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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20

Case Study - Propane School Bus Fleets

As part of the U.S. Department of Energy’s (DOE’s) effort to deploy transportation technologies that reduce U.S. dependence on imported petroleum, this study examines five school districts, one in Virginia and four in Texas, successful use of propane school buses. These school districts used school buses equipped with the newly developed liquid propane injection system that improves vehicle performance. Some of the school districts in this study saved nearly 50% on a cost per mile basis for fuel and maintenance relative to diesel. Using Argonne National Laboratory’s Alternative Fuel Life-Cycle Environmental and Economic Transportation (AFLEET) Tool developed for the DOE’s Clean Cities program to help Clean Cities stakeholders estimate petroleum use, greenhouse gas (GHG) emissions, air pollutant emissions and cost of ownership of light-duty and heavy-duty vehicles, the results showed payback period ranges from 3—8 years, recouping the incremental cost of the vehicles and infrastructure. Overall, fuel economy for these propane vehicles is close to that of displaced diesel vehicles, on an energy-equivalent basis. In addition, the 110 propane buses examined demonstrated petroleum displacement, 212,000 diesel gallon equivalents per year, and GHG benefits of 770 tons per year.

Alvin Independent School District↗

Deploying Electric Vehicles and Electric Vehicle Supply Equipment: Tiger Teams Offer Project Assistance for Federal Fleets

To assist federal agencies with the transition to plug-in electric vehicles (PEVs), including battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), FEMP offers technical guidance on electric vehicle supply equipment (EVSE) installations and site-specific planning through partnerships with the National Renewable Energy Laboratory’s EVSE Tiger Teams.

electric vehicle↗

Existing Plants – Fleet Assessment

Presented by NETL at 2019 Annual Project Review Meeting for Crosscutting, Rare Earth Elements, Gasification and Transformative Power Generation, 04/19

Existing Coal Fleet Electric Generating Units↗

Nth-plant supply: corn stover supplies and costs in a fleet of biorefineries

Feedstock cost and cost variability is expected to increase with the number of biorefineries. To quantify this effect, this spatial-economic analysis simulates feedstock cost and cost variability of an industry based on corn stover as a function of the number of biorefineries. Results are reported for nine scenarios (a base case and sensitivity analysis of four variables – harvest efficiency, sustainability constraints, opportunity cost, and corn grain yield) under deterministic and stochastic simulations, assuming biorefineries using 658 000 Mg (725 000 tons) year- 1 of corn stover in 2019. The resulting supply curves are highly elastic (i.e. little change in cost) for the first 50 of the 121 biorefineries, with price increases in subsequent biorefineries depending on scenario. In the base-case deterministic scenario, weighted-average stover costs are $66 Mg -1 ($60 ton- 1 ), $69 Mg -1 ($62 ton -1 ), and $156 Mg -1 ($142 ton -1 ), at the first, 60th, and 121st biorefineries, respectively. The stochastic simulations, subject to observed 30-year corn yield variability, follow a similar pattern, with price distributions that vary by scenario. The base-case stochastic simulations illustrate minimal cost variability for the first 60 biorefineries, but rapid increases in cost variability in the second half of potential biorefineries, with similar patterns observed in the other scenarios. Of the four variables explored, price was most sensitive to harvest efficiency, followed by sustainability constraints, corn yield, and opportunity cost. Results suggest that, under conventional logistics, about half of the US corn stover resource is reliably available with minimum cost increase and variability. Interactive visualization is available at https://doi.org/10.11578/1828779.

09 BIOMASS FUELS↗