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Development of Integrated Vehicle and Fuel Scenarios in a National Energy System Model for Low Carbon U.S. Transportation Futures

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  • Yang, Christopher
  • Zakerinia, Saleh
  • Ramea, Kalai
  • Miller, Marshall

Abstract

Transportation is a major emitter of greenhouse gas (GHG) emissions in the United States accounting for 27% of the country’s emissions, second only to the electricity sector. As a result, reducing GHG emissions are essential for mitigating some of the most damaging potential impacts associated with climate change and because of the importance and relative size of the transportation sector, it would need to contribute a significant amount of emissions reduction. This report describes the development and use of an U.S. energy system optimization model (US-TIMES) in order to analyze the reductions in GHG emissions that can come about through policy targets. These policy targets induce technology investments and operation in order to satisfy the demand for energy services and environmental policy constraints (notably GHG emission targets). The model development focused on two key areas within the transportation sector, light-duty vehicles and heavy-duty vehicles. In the light-duty space, we incorporated consumer choice elements into the energy system optimization framework through increasing consumer heterogeneity and adding non-monetary decision factors such as risk and fueling inconvenience. For heavy-duty vehicles, we adopt a segmentation approach and update vehicle cost and performance assumptions from our recent work. The model is used to project scenarios for low carbon futures from a reference scenario all the way to an 80% GHG reduction target. View the NCST Project Webpage

Suggested Citation

  • Yang, Christopher & Zakerinia, Saleh & Ramea, Kalai & Miller, Marshall, 2018. "Development of Integrated Vehicle and Fuel Scenarios in a National Energy System Model for Low Carbon U.S. Transportation Futures," Institute of Transportation Studies, Working Paper Series qt9cb5t3k4, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt9cb5t3k4
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    References listed on IDEAS

    as
    1. Ramea, Kalai & Bunch, David S. & Yang, Christopher & Yeh, Sonia & Ogden, Joan M., 2018. "Integration of behavioral effects from vehicle choice models into long-term energy systems optimization models," Energy Economics, Elsevier, vol. 74(C), pages 663-676.
    2. Yang, Christopher & Ogden, Joan M, 2007. "Determining the lowest-cost hydrogen delivery mode," Institute of Transportation Studies, Working Paper Series qt1804p4vw, Institute of Transportation Studies, UC Davis.
    3. DeCarolis, Joseph & Daly, Hannah & Dodds, Paul & Keppo, Ilkka & Li, Francis & McDowall, Will & Pye, Steve & Strachan, Neil & Trutnevyte, Evelina & Usher, Will & Winning, Matthew & Yeh, Sonia & Zeyring, 2017. "Formalizing best practice for energy system optimization modelling," Applied Energy, Elsevier, vol. 194(C), pages 184-198.
    4. Yang, Christopher & Ogden, Joan M, 2007. "Determining the lowest-cost hydrogen delivery mode," Institute of Transportation Studies, Working Paper Series qt7p3500g2, Institute of Transportation Studies, UC Davis.
    5. Yang, Christopher & Ogden, Joan M & Hwang, Roland & Sperling, Daniel, 2011. "California’s Energy Future: Transportation Energy Use in California," Institute of Transportation Studies, Working Paper Series qt70j8b21c, Institute of Transportation Studies, UC Davis.
    6. Yang, Christopher, 2011. "California’s Energy Future: Transportation Energy Use in California," Institute of Transportation Studies, Working Paper Series qt8j69x46d, Institute of Transportation Studies, UC Davis.
    7. Wilson, Deborah & Swisher, Joel, 1993. "Exploring the gap : Top-down versus bottom-up analyses of the cost of mitigating global warming," Energy Policy, Elsevier, vol. 21(3), pages 249-263, March.
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    10. Miller, Marshall & Wang, Qian & Fulton, Lew, 2017. "Truck Choice Modeling: Understanding California's Transition to Zero-Emission Vehicle Trucks Taking into Account Truck Technologies, Costs, and Fleet Decision Behavior," Institute of Transportation Studies, Working Paper Series qt1xt3k10x, Institute of Transportation Studies, UC Davis.
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