In the next two decades, the U.S. refining industry will face significant changes resulting from a rapidly evolving domestic petroleum energy landscape. The rapid influx of domestically sourced tight light oil and relative demand shifts for gasoline and diesel will impose challenges on the ability of the U.S. refining industry to satisfy both demand and quality requirements. This study uses results from Linear Programming (LP) modeling data to examine the potential impacts of these changes on refinery, process unit, and product-specific efficiencies, focusing on current baseline efficiency values across 43 existing large U.S. refineries that are operating today. These results suggest that refinery and product-specific efficiency values are sensitive to crude quality, seasonal and regional factors, and refinery configuration and complexity, which are determined by final fuel specification requirements. Additional processing of domestically sourced tight light oil could marginally increase refinery efficiency, but these benefits could be offset by crude rebalancing. The dynamic relationship between efficiency and key parameters such as crude API gravity, sulfur content, heavy products, residual upgrading, and complexity are key to understanding possible future changes in refinery efficiency. Relative to gasoline, the efficiency of diesel production is highly variable, and is influenced by the number and severity of units required to produce diesel. To respond to future demand requirements, refiners will need to reduce the gasoline/diesel (G/D) production ratio, which will likely result in greater volumes of diesel being produced through less efficient pathways resulting in reduced efficiency, particularly on the marginal barrel of diesel. This decline in diesel efficiency could be offset by blending of Gas to Liquids (GTL) diesel, which could allow refiners to uplift intermediate fuel streams into more efficient diesel production pathways, thereby allowing for the efficient production of incremental barrels of diesel without added capital investment for the refiner. Given the current wide range of refinery carbon intensity values of baseline transportation fuels in LCA models, this study has shown that the determination of refinery, unit, and product efficiency values requires careful consideration in the context of specific transportation fuel GHG policy objectives.
[1]
Amgad Elgowainy,et al.
Energy efficiency and greenhouse gas emission intensity of petroleum products at U.S. refineries.
,
2014,
Environmental science & technology.
[2]
Sujit Das,et al.
Low-carbon fuel standard—Status and analytic issues
,
2010
.
[3]
N. Strachan,et al.
Critical mid-term uncertainties in long-term decarbonisation pathways
,
2012
.
[4]
Michael Wang,et al.
Allocation of energy use in petroleum refineries to petroleum products
,
2004
.
[5]
Will Usher,et al.
An expert elicitation of climate, energy and economic uncertainties
,
2013
.
[6]
Luis Pablo Dancuart,et al.
Fischer-Tropsch Based GTL Technology: a New Process?
,
2007
.
[7]
Andrew D. Jones,et al.
Supporting Online Material for: Ethanol Can Contribute To Energy and Environmental Goals
,
2006
.
[8]
Grant S Forman,et al.
Greenhouse Gas Emission Evaluation of the GTL Pathway.
,
2011,
Environmental science & technology.
[9]
Larry Bredeson,et al.
Factors driving refinery CO2 intensity, with allocation into products
,
2010
.
[10]
Jessica P. Abella,et al.
Model to investigate energy and greenhouse gas emissions implications of refining petroleum: impacts of crude quality and refinery configuration.
,
2012,
Environmental science & technology.
[11]
Michael Q. Wang,et al.
Well-to-Wheels Energy and Greenhouse Gas Emission Results and Issues of Fuel Ethanol
,
2008
.
[12]
R. Schnepf,et al.
Renewable Fuel Standard (Rfs): Overview and Issues
,
2012
.
[13]
Roberto Schaeffer,et al.
The energy efficiency of crude oil refining in Brazil: A Brazilian refinery plant case
,
2011
.
[14]
Hong Huo,et al.
Methods of dealing with co-products of biofuels in life-cycle analysis and consequent results within the U.S. context
,
2011
.