Abstract
Fires initiated by powerline faults disproportionately are associated with a majority of bushfire fatalities in South-Eastern Australia. Over 150 deaths have occurred since 1977 in South-Eastern Australia. A response from governments and utilities has been to embark on electricity asset improvement and replacement programs where the definition of improvement is tied to an aim of reducing powerline sparked ignitions under the most dangerous meteorological conditions for fire. This paper introduces an optimization model which provides a strategy for adding technologies to powerline distribution assets such that there are improvements interms fire risk being lowered. The goal of the model is to minimize financial outlay while the risk of electricity sparked bushfire incidence is a solid constraint in the model, set to mimic potential bushfire risk reduction target scenarios. Currently, strategies for targeting investment in improvement of the electrical distribution system have not used such a mathematically based optimization approach. Instead they are based on expert interpretation of risk maps which visualize risk of fault of asset technologies with the consequence of fire starts at the same locations. Application of an optimization model by government and utilities when investing in powerline improvements could lead to reduced bushfire impacts within given funding frameworks relative to current practice. Estimated fault and fire ignition behavior of current and proposed electrical asset technology are a basis for our model. Fire mitigating treatments can range from the installation of new electrical fault detection systems at zone sub-stations; burying individual sections of powerline; installation of automatic circuit reclosers (ACRs); adjusting the settings on existing ACRs; insulating bare lines; etc. The work here represents a natural extension of bushfire risk-modelling work being undertaken by the authors in collaboration with the Victorian Government’s Powerline Bushfire Safety Program (PBSP).
Original language | English |
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Title of host publication | MODSIM2015, 21st International Congress on Modelling and Simulation |
Editors | Robert Anderssen, Tony Weber, Malcolm McPhee |
Place of Publication | Australia |
Publisher | Modelling and Simulation Society of Australia and New Zealand (MSSANZ) |
Pages | 1834-1840 |
Number of pages | 7 |
ISBN (Electronic) | 9780987214355 |
Publication status | Published - 2015 |
Externally published | Yes |
Event | International Congress on Modelling and Simulation 2015: Partnering with industry and the community for innovation and impact through modelling - Gold Coast Convention and Exhibition Centre, Broadbeach, Australia Duration: 29 Nov 2015 → 4 Dec 2015 Conference number: 21st https://www.mssanz.org.au/modsim2015/ |
Conference
Conference | International Congress on Modelling and Simulation 2015 |
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Abbreviated title | MODSIM2015 |
Country/Territory | Australia |
City | Broadbeach |
Period | 29/11/15 → 4/12/15 |
Other | The 21st International Congress on Modelling and Simulation (MODSIM2015) was held at the Gold Coast Convention and Exhibition Centre, Broadbeach, Queensland, Australia from Sunday 29 November to Friday 4 December 2015. It was held jointly with the 23rd National Conference of the Australian Society for Operations Research and the DSTO led Defence Operations Research Symposium (DORS 2015). The theme for this event was Partnering with industry and the community for innovation and impact through modelling. Papers from these proceedings should be cited using this format: Walmsley, B.J., Oddy, V.H., Gudex, B.W., Mayer, D.G. and McPhee, M.J. (2015). Transformation of the BeefSpecs fat calculator: Addressing eating quality and production efficiency with on-farm decision making. In Weber, T., McPhee, M.J. and Anderssen, R.S. (eds) MODSIM2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2015, pp. 490–496. ISBN: 978-0-9872143-5-5. www.mssanz.org.au/modsim2015/B4/walmsley.pdf |
Internet address |
Keywords
- Bushfire risk
- mixed-integer programming
- powerline safety
- combinatorial optimization