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Factors influencing cost-effectiveness of maintenance of power distribution poles subjected to hurricanes: a system-dynamics-based analysis

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  • Jin Tian
  • Yue Li

Abstract

Based on a system dynamics (SD) model of long-term cost-effectiveness of power pole maintenance over 50 years, the influence of factors that affect cost-effectiveness was examined. Taking a typical region subjected to hurricanes (i.e., Miami-Dade County, USA) as a case, the SD model was established and tested with scenarios of power poles maintenance strategies. Factors such as wind speed variation (due to climate change), regional annual growth rate of the pole population, and discount rate were explored. It was shown that changing the parameters for these factors results in the following: The variation of wind speed due to climate change produces a negative impact on cost-effectiveness under the given replacement strategy; the factors of wind speed and annual growth rate of poles have a significant influence on the replacement ratio of poles particularly in the later period such as later 30 years; similarly, the discount rate has a marked impact on cumulative cost in the later decades. The difference between the contribution of factors is more significant in the later stages of the design life. The simulation results indicate how the change of these factors can lead to an impact on cost-effectiveness over time. The results have meaningful strategy implications, allowing an optimization of the timing of maintenance and a focus on different critical factors at various time periods. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Jin Tian & Yue Li, 2014. "Factors influencing cost-effectiveness of maintenance of power distribution poles subjected to hurricanes: a system-dynamics-based analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 72(2), pages 633-650, June.
    • Handle: RePEc:spr:nathaz:v:72:y:2014:i:2:p:633-650
    DOI: 10.1007/s11069-013-1023-1
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    References listed on IDEAS

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    1. Confalonieri, R. & Bellocchi, G. & Bregaglio, S. & Donatelli, M. & Acutis, M., 2010. "Comparison of sensitivity analysis techniques: A case study with the rice model WARM," Ecological Modelling, Elsevier, vol. 221(16), pages 1897-1906.
    2. Tong, Charles, 2010. "Self-validated variance-based methods for sensitivity analysis of model outputs," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 301-309.
    3. Han, Seung-Ryong & Guikema, Seth D. & Quiring, Steven M. & Lee, Kyung-Ho & Rosowsky, David & Davidson, Rachel A., 2009. "Estimating the spatial distribution of power outages during hurricanes in the Gulf coast region," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 199-210.
    4. Jin Tian & Yue Li, 2014. "System dynamics assessment of mitigation strategies for power distribution poles subjected to hurricanes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(2), pages 1263-1285, January.
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