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Life cycle costing of diesel, natural gas, hybrid and hydrogen fuel cell bus systems: An Australian case study

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  • Ally, Jamie
  • Pryor, Trevor

Abstract

The transit authority in Perth, Western Australia, has put several alternative fuel buses, including diesel-electric hybrid and hydrogen fuel cell buses, into revenue service over the years alongside conventional diesel and natural gas buses. Primary data from this fleet is used to construct a Life Cycle Cost (LCC) model, providing an empirical LCC result. The model is then used to forecast possible scenarios using cost estimates for next generation technologies. The methodology follows the Australian/New Zealand Standard for Life Cycle Costing, AS/NZS 4536:1999. The model outputs a dollar value in real terms that represents the LCC of each bus transportation technology. The study finds that Diesel buses deliver the lowest Total Cost of Ownership (TCO). The diesel-electric hybrid bus was found to have a TCO that is about 10% higher than conventional diesel. The premium to implement and operate a hydrogen bus, even if industry targets are attained, is still substantially greater than the TCO of a conventional diesel bus, unless a very large increase in the diesel fuel price occurs. However, the hybrid and hydrogen technologies are still very young in comparison to diesel and economies of scale are yet to be realised.

Suggested Citation

  • Ally, Jamie & Pryor, Trevor, 2016. "Life cycle costing of diesel, natural gas, hybrid and hydrogen fuel cell bus systems: An Australian case study," Energy Policy, Elsevier, vol. 94(C), pages 285-294.
  • Handle: RePEc:eee:enepol:v:94:y:2016:i:c:p:285-294
    DOI: 10.1016/j.enpol.2016.03.039
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    References listed on IDEAS

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    1. Chen, Shikuan & Chang, Ming-Jen, 2015. "Capital control and exchange rate volatility," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 167-177.
    2. Li, Wu, 2015. "The Exchange Function and A Dynamic Exchange Model," MPRA Paper 68529, University Library of Munich, Germany.
    3. Colin J. Cockroft & Anthony D. Owen, 2007. "The Economics of Hydrogen Fuel Cell Buses," The Economic Record, The Economic Society of Australia, vol. 83(263), pages 359-370, December.
    4. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
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