Risk Evaluation: Power System Induced Bush & Grass Fires and the Catastrophe Potential

Stillman R.H. and Darveniza M. (1991) Risk Evaluation: Power System Induced Bush & Grass Fires and the Catastrophe Potential. IEEE Transactions on Reliability, 40 3: 309-315. doi:10.1109/24.85448

Author Stillman R.H.
Darveniza M.
Title Risk Evaluation: Power System Induced Bush & Grass Fires and the Catastrophe Potential
Journal name IEEE Transactions on Reliability
ISSN 1558-1721
Publication date 1991-01-01
Sub-type Article (original research)
DOI 10.1109/24.85448
Open Access Status Not yet assessed
Volume 40
Issue 3
Start page 309
End page 315
Total pages 7
Language eng
Subject 2208 Electrical and Electronic Engineering
2213 Safety, Risk, Reliability and Quality
Abstract The paper outlines a modeling technique concerned with risk and failure of overhead power-distribution systems. This work examines the probabilistic low-order hazard of extreme consequence such as the grass & bush fires which engulfed southeastern Australia in 1983 February. The 3-part methodology is based on revision of probabilities derived from a line-fault database and the extremes of a Gumbel distribution. A risk-evaluation example of an actual event is included. The bushfire is an endemic part of the Australian climate (as is the case with southern California and the south of France). The movement of population and urbanisation have greatly exacerbated the consequences. Risk evaluation and the catastrophic event have to be seen in the context of the state of system repair, particularly for marginally operating, rural systems. The paper formulates a methodology for representing and analyzing the elements which combine to cause an overhead distribution system to breakdown and generate a risk situation. It is based on using data as they are normally reported in fault situations. The application of conditional probabilities to revise available data is based on making what appears to be a complicated problem solvable by dividing it into parts. That is, the initial discrete model is revised by weather weighting and a unique temperature. The outcome is then further revised by including locality, litigious claim, and catastrophe probabilities. Reader Aids - Purpose: Case history Special math needed for explanations: Conditional probability and Gumbel extreme-value statistics Special math needed to use results: None Results useful to: Power-distribution engineers and insurance-risk managers.
Keyword grass/bush Are
loss liability
power line
risk evaluation
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collection: Scopus Import - Archived
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 7 times in Scopus Article | Citations
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Created: Tue, 14 Jun 2016, 14:27:11 EST by System User