population: 1900-2002, Statistical Ab- stract of the United States, U. S. Department of Commerce, Washington, DC, (www.census.gov/statab/hist/HS-01.pdf), 2003.
- U. S. Census Bureau, Table HS-43 -Energy supply and disposition by type of fuel: 1949-2002, Statistical Abstract of the United States, U. S. Depart-ment of Commerce, Washington, DC (www.census.gov/statab/hist/HS-43.pdf ), 2003.
- R. Zimmerman, Critical infrastructure and interdependency, in The McGraw-Hill Homeland Security Handbook, D. Kamien (Ed. ), McGrawHill, New York, pp. 523-545, 2006.Google Scholar
- R. Zimmerman, C. Restrepo, J. Simonoff and L. Lave, Risks and costs of a terrorist attack on the electricity system, in The Economic Costs and Consequences of Terrorism, H. Richardson, P. Gordon and J. Moore II (Eds. ), Edward Elgar, Cheltenham, United Kingdom, pp. 273-290, 2007.Google Scholar