Advancing Hazard Assessment of Energy Accidents in the Natural Gas Sector with Rough Set Theory and Decision Rules

Marco Cinelli, Matteo Spada, Miłosz Kadziński, Grzegorz Miebs and Peter Burgherr
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Marco Cinelli: Future Resilient Systems (FRS), Swiss Federal Institute of Technology (ETH) Zürich, Singapore-ETH Centre (SEC), Singapore 138602, Singapore
Matteo Spada: Paul Scherrer Institut (PSI), Laboratory for Energy Systems Analysis, 5232 Villigen PSI, Switzerland
Miłosz Kadziński: Institute of Computing Science, Poznań University of Technology, 60-965 Poznań, Poland
Grzegorz Miebs: Institute of Computing Science, Poznań University of Technology, 60-965 Poznań, Poland
Peter Burgherr: Paul Scherrer Institut (PSI), Laboratory for Energy Systems Analysis, 5232 Villigen PSI, Switzerland

Energies, 2019, vol. 12, issue 21, 1-17

Abstract: The impacts of energy accidents are of primary interest for risk and resilience analysts, decision makers, and the general public. They can cause human health and environmental impacts, economic and societal losses, which justifies the interest in developing models to mitigate these adverse outcomes. We present a classification model for sorting energy accidents in the natural gas sector into hazard classes, according to their potential fatalities. The model is built on decision rules, which are knowledge blocks in the form of “if (condition), then (classification to hazard class x)”. They were extracted by the rough sets method using natural gas accident data from 1970–2016 of the Energy-related Severe Accident Database (ENSAD) of the Paul Scherrer Institut (PSI), the most authoritative information source for accidents in the energy sector. This was the first attempt to explore the relationships between the descriptors of energy accidents and the consequence (fatalities). The model was applied to a set of hypothetical accidents to show how the decision-making process could be supported when there is an interest in knowing which class (i.e., low, medium, high) of fatalities an energy accident could cause. The successful use of this approach in the natural gas sector proves that it can be also adapted for other energy chains, such as oil and coal.

Keywords: hazard assessment; energy accidents; decision support; rough sets; classification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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