VISION Model : description of model used to estimate the impact of highway vehicle technologies and fuels on energy use and carbon emissions to 2050.

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The VISION model has been developed by the U.S. Department of Energy (DOE) to provide estimates of the potential energy use, oil use, and carbon emission impacts to 2050 of advanced light- and heavy-duty highway vehicle technologies and alternative fuels. DOE supports research of advanced transportation technologies (including fuels) and is frequently asked to provide estimates of the potential impacts of successful market penetration of these technologies, sometimes on a relatively quick-turnaround basis. VISION is a spreadsheet model in Microsoft Excel that can be used to respond rapidly to quick-turnaround requests, as well as for longer-term analyses. It uses vehicle ... continued below

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50 pages

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Singh, M.; Vyas, A. & Steiner, E. February 19, 2004.

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Description

The VISION model has been developed by the U.S. Department of Energy (DOE) to provide estimates of the potential energy use, oil use, and carbon emission impacts to 2050 of advanced light- and heavy-duty highway vehicle technologies and alternative fuels. DOE supports research of advanced transportation technologies (including fuels) and is frequently asked to provide estimates of the potential impacts of successful market penetration of these technologies, sometimes on a relatively quick-turnaround basis. VISION is a spreadsheet model in Microsoft Excel that can be used to respond rapidly to quick-turnaround requests, as well as for longer-term analyses. It uses vehicle survival and age-dependent usage characteristics to project total light and heavy vehicle stock, total vehicle miles of travel (VMT), and total energy use by technology and fuel type by year, given market penetration and vehicle energy efficiency assumptions developed exogenously. Total carbon emissions for on-highway vehicles by year are also estimated because life-cycle carbon coefficients for various fuels are included in VISION. VISION is not a substitute for the transportation component of the Energy Information Administration's (EIA's) National Energy Modeling System (NEMS). NEMS incorporates a consumer choice model to project market penetration of advanced vehicles and alternative fuels. The projections are made within the context of the entire U.S. economy. However, the NEMS model is difficult to use on a quick-turnaround basis and only makes projections to 2025. VISION complements NEMS with its relative ''user-friendliness'' and by extending the time frame of potential analysis. VISION has been used for a wide variety of purposes. For illustration, we have listed some of its most recent and current uses in Table 1.1. Figures 1.1-1.3 illustrate the results of some of those runs. These graphs are not actual model output, but they are based on model results. The main body of this report describes VISION's methodology and data sources. The methodology and data sources used in the light- and heavy-vehicle portions of the model are discussed separately. Some suggestions for future improvements to the model are made. Appendix A provides instructions on how to run the VISION model. Appendix B describes the procedure for updating the model with the latest EIA Annual Energy Outlook (AEO).

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50 pages

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  • Other Information: PBD: 19 Feb 2004

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  • Report No.: ANL/ESD/04-1
  • Grant Number: W-31-109-ENG-38
  • DOI: 10.2172/822561 | External Link
  • Office of Scientific & Technical Information Report Number: 822561
  • Archival Resource Key: ark:/67531/metadc787699

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  • February 19, 2004

Added to The UNT Digital Library

  • Dec. 3, 2015, 9:30 a.m.

Description Last Updated

  • March 24, 2016, 3:39 p.m.

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Singh, M.; Vyas, A. & Steiner, E. VISION Model : description of model used to estimate the impact of highway vehicle technologies and fuels on energy use and carbon emissions to 2050., report, February 19, 2004; Illinois. (digital.library.unt.edu/ark:/67531/metadc787699/: accessed September 24, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.