NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

Optimizing Federal Fleet Vehicle 

Acquisitions: An Eleven-Agency 

FY 2012 Analysis

Mark Singer and Ryan Daley

Technical Report

NREL/TP-5400-62264

February 2015
NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

National Renewable Energy Laboratory

15013 Denver West Parkway

Golden, CO 80401

303-275-3000 • www.nrel.gov

Optimizing Federal Fleet Vehicle 

Acquisitions: An Eleven-Agency 

FY 2012 Analysis

Mark Singer and Ryan Daley

Prepared under Task No. 5400.2000

Technical Report

NREL/TP-5400-62264

February 2015
NOTICE

This report was prepared as an account of work sponsored by an agency of the United States government. 

Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, 

express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of 

any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately 

owned rights. Reference herein to any specific commercial product, process, or service by trade name, 

trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, 

or favoring by the United States government or any agency thereof. The views and opinions of authors

expressed herein do not necessarily state or reflect those of the United States government or any agency thereof.

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Available electronically at http://www.osti.gov/scitech

Available for a processing fee to U.S. Department of Energy

and its contractors, in paper, from:

U.S. Department of Energy

Office of Scientific and Technical Information

P.O. Box 62

Oak Ridge, TN 37831-0062

phone: 865.576.8401

fax: 865.576.5728

email: mailto:reports@adonis.osti.gov

Available for sale to the public, in paper, from:

U.S. Department of Commerce

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

phone: 800.553.6847

fax: 703.605.6900

email: orders@ntis.fedworld.gov

online ordering: http://www.ntis.gov/help/ordermethods.aspx

Cover Photos: (left to right) photo by Pat Corkery, NREL 16416, photo from SunEdison, NREL 17423, photo by Pat Corkery, NREL 

16560, photo by Dennis Schroeder, NREL 17613, photo by Dean Armstrong, NREL 17436, photo by Pat Corkery, NREL 17721.

NREL prints on paper that contains recycled content.
iii

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Acknowledgements

This work was supported by the U.S. Department of Energy’s (DOE) Federal Energy 

Management Program (FEMP). Additional support came from the National Renewable Energy 

Laboratory (NREL), a national laboratory of DOE’s Office of Energy Efficiency and Renewable 

Energy, operated by the Alliance for Sustainable Energy, LLC.

The authors would like to thank Mike Helwig for support in developing and updating the 

primary NOVA optimization code as well as providing expertise on how to make necessary 

updates and changes to assumptions and inputs. Additionally fleet subject matter experts at 

NREL including George Mitchell, Caley Johnson, John Gonzales, Navid Ahdieh, and Margo 

Melendez provided helpful insights for the construction of model assumptions and calculations. 

Witt Sparks was helpful in the development of key data inputs.

The authors would like to specifically thank Mark Reichhardt, Brad Gustafson, and Amanda 

Sahl from the Sustainable Federal Fleets program at FEMP, and Robert Westby, FEMP Program 

Manager at NREL, without whom the data and resources necessary for this research would not 

be available.

All judgments in the final analytic methodologies and interpretations are the responsibility of the 

authors and not of the experts acknowledged above.
iv

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Acronyms

AFV alternative fuel vehicle

BEV battery-electric vehicle

B100 pure biodiesel

CNG compressed natural gas

DOE U.S. Department of Energy 

ECRA Energy Conservation and Reauthorization Act

EISA Energy Independence and Security Act

EPAct Energy Policy Act

EV electric vehicle

FEMP Federal Energy Management Program

FFV flex-fuel vehicle

FSR Field Service Representative

FY fiscal year

GGE gasoline gallon equivalent

GHG greenhouse gas

GSA General Services Administration

GVWR gross vehicle weight rating

HEV hybrid electric vehicles

LDV light-duty vehicles

MCDM multi-criteria decision making

MPGGE miles per gasoline gallon equivalent

NDAA National Defense Authorization Act

NOVA NREL Optimal Vehicle Acquisition

NREL National Renewable Energy Laboratory

PHEV plug-in hybrid electric vehicles

SSPP Strategic Sustainability Performance Plan

VAM Vehicle Allocation Methodology

VMT vehicle miles traveled
v

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Executive Summary

Over the past two decades, numerous mandates focusing on environmental sustainability and 

energy management in federal fleets have created a complex regulatory landscape. It has proven 

challenging for federal fleet managers to effectively prioritize and make progress toward these 

mandated goals. This is particularly true when considering that the primary task of federal fleet 

managers is to ensure that the fleet meets the mission objectives of their agency and that a 

smaller fraction of fleet manager time is spent on achieving mandates.

Prior research has identified methodologies and tools to help managers efficiently prioritize and 

understand tradeoffs between different mandate attainment strategies. The vehicle acquisition 

process has been a particular focus of prior investigations as it is a key decision point with a high 

impact on the ability of fleets to meet mandates. This report focuses on a fiscal year (FY) 2012 

effort that used the NREL Optimal Vehicle Acquisition (NOVA) analysis to identify optimal 

vehicle acquisition recommendations for eleven diverse federal agencies. The recommendations

were completed in time to inform the agencies’ final FY 2013 vehicle acquisition plans. In this 

way, the effort showed that the theoretical benefits of a vehicle acquisition optimization effort 

could be applied during the ordering cycle.

Results of the study show that by following a vehicle acquisition plan that maximizes the 

reduction in greenhouse gas (GHG) emissions, significant progress is also made toward the 

mandated complementary goals of petroleum use reduction and alternative fuel use increase. In 

addition to the specific vehicle recommendations, results showed that agencies could benefit 

from more generalized guidance of:

1. Targeting flex-fuel vehicles (FFVs) in locations where E85 is available

2. Targeting hybrid electric vehicles (HEVs) when budget allows, where E85 is not 

available, and when driving routes involve stopping and starting that enables HEVs to 

achieve their full fuel economy benefit.

3. Targeting the most efficient conventional gasoline vehicles or FFVs available where E85 

is not available and the budget is constrained.

Following the specific vehicle recommendations proved challenging for the agencies. Fleet 

organization structures, mission nuances, and user preferences were found to vary widely among 

fleets from the national to the local levels. Additionally the General Services Administration 

(GSA) has to manage its own constraints and is not always able to deliver specific vehicle makes 

and models in the exact numbers chosen by the model. Efforts that take into account the varied 

organizational structures of federal fleets and the constraints on vehicle availability from GSA 

would have a greater potential to positively affect fleet performance toward mandated goals. In 

addition, future studies supporting the federal fleet ordering process would benefit from an effort to 

define vehicle capability standards precise enough to ensure that replacement recommendations 

meet highly specific mission requirements.
vi

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table of Contents

1 Introduction........................................................................................................................................... 1

2 Background........................................................................................................................................... 2

2.1 History of Federal Fleet Regulations............................................................................................. 2

2.2 Reduce GHG Emissions................................................................................................................ 3

2.3 Vehicle Acquisition....................................................................................................................... 4

2.4 Federal Fleet Mandate Performance.............................................................................................. 5

2.5 Fleet Management Operations and Organizations ........................................................................ 7

2.6 GSA Leased Vehicle Ordering Process......................................................................................... 8

2.7 Technical Assistance Offer from the DOE Federal Energy Management Program.................... 10

3 Methodology: Model Structure and Assumptions .......................................................................... 11

3.1 NOVA Analysis Description....................................................................................................... 11

3.2 Model Calculations ..................................................................................................................... 11

3.3 Vehicle Availability .................................................................................................................... 11

3.4 Vehicle Geography...................................................................................................................... 12

3.5 Annual Vehicle Fuel Consumption ............................................................................................. 13

3.6 Percentage of Alternative Fuel Use............................................................................................. 14

3.7 GHG Emissions........................................................................................................................... 14

3.8 AFV Incremental Budget ............................................................................................................ 16

3.9 Acquisition Mandates in the Model ............................................................................................ 17

4 Model Development............................................................................................................................ 18

4.1 Optimization Model Indices........................................................................................................ 18

4.2 Optimization Model Decision Variable ...................................................................................... 18

4.3 Optimization Model Definitions ................................................................................................. 18

4.4 Optimization Model Constraints................................................................................................. 19

4.5 Optimization Model Objective Function..................................................................................... 19

5 Model Runs and Results.................................................................................................................... 21

5.1 Optimization Model Results........................................................................................................ 21

5.2 Vehicle Technology Comparisons .............................................................................................. 23

5.3 Estimated Impacts of Recommendations.................................................................................... 24

5.4 Sources of Impact........................................................................................................................ 27

6 Conclusions ........................................................................................................................................ 30

7 References .......................................................................................................................................... 31

Appendix A. Federal Fleet Requirements............................................................................................... 32
vii

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

List of Figures

Figure 1. Organization of mandates.............................................................................................................. 3

Figure 2. Acquisition credits......................................................................................................................... 5

Figure 3. Federal fleet vehicles..................................................................................................................... 6

Figure 4. Fleet fuel consumption .................................................................................................................. 7

Figure 5. Fleet vehicles by ownership versus leased .................................................................................... 9

Figure 6. Sedan fuel consumption comparisons ......................................................................................... 23

Figure 7. Sedan GHG emissions comparisons............................................................................................ 24

Figure 8. Sources of petroleum reduction................................................................................................... 28

Figure 9. Sources of petroleum reduction by agency.................................................................................. 29

List of Tables

Table 1. CO2 Emissions Factors by Fuel Type ........................................................................................... 15

Table 2. CH4 and N2O Emissions Factors by Fuel Type ............................................................................ 15

Table 3. GGE Conversion Factors by Fuel Type........................................................................................ 16

Table 4. Agency AFV Surcharges .............................................................................................................. 17

Table 5. FY 2012 GSA Leased Vehicle Inventories and Recommendations ............................................. 21

Table 6. NOVA Recommendations by Vehicle Fuel Type......................................................................... 22

Table 7. Estimates of Petroleum Reduction................................................................................................ 25

Table 8. Estimates of GHG Emissions Reduction ...................................................................................... 25

Table 9. Estimates of Alternative Fuel Increase ......................................................................................... 26

Table 10. Partial Fleet Replacement Petroleum Reduction ........................................................................ 27

Table 11. Summary of Primary and Supporting Federal Fleet Requirements............................................ 32
1

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

1 Introduction

Beginning with alternative fuel vehicle (AFV) acquisition requirements in The Energy Policy Act 

of 1992 (EPAct 1992), numerous mandates have focused on energy management of the federal

fleet during the past two decades. This has created a complex regulatory landscape where 

achieving compliance must be balanced with a wide variety of agency mission objectives and 

operational needs, organizational structures, and budgets. The combination of competing 

regulatory and operational priorities during the vehicle acquisition process make it challenging for 

federal fleet managers to make progress toward the goals of alternative fuel and advanced vehicle 

technology deployment, energy security, environmental sustainability, and cost savings.

This paper discusses the results of a fiscal year (FY) 2012 study to support the vehicle 

acquisition process for eleven federal agencies. Using the NREL Optimal Vehicle Acquisition 

(NOVA) analysis, the study produced specific, individual vehicle recommendations determined 

by integer optimization models for each agency, in consideration of the wide array of competing 

acquisition requirements for these fleets. Development and use of the NOVA analysis expands 

on previous work by Helwig and Deason (2007) and Deason and Jefferson (2010). 

The General Services Administration (GSA) manages 

standardized data for all vehicles leased through GSA 

by federal agencies. We drew from these GSA leased 

vehicle data sets to feed the NOVA models for a 

diverse group of eleven agencies. Running analyses for 

each agency based on standard data allowed us to 

consider the nuances of each specific agency, arrive at 

conclusions that cross all the agencies, and show the 

scale of impact an optimization effort can have in the 

federal fleet. Yet the benefits of any optimization effort 

are inherently dependent on the strict enforcement of the outputs generated – any deviation from 

that output necessarily constitutes a suboptimal implementation.

In order for mandates to have the intended impact, they must account for the context in which the 

fleets operate. Accordingly, we also discuss the setting in which fleet managers approach the 

vehicle ordering process: we estimated the theoretical impacts of the optimized 

recommendations on mandated goals, but the actual impacts are difficult to predict primarily due 

to variances across and within agencies related to (1) specific mission requirements and (2) 

centralization or de-centralization of decision-making authority. These factors contributed to 

numerous instances where the ‘optimized’ acquisition recommendations likely were not chosen 

to be followed. These hurdles could be overcome if more specific mission requirements could be 

defined, as the model can handle the more detailed requirements, and if agencies chose to have a 

more centralized vehicle acquisition process. Applied use of optimization models in federal

fleets shows significant benefits are possible, but fleet managers face challenging operational 

hurdles in achieving the theoretical improvements that the models predict.

Benefits of a NOVA Analysis

• Maximize budget: Get a more 

efficient fleet for your money

• Minimize waste: Place the 

optimal vehicle at the optimal 

location

• Achieve targets: Efficiently plan 

for compliance.
2

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

2 Background

2.1 History of Federal Fleet Regulations

Federal fleets are looked upon to be leaders in fleet energy management. Because of this, there have 

been numerous legislative and executive efforts to support the implementation of alternative fuel and 

advanced vehicle technology, energy security, and environmental sustainability. The U.S. 

Department of Energy (DOE) (2010, 2011), as well as Deason and Jefferson (2010), provide a 

comprehensive overview of these regulations and their applicability to federal agencies. Table 11 in 

appendix A as adapted from DOE (2010) provides a brief overview of these requirements and covers 

the following statutes and Executive Orders (EOs): 

• EPAct 1992, as amended by the Energy Conservation and Reauthorization Act (ECRA) 

of 1998 and Section 2862 of the National Defense Authorization Act (NDAA) of 2008

• The Energy Policy Act of 2005 (EPAct 2005)

• E.O. 13423 Strengthening Federal Environmental, Energy, and Transportation 

Management, signed on January 24, 2007

• Energy Independence and Security Act (EISA) of 2007

• E.O. 13514, Federal Leadership in Environmental, Energy, and Economic Performance, 

signed on October 5, 2009.

While each of these regulations and specific mandates broadly share a sustainability focus, 

progress toward one mandated goal did not guarantee success amongst the others. This made for 

a complex environment for fleet managers that also had to consider fleet mission objectives and 

budgets. Without clear direction, fleet managers individually had to weigh the relative 

importance of mandates and accept the tradeoffs for prioritizing one over another. Deason and 

Jefferson (2010) as well as Helwig and Deason (2007), have shown that fleet manager opinions 

have varied widely on the relative importance of mandated objectives. In an effort to support 

fleet manager decision-making, Deason and Jefferson (2010) developed a multi-criteria decision 

making (MCDM) approach to help fleet managers weigh the perceived importance of mandates 

and help them create structured fleet management strategies.

In this complex setting, E.O. 13514, Federal Leadership in Environmental, Energy, and Economic 

Performance, signed on October 5, 2009, established “an integrated strategy toward sustainability 

in the federal government and makes reduction of greenhouse gas (GHG) emissions a priority for 

federal agencies.” Additionally E.O. 13514 required DOE to issue comprehensive guidance on 

sustainability in the federal fleet in coordination with GSA – Guidance for Federal Agencies on 

E.O. 13514, Section 12, Federal Fleet Management (DOE, 2010) and Comprehensive Federal 

Fleet Management Handbook (DOE 2014)

1 fulfilled this requirement. 

Through these documents, DOE has established a de facto prioritization of federal fleet 

sustainability mandates where reducing GHG emissions is the top priority and reducing petroleum 

consumption is the primary mechanism to achieve this goal; the remaining mandates support this 

overarching metric. Figure 1 (DOE 2014) summarizes the organization of these mandates. 

 1 FEMP’s Comprehensive Federal Fleet Management Handbook was originally published in 2011 and last updated in 

2014.
3

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 1. Organization of mandates

In accordance with the direction of E.O. 13514 and the framework developed by DOE, the study 

discussed in this paper prioritized reducing GHG emissions.

2.2 Reduce GHG Emissions

E.O. 13514 required federal agencies to establish aggressive targets for reducing GHG emissions 

throughout the operation of the federal government by January 4, 2010. GHG emissions are split 

into three source categories, or “scopes” (White House 2010):

• Scope 1 includes GHG emissions from sources owned or controlled by a federal agency: 

vehicles and equipment, stationary combustion for buildings, on-site landfills and 

wastewater treatment, and fugitive emissions. 

• Scope 2 includes GHG emissions from electricity, heat, or steam purchased by federal

agencies; includes electricity used in the operation of Electric Vehicles (EVs). 

• Scope 3 includes GHGs from sources not directly owned or controlled by federal entities 

(e.g., business travel, employee commuting, contracted waste disposal, etc.). 

GHG emission reduction requirements for federal fleet vehicles fall under both Scope 1 and 

Scope 2 emissions. 

E.O. 13514 further required agencies to establish baseline inventories of GHG emissions based 

on FY 2008 operations, establish organizational GHG reduction targets, create (and update 

annually) a Strategic Sustainability Performance Plan (SSPP)2

, and report GHG emissions 

annually (White House 2012). E.O. 13514 touched on agency vehicle acquisition efforts in 

 2 Federal agency SSPPs are available through the White House at http://archive-sustainability.performance.gov/. 
4

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Section 2(a) iii, Goals for Agencies, which requires the head of each agency to consider reducing 

the use of fossil fuels by (White House 2009): 

A. Using low GHG-emitting vehicles and AFVs.

B. Optimizing the number of vehicles in the agency fleet

C. Reducing, if the agency operates a fleet of at least 20 motor vehicles, the agency fleet’s 

total consumption of petroleum fuel by a minimum of 2 percent annually through the end 

of FY 2020, relative to a baseline of FY 2005.

2.3 Vehicle Acquisition

The acquisition of new fleet vehicles is an operational effort that plays a critical role in the 

federal fleet’s ability to meet sustainability mandates; it is the primary focus of this study. The 

following regulations cover the acquisition of vehicles in the federal fleet: 

• EPAct 1992 requires that 75% of all light-duty vehicles (LDV) acquired in metropolitan 

statistical areas (MSA) must be AFVs. 

• ECRA 1998 states that for every 450 gallons of pure biodiesel (B100) used in agency 

fleets received a credit equal to one AFV acquisition. 

• NDAA 2008 added hybrid electric vehicles (HEV) to the definition of an AFV, and “any 

other type of vehicle that EPA demonstrates to DOE would achieve a significant 

reduction in petroleum consumption” (DOE 2014). 

• EISA 2007 requires agencies to acquire only low-GHG emitting vehicles; “...any low GHGemitting vehicle acquired in lieu of a [Flex Fuel Vehicle (FFV)] that an agency reasonably 

determines qualifies for a fuel waiver under EPAct 2005 § 701 is now included in the 

expanded definition of an AFV” (EPA 2012).

• E.O. 13423 requires the acquisition of plug-in hybrid electric vehicles (PHEVs) when 

they are commercially available at costs reasonably comparable to non-PHEVs. 

While the focus of this study touches on all of these requirements, it is more specifically concerned 

with acquiring the appropriate AFVs in locations where agencies can reap the most benefit from a 

particular technology. Acquiring the appropriate AFVs in optimal locations sets agencies up to 

achieve the overarching goals of GHG emission reductions, petroleum reduction, and alternative fuel 

use over the lifetime of their vehicles. Conversely, suboptimal vehicle acquisitions can impede a 

fleet’s ability to meet sustainability mandates and lead to unnecessary costs for agencies operating 

under highly scrutinized and constrained budgets. 

Helwig and Deason (2007) noted the lack of a requirement to actually use alternative fuel in 

federal AFVs as a core deficiency of EPAct 1992. This shortcoming was first remedied via

E.O. 13149, Greening the Government through Federal Fleet and Transportation Efficiency, and 

subsequently addressed in Section 701 of EPAct 2005. Section 701 requires that all dual-fueled 

AFVs in the federal fleet only be operated on alternative fuel unless they received a waiver from 

this requirement through DOE if (1) alternative fuel is not reasonably available within 5 miles or 
5

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

a 15-minute drive from the vehicle’s garage location, or (2) alternative fuel is unreasonably more 

expensive than gasoline (DOE, 2011). 

In addition to Section 701, the Presidential Memorandum − Federal Fleet Performance was 

issued on May 24, 2011. This memo requires federal agencies to complete an annual Vehicle 

Allocation Methodology (VAM), which was developed and distributed to the fleets through 

GSA. In addition, “by December 31, 2015, all new light-duty vehicles leased or purchased by 

agencies must be alternative fueled vehicles, such as hybrid or electric, compressed natural gas, 

or biofuel. Moreover, agency alternative fueled vehicles must, as soon as practicable, be located 

in proximity to fueling stations with available alternative fuels, and be operated on the alternative 

fuel for which the vehicle is designed. Where practicable, agencies should encourage 

development of commercial infrastructure for alternative fuel or provide flex fuel and alternative 

fuel pumps and charging stations at federal fueling sites” (White House 2011). 

While the passage of requirements to use alternative fuel has addressed some of the initial 

shortcomings of EPAct 1992, underuse of alternative fuel and the suboptimal placement of AFV 

technologies continue to hamper federal fleet efforts to reduce GHG emissions and petroleum use. 

2.4 Federal Fleet Mandate Performance

The federal fleet has exceled in meeting the EPAct 1992 AFV acquisition requirement in recent 

years as can be seen in Figure 2.

Figure 2. Acquisition credits3

Further, Figure 3 shows the federal fleet has consistently increased the portion of the fleet that is 

comprised of AFVs. In 2012, this AFV percentage reached 33 percent. 

 3 http://federalfleets.energy.gov/performance_data/afv_acquisition_compliance. Accessed May 20, 2014.
6

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 4 shows that petroleum consumption has slightly increased since 2000. During the same 

time period, the percentage of total fuel use that is alternative fuel has steadily increased, but the 

percentage remains relatively low. 

There are multiple reasons for the stark difference between the percentage of the fleet that is 

comprised of AFVs and the percentage of fuel use that is alternative fuel. Daley (2014) 

investigated federal fleet fueling behavior and found that drivers consistently miss opportunities 

to use available alternative fuel. Additionally, AFVs have not always been located where they 

have access to alternative fuel infrastructure. The challenge of better locating AFVs is a focus of 

the study that follows.

Figure 3. Federal fleet vehicles4

 4 http://federalfleets.energy.gov/sites/default/files/static_page_docs/ff3_vehicles_fuel_type_FY12.xls. Accessed 

May 20, 2014.
7

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 4. Fleet fuel consumption5

2.5 Fleet Management Operations and Organizations

Fleet operations across the federal government include management of vehicle inventories to 

efficiently meet agency mission objectives, maintenance of the vehicles, and acquisition and 

disposal of vehicles. 

In comparison to private fleets that may support a relatively consistent function across an 

organization, federal fleets were found to support highly diverse mission requirements including:

• Passenger and cargo transport

• Low and high passenger-count transport

• Short distance and long-haul transport

• Rural, suburban, and urban transport

• On-road and off-road transport

• Highly routinized and highly irregular transport

• Mobile workstation transport.

Federal fleet missions are not entirely static and can expand and change. These changes are the 

consequence of shifting agency responsibilities due to specific legislative and executive actions 

 5 http://federalfleets.energy.gov/sites/default/files/static_page_docs/ff9_covered_petro_alt_fuel_FY13.xlsx.

Accessed May 20, 2014.
8

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

such as increased border security in response to national security needs or increased military 

activity in a time of war. Missions can also change as a consequence of providing services to a 

population with growing and shifting demographics, including a growing elderly population, a 

growing number of veterans returning from war, and a growing public population in general. 

Federal fleets may also encounter significant unscheduled mission requirements such as 

responding to natural disasters. Fleet missions can also often shrink over time as funding 

priorities change. 

Federal fleet managers work to meet requirements within a variety of organizational structures.

These structures can be highly centralized where national fleet management has visibility into 

operations through mid-levels and down to the local level. Mid-level and local fleet managers are 

accountable to the national management in these centralized structures. Alternatively, fleet 

management can often be highly decentralized where national fleet managers have little visibility 

into specific fleet operations. Mid-level and local fleet managers operate with a high degree of 

autonomy and have only cursory reporting requirements to higher levels in decentralized structures. 

Many federal fleets fall somewhere between the extremes of a highly centralized or highly 

decentralized structure. 

It is within this operational setting that fleet managers often spend only a fraction of their time 

working to meet fleet sustainability mandates. The importance placed on meeting mandates 

varies across fleets. Those agencies that have chosen a more centralized organizational structure 

and have high level leadership focused on successfully meeting mandates tend to more 

aggressively pursue results. 

2.6 GSA Leased Vehicle Ordering Process

Our study supporting the eleven federal agencies in FY 2012 focused on the GSA-leased portion 

of the fleets. Federal fleets are able to acquire vehicles by purchasing them directly through 

GSA, leasing them though GSA, or leasing them through commercial vendors. In FY 2012, as 

Figure 5 shows, 30 percent of all federal vehicles were GSA leased vehicles. 
9

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 5. Fleet vehicles by ownership versus leased 

Source: Federal Automotive Statistical Tool (FAST)

As a matter of scale and complexity, a single federal agency may manage between a couple 

dozen to more than 50,000 GSA-leased vehicles. Each year the GSA offers hundreds of lease 

vehicle models to choose from. Fleets may acquire and manage vehicles for locations numbering 

five or less to thousands across the country.

The GSA-leased vehicle ordering process is somewhat different for every agency and, in part, is a 

product of the individual agency organizational structure. Headquarters national fleet managers for 

each agency work with the GSA Fleet central office to set high level goals for a particular acquisition 

cycle. Local level fleet managers across the country work with their GSA Field Service 

Representatives (FSRs). Both the agencies and GSA have mid-level region or other organizational 

management levels that coordinate between the national and local levels.

The vehicle ordering timeline fluctuates, but generally begins late in the summer months when 

GSA identifies current agency vehicles as replacement-eligible. Local level fleet management 

works with their FSRs throughout the fall months to submit orders to GSA. Agency national 

management is able to review and change orders until orders are finalized in December or 

January. GSA then delivers newly leased vehicles throughout the year. 

National fleet management in centralized fleet organizations will set goals for the fleet as a 

whole and distribute specific vehicle recommendations or generalized guidance to local fleet 

managers. Local fleet managers that wish to deviate from the national direction may then work 

within a defined structure to request an exception from higher-level management. Mid-level or 

national management closely review final vehicle orders prior to submittal to GSA.
10

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Local fleet managers in decentralized agencies may receive general guidance from national 

management, but in practice have a great degree of freedom in the ordering process. National 

managers in this structure may or may not have timely and readily available visibility into the 

local vehicle ordering process. National managers that are able to review orders may not be in a 

position to change the orders prior to their submittal to the GSA. 

GSA plays a vital customer service role throughout the ordering process, working to ensure that 

an agency receives their requested vehicles to meet mission requirements. However, GSA must 

balance the desires of fleet managers across the federal government, contract with vehicle 

manufacturers to provide the appropriate vehicles, and work within the constraints of its own 

operating environment. In some instances GSA may not be able to provide specified vehicle 

makes and models in the quantities requested by the agencies at every location. While GSA is 

highly supportive of agency efforts to achieve mandated sustainability goals, it is ultimately up 

to each agency management structure to determine the best way to reach those goals.

2.7 Technical Assistance Offer from the DOE Federal Energy 

Management Program 

DOE is required by law to provide support to agencies during the vehicle acquisition process 

under EPAct 1992 § 305. Specifically, DOE is directed to “... provide guidance, coordination 

and technical assistance to federal agencies in the procurement and geographic location of 

alternative fueled vehicles purchased through the Administrator of General Services.” Under this 

direction and in direct response to the May 24, 2011, Presidential Memorandum – Federal Fleet 

Performance, the DOE Federal Energy Management Program (FEMP) offered assistance to all 

federal fleets, and ultimately supported eleven fleets in FY 2012 by providing the NOVA 

analyses during the planning and execution of the GSA-leased vehicle acquisition process. GSA 

leased vehicles were the focus of this study due to the readily available and consistent datasets 

for GSA-leased vehicles across all agencies. These datasets are not always available for those 

portions of the federal fleet that are owned or commercially leased by the agencies.

The 2012 support provided agencies with specific optimal vehicle recommendations for each 

vehicle in the agency inventory prior to the beginning of the ordering cycle and the 

determination of the specific vehicles eligible for replacement. The intent of the 

recommendations was to help agency fleet managers make more informed decisions about how 

best to achieve sustainability goals during the vehicle ordering process. It was up to the national 

agency fleet managers to use and distribute the recommendations in their organization as they 

saw best prior to and during the ordering process.
11

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

3 Methodology: Model Structure and Assumptions

3.1 NOVA Analysis Description

NOVA analyses rely on a series of integer optimization models initially created by Dr. Michael 

Helwig (Helwig and Deason 2007) and further developed at the National Renewable Energy 

Laboratory (NREL). NOVA models consider an existing inventory of vehicles and determine a 

set of replacement vehicles that will achieve a specified optimal goal while considering fleet 

constraints, including vehicle locations, alternative fuel vehicle budgets, and compliance with 

fleet mandates.

As discussed earlier, DOE established that the reduction of GHG emissions is the primary fleet 

sustainability objective since the signing of E.O. 13514. In accordance with this prioritization, 

the NOVA model used for the FY 2012 study determines the set of replacement vehicles that 

maximizes the reduction in GHG emissions in comparison to the existing inventory while 

considering fleet constraints. The model results show significant progress is made toward the 

complementary goals of petroleum use reduction and alternative fuel use increase. This is due to 

the fact that GHG emissions from the federal fleet are primarily the result of burning traditional 

petroleum fuels (i.e., gasoline and diesel). The combination of using more efficient vehicles that 

burn less fuel in total and using more alternative fuels that emit fewer GHG emissions achieves 

the overall goal of reducing fleet GHG emissions.

3.2 Model Calculations

At a high level, the NOVA model calculates the estimated annual fuel consumption for each 

vehicle in the inventory and each replacement vehicle option. The fuel consumption estimates 

are then converted to GHG emissions estimates. The model compares these estimated values for 

the replacement vehicle options and determines the set of replacement vehicles that will 

maximize the reduction of GHG emissions for the inventory in total while staying under budget 

and within other model constraints.

3.3 Vehicle Availability

The primary inputs to the model are the agency’s existing GSA-leased vehicle inventory and the 

list of vehicles available for lease to the agency from the GSA. The existing inventory vehicles 

are segmented into four primary vehicle types including sedan, pick-up, van, and SUV. The 

model primarily considers the light-duty (gross vehicle weight rating (GVWR) less than 8,500 

lbs.) portions of the fleets because these vehicles have readily available fuel economy ratings by 

each vehicle make and model that allow for vehicle fuel consumption comparisons – the 

assumptions for vehicle fuel consumption is detailed below.

A portion of each fleet did not receive specific vehicle recommendations. These vehicles included 

special use vehicles, such as emergency response or law enforcement vehicles, as well as larger 

medium-duty (8,500 – 10,000 lbs. GVWR) and heavy-duty vehicles (greater than 10,000 lbs. 

GVWR). These vehicles did not have available replacement options with specific make and model 

fuel economy ratings. The general acquisition guidance provided for replacement of these vehicles is 

to acquire the most efficient vehicle available to meet mission requirements.
12

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

The model allows vehicles to only be replaced by vehicles of the same vehicle type (e.g., a pickup can only be replaced by another pick-up). This replacement constraint ensures vehicles are 

replaced by vehicles of similar functionality and mission capability. A more specific designation 

of a mission requirement for each vehicle was not available at the time of this analysis across the 

fleets in a standard format. The constraint to ensure vehicles are replaced by the same vehicle 

type ensures the fleet capability is not drastically altered by the recommended vehicles. 

The lack of visibility into the fleet mission requirements is a significant hurdle in evaluating the 

alignment of existing fleet capabilities to mission and to properly evaluate the viability of 

replacement options that may alter fleet functionality. However, the model can easily be updated 

to include more specific constraints and this occurred on several occasions where agencies were 

able to provide them. An example would be when an agency decided the smallest sedan allowed 

to replace an existing sedan be a compact sedan rather than allowing the NOVA model to choose 

from the smaller sub-compact sedan type. In this instance the larger compact sedan was required 

to meet mission requirements. These requests were incorporated into the model as requested by 

agency fleet managers.

The vehicles available for lease from GSA include a range of vehicle fuel technologies from 

traditional gasoline and diesel vehicles to AFV technologies including E85-capable FFVs, 

HEVs, compressed natural gas (CNG) vehicles, PHEVs, and battery-electric vehicles (BEV). 

AFVs, with the exception of HEVs, require access to alternative fuel infrastructure to use the

appropriate alternative fuel. In addition to strict alternative fuel vehicles, diesel vehicles are “B20 

capable,” meaning they can be fueled with a blend of diesel that is comprised of 20 percent 

biodiesel and 80 percent petroleum diesel. Diesel vehicles are primarily available in mediumand heavy-duty vehicle model types. As previously mentioned, this study primarily focused on 

the light-duty portion of the fleet, and therefore diesel technologies did not have a significant 

impact on the analysis outputs.

3.4 Vehicle Geography

The analysis effort assigned a geographic location to each vehicle in the existing inventory to 

determine the vehicle proximity to known, available, alternative fuel infrastructure. GSA 

provides each agency with fuel transaction history reports that include the specific station 

locations at which each vehicle has fueled. Previous studies have relied on the garage location of 

the vehicle listed in the GSA inventory reports (Helwig and Deason, 2007). We assumed the fuel 

transaction locations were indicative of where vehicles operated and relied on the fueling data to 

determine the vehicle geographies. The NOVA model itself can accept whichever location a fleet 

deems most accurate.

The analysis used the transaction dataset to assign each vehicle a location determined by the 

station location at which the vehicle most often fueled in the prior fiscal year, 2011. In some 

instances, vehicle locations were not able to be determined from the transaction data. These 

vehicles either did not appear in the transaction data, or the vehicle transaction locations could 

not be accurately assigned a latitude and longitude based on the station address information. In 

these instances, the vehicle location reverted to the most precise garage location available, the 

center point of the garage zip code in the inventory data. 
13

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

The location of known alternative fuel infrastructure is available through the Alternative Fueling 

Station Locator on the Alternative Fuels Data Center6

. The Station Locator is maintained by the 

DOE Clean Cities Program and is regularly updated as alternative fuel infrastructure becomes 

available or closes.

In order for the model to consider an alternative fuel to be to be available to a particular vehicle, 

the infrastructure must be within a predefined distance from the specific vehicle location as 

defined above – the station most often visited in FY 2011 or the garage zip code when a 

transaction location was not available. The model considers E85 and CNG to be available to a 

vehicle if known infrastructure of the fuel type is located within five miles. DOE FEMP uses the 

five-mile distance cutoff when determining EPAct 2005 § 701 waiver status, and therefore the 

same five-mile distance was used as a cutoff for this study (DOE 2014).

Electric charging infrastructure is considered to be available to a vehicle location if known 

infrastructure is available within one mile. At the time of the study, electric vehicles were not yet 

broadly available to the fleet. The details of how agencies planned to use and charge the vehicles 

were not yet fully understood. It was assumed that agencies would require vehicles to charge on 

a regular basis in a location convenient to the operating location. The one-mile cutoff to define 

availability was arbitrary but was intended to meet the regular charging requirement. 

In addition to the distance requirement, agencies must be able to access the alternative fuel 

infrastructure for the analysis to consider the alternative fuel available. Agency fleet vehicles are 

considered to have access to the infrastructure if the station is publicly accessible and accepts the 

Wright Express credit card with which GSA-leased vehicles purchase fuel. Private infrastructure 

that is operated by an agency is also considered to be available to that agency’s vehicles. 

Alternative fuel infrastructure may open or cease operations over time and could impact the 

assumptions of alternative fuel availability; only infrastructure that was open and accessible at 

the time of the analysis was considered.

3.5 Annual Vehicle Fuel Consumption

The estimated annual fuel consumption for each vehicle was calculated by dividing the expected 

annual vehicle miles travelled for each vehicle by the vehicle fuel economy rating: 

AAAAAA F F CC C CCCCC

= (E E AAAAAA V h i M TT T )

/(V h i F F E E R R)

The fuel economy for each of the available vehicles for lease was determined by the combined 

fuel economy rating as reported for the vehicle in the GSA AFV Lease Guide7 made available to 

agency fleets. Fuel economy ratings from the EPA−administered website 

http://www.fueleconomy.gov were used in instances where the ratings were not available in the 

GSA AFV Lease Guide. Existing inventory vehicles were assigned fuel economy ratings by 

vehicle segment based on an average of the ratings of all the available vehicles for lease in the 

 6 http://www.afdc.energy.gov/locator/stations 7 http://www.gsa.gov/portal/content/104224
14

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

segment in the 2011 GSA AFV Lease Guide. Future efforts could be improved by using a more 

specific vehicle fuel-economy rating for each vehicle in the existing fleet. 

Each vehicle in an agency fleet was assigned the same annual-vehicle-miles-traveled value 

estimated by an average across all vehicles in the agency fleet. The inventory dataset contained a 

mileage field for each vehicle, but the raw data contained enough extreme and possibly invalid 

values for individual vehicles that the decision was made to use an average in place of the 

specific vehicle mileage. Some agencies preferred to use an internally created or known standard 

value to be used for the agency-wide vehicle miles traveled estimate. 

3.6 Percentage of Alternative Fuel Use

AFVs dedicated to a particular fuel type were only allowed by the model to be placed in locations 

where the fuel was available and were assumed to use the fuel 100 percent of the time. FFVs were 

allowed to be placed in any location; however, FFVs in locations without available E85 were 

assumed to not use any alternative fuel. FFVs in locations where E85 was available were assumed to 

be filled with the fuel 50 percent of the time and filled with traditional gasoline the remainder of the 

time. It can be seen in the fuel transaction reports that vehicles often operate over broad geographies 

with differing alternative fuel availability. The 50-percent-use assumption was intended to account 

for this reality and to not overstate the potential consumption of alternative fuel. 

3.7 GHG Emissions

GHG emissions are calculated in terms of metric tons of carbon dioxide equivalents (MT of 

CO2e), based on the annual quantities of fuel consumption for each vehicle by applying GHG 

conversion factors to the annual fuel consumption estimates. The federal fleet follows guidance 

from the White House Council on Environmental Quality (CEQ) on how to account for 

greenhouse gas emissions by calculating the tailpipe emissions that occur when the particular 

fuel is consumed by the vehicle during operation. The conversion factors used in the NOVA 

analysis are available in the Federal Fleet Handbook (DOE 2014) and are displayed in Table 1

and Table 2. The factors for CO2, CH4, and NO2 are available for each fuel type in terms of 

gasoline gallon equivalents (GGE). 

A singular GHG conversion factor to convert from GGEs to MT of CO2e for each fuel type is 

calculated from the conversion factors as follows:

GG M o CC2 CC F

= k /GG CC2 + (k /GG CC4 ∗ 21)

+ (k /GG N2 ∗ 310)

Fuel consumption is first converted from the natural units of the fuel type to GGEs by applying a 

separate GGE conversion factor listed in the federal fleet guidance for E.O. 13514 (DOE 2010).

The GGE conversion factors are displayed in Table 3. 
15

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 1. CO2 Emissions Factors by Fuel Type

Source: DOE 2014

Table 2. CH4 and N2O Emissions Factors by Fuel Type

Source: DOE 2014
16

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 3. GGE Conversion Factors by Fuel Type

Source: DOE 2010

3.8 AFV Incremental Budget

A primary management constraint for each agency is the AFV incremental budget. At the time of the 

study each AFV leased from GSA carried an incremental cost that represented the difference in cost 

between an AFV model and a base, low-cost option in each vehicle configuration. This incremental 

cost was listed for each AFV in the GSA AFV Lease Guide available from the GSA Alternative Fuel 

Vehicles website8

. Incremental costs ranged from a hundred dollars or less for some E85 capable 

FFVs to more than twenty thousand dollars for some electric vehicles.

Agencies pay for this incremental cost in the form of a monthly AFV surcharge on all (both AFV and 

non-AFVs) vehicles in the fleet. Some agencies budget for a higher investment in AFVs and set a 

higher AFV surcharge. Other agencies spend less on AFVs and therefore have a lower AFV 

surcharge. The range of AFV surcharges for the 11 agencies is listed in Table 4. The NOVA model 

ensures that the incremental AFV costs of the recommended set of replacement vehicles will not 

result in an AFV surcharge higher than the budgeted level. 

 8 http://www.gsa.gov/portal/content/104224
17

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 4. Agency AFV Surcharges

3.9 Acquisition Mandates in the Model

The NOVA model ensures satisfaction of the EPAct 1992 requirement that 75 percent of all 

LDV acquisitions in MSAs are AFVs. The GSA inventory dataset identifies which vehicles are 

in MSAs and the model ensures that at least 75 percent of these vehicles are AFVs. The model 

includes HEVs and PHEVs as vehicles that are considered AFVs in accordance with NDAA 

2008.

The EISA 2007 requirement to acquire only low-GHG vehicles is not directly accounted for in 

the model constraints. Low-GHG vehicles were not broadly available across all vehicle 

segments, and agencies frequently require vehicles that are not low-GHG vehicles in order to 

meet mission requirements. As an example, there were no low-GHG pickup truck options 

available for lease in FY 2012. The model does optimize the reduction of GHG emissions overall 

and therefore does support the spirit of the requirement. However, in order to produce 

recommendations that could meet agency mission requirements, the model does not explicitly 

enforce the requirement.

The model does not force the acquisition of PHEVs per E.O. 13423 as the current costs associated 

with available PHEVs were not considered to be comparable to non-PHEVs. As an example, a 

PHEV available for lease in FY 2012 carried an AFV incremental cost of over $20,000.
18

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

4 Model Development

4.1 Optimization Model Indices

The agency integer optimization models take advantage of the following indices:

• i = Agency, i = 1-11

• j = Vehicle type available for leasing from GSA j = 1-128

• k = Vehicle being replaced in agency inventory k = 1-number of vehicles in agency 

inventory

• l = Alternative fuel infrastructure access (1 = has access to existing AF stations, 2 = 

would have access only to newly constructed AF stations, 3 = does not have access to any 

AF stations, l = 1,2,3 

• m = Vehicle fuel types (1 = CNG, 2 = LPG, 3=E85, 4 = LNG, 5 = Gasoline Hybrid, 6 = 

Biodiesel, 8 = Gasoline, 9 = Electricity) m = 1-9

• o = Vehicle location, o = 1-number of agency unique vehicle locations

• p= Fuel types used (1 = CNG, 2 = LPG, 3 = E85, 4 = LNG, 5 = Petroleum Diesel, 6 = 

Biodiesel, 7 = Gasoline, 8 = Electricity), p = 1-8

4.2 Optimization Model Decision Variable 

The decision variable in the model is “AFVsAcquired (i,j,k,l,m,o)” which provides the vehicle type j

of vehicle fuel type m to replace vehicle k in the inventory with alternative fuel access type l at 

location o for agency i.

AFVsAcquired takes the value of 1 for the optimized combinations of incoming and outgoing 

vehicles defined by the indices. All other combinations take the value of 0. The NOVA model has 

the capability to optimize across fleets, but this study considered each agency fleet individually and 

therefore i was always 1 and represented the single agency studied. The alternative fuel infrastructure 

access options include the option to construct new infrastructure, but this study did not consider 

options to build new infrastructure, and therefore the l index took the value of 1, “has access to 

existing AF stations,” or 3, “does not have access to any AF stations.”

4.3 Optimization Model Definitions

A sampling of the definitions in the model included:

• IncrementalCost(j) = The incremental cost to acquire vehicle type j

• EPActCredit(j) = The number of EPAct vehicle acquisition credits for acquiring vehicle 

type j

• IncrementalBudget(i) = The incremental budget for agency i

• TotalLDMSA(i) = The total number of light-duty vehicles in MSAs in agency i

• TotalAnnualOutgoingGGE(k,o,p) = The estimated annual fuel use in GGEs of fuel type p

by vehicle k in the inventory at location o
19

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

• TotalAnnualIncomingGGE(j,o,p) = The estimated annual fuel use in GGEs of fuel type p

by incoming vehicle type j at location o

• GHGFactor(p) = The GGE to MT of CO2e conversion factor for fuel type p

The “TotalAnnualOutgoingGGE” and “TotalAnnualIncomingGGE” metrics were calculated by 

taking into account the types of fuels each vehicle can operate with and the availability of the 

alternative fuel at each vehicle location. As an example, if vehicle k1 in the inventory is an FFV 

capable of running on E85 or gasoline and is located at location o1 which has E85 available, 

TotalAnnualOutgoingGGE(k1,o1,Gasoline) and TotalAnnualOutgoingGGE(k1,o1,E85) would be

non-zero GGE values. If the same vehicle were operating at location o2, which does not have 

E85 available, TotalAnnualOutgoingGGE(k1,o2,Gasoline) would be a non-zero value while 

TotalAnnualOutgoingGGE(k1,o2,E85) would be zero. The metric would carry a zero value of all 

other fuel types.

4.4 Optimization Model Constraints

Two of the constraints used in the models are illustrated below:

(1) Budget must not be exceeded:

� A A AA ( ,j, k, , , ) ∗ I (j) ≤ I I ( ),

j,k,l,m,o

(2) EPAct vehicle acquisition credits must meet or exceed 75 percent of the number of light-duty 

vehicles in MSAs in the fleet:

� A A AA ( ,j, k, , , ) ∗ EE E (j) ≥ 0.75 ∗ T TT T ( ),

j,k,l,m,o

Additional constraints ensured dedicated alternative fuel vehicles were not placed in locations 

where the appropriate alternative fuel was not available, as well as appropriate integer, binary, 

and non-negativity constraints.

4.5 Optimization Model Objective Function

The objective function maximizes the difference of GHG emissions of the outgoing vehicles and 

incoming vehicles as follows:

Maximize � � [A A AA (i, j, k, l, m, o) × T (k, o, p) × G G ( )]

i,j,k,l,m,o,p

�

− � � [A A AA (i, j, k, l, m, o) × T (j, o, p)

i,j,k,l,m,o,p

× G G ( )]�

Since the GHG emissions of the outgoing vehicles are fixed and known, maximizing this 

difference is equivalent to making incoming vehicle GHG emissions as small as possible, which 

is the goal of this model.
20

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

GHG emissions are calculated by applying the appropriate fuel-type GHG-emissions factors to 

the annual fuel consumption of each vehicle. The “TotalAnnualOutgoingGGE” and 

“TotalAnnualIncomingGGE” metrics take into account fuel availability at the location of each 

vehicle and the impacts, if any, that availability has on the quantities of alternative fuel and 

petroleum the vehicles are estimated to use.
21

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

5 Model Runs and Results

5.1 Optimization Model Results

NOVA model runs and analyses were completed for each of the 11 agencies individually. In a 

typical year, agencies replace about 10 to 30 percent of their vehicle inventories. However,

analyses were completed to generate replacement recommendations for every vehicle in the 

agency inventories with a discernible light-duty replacement option. By analyzing the entire 

existing inventory, we were able to complete the study prior to the vehicle ordering cycle when 

specific vehicles are identified as replacement eligible. In addition, the study supported agency 

out-year planning by providing recommendations for vehicles that would be replaced in 

subsequent years. 

Across the eleven fleets, 68,866 vehicle recommendations were developed, as shown in Table 5. 

The vehicle recommendations totaled 11% of all 600,405 federal fleet vehicles in FY 2012. 

Table 5. FY 2012 GSA Leased Vehicle Inventories and Recommendations

The final vehicle recommendations included FFVs, HEVs, and efficient conventional gasoline 

vehicles. These technologies were recommended after the model weighed the GHG savings 

benefits against the costs of acquiring large numbers of the vehicles across the fleet.
22

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 6. NOVA Recommendations by Vehicle Fuel Type

Table 6 shows how FFVs dominated the vehicle recommendations. This occurred for several 

reasons: (1) FFVs have a very low AFV incremental cost in comparison to other technologies. 

(2) FFVs have become available in highly efficient models that even when operated only on 

gasoline achieve higher mile-per-gallon ratings than other traditional gasoline only models. (3) 

The vehicles allow for significant petroleum displacement when fueled regularly with E85.

Highly efficient HEVs were recommended in smaller but significant numbers. HEVs were not 

recommended in higher numbers primarily due to high incremental costs. The model determined 

that the budget needed for the cost of acquiring a single HEV was better spent toward the goal of 

achieving overall fleet GHG reductions by spreading that cost across many efficient FFVs that 

can regularly fuel with E85.

CNG vehicles ultimately were not recommended. There was only a single light-duty CNG 

vehicle model available to the agencies, and it carried a high incremental cost. Additionally there

was a relative lack of CNG infrastructure available to the fleet locations. Finally, the estimated 

GHG emissions from the CNG vehicle were higher than other vehicle alternatives, due in part to 

the lower fuel economy of the CNG vehicle.

At the time of the analysis, EVs and PHEVs were available to the fleets through GSA in small 

numbers only in a pilot program aimed at introducing the vehicle technology to the federal fleet. For 

this reason along with high incremental costs, these vehicles were not recommended to agencies.

While the model did not recommend CNG, PHEV, or BEV technologies, agencies were 

encouraged to pursue the technologies in instances where budget and the local vehicle operating 

environment could allow the technologies to succeed.
23

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

5.2 Vehicle Technology Comparisons

Figure 6 compares some of the different vehicle models and fuel technologies available through 

GSA in the sedan segment at the time of the study and displays why the chosen vehicle 

technologies dominated. 

Figure 6. Sedan fuel consumption comparisons

Compared to a traditional gasoline-powered sedan, significant gasoline savings could be 

achieved through the use of the highest efficiency traditional gasoline vehicle available, which 

carried zero incremental cost. A higher level of fuel savings could be achieved through the use of 

an HEV, which carried a sizeable incremental cost. An efficient FFV could achieve an even 

greater gasoline savings if the FFV regularly used E85. Figure 6 employs the 50 percent use 

assumption for an FFV with available E85. Finally, a CNG vehicle would operate only on CNG 

and not use gasoline, but the vehicle carried a sizeable incremental cost.

Figure 7 displays a similar comparison after the fuel consumption values are converted to GHG 

emissions. In this comparison, the FFV filling with E85 50 percent of the time could produce the 

least amount of GHG emissions of any of the vehicle options. The HEV could produce the least 

amount of GHG emissions in instances where vehicles do not have access to E85. As previously 

stated, the available CNG vehicle was not recommended due to several reasons. In this view, it 

can be seen that the estimated GHG emissions from the CNG vehicle, while lower than the 

traditional gasoline vehicles, were higher than other vehicle alternatives.

Noticeably, the E85 GHG impact is very small. Per the Federal Fleet Handbook (DOE 2014) 

“CO2 emissions from the biofuels portion of the fuel are known as biogenic emissions, and must 
24

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

be reported within the appropriate scope in which they occur and must be categorized as 

biogenic. Agencies are not required to include these emissions in their reduction targets under 

E.O. 13514 at this time.” The federal fleet methodology of accounting for GHG emissions from 

burning E85 considers the ethanol portion of the fuel to be produced from a biogenic source. The 

biogenic portion of the GHG emissions are not counted as emissions against agencies’ emission 

inventories and reduction targets. Therefore, the GHG conversion factor used in this study 

excludes the biogenic emission factors in Table 1. 

Figure 7. Sedan GHG emissions comparisons

5.3 Estimated Impacts of Recommendations

The potential impact of replacing existing inventory vehicles with the recommended vehicles on 

the metrics of overall fleet petroleum use, alternative fuel use, and GHG emissions was estimated 

for each agency. These metrics were estimated for both the current vehicle inventory as well as 

the recommended vehicles, and then compared. The comparisons were not related back to 

observed or officially reported fuel use. The comparisons represented theoretical maximums for 

the portion of the fleet receiving recommendations after one year of operation. The comparisons 

rely on a number of assumptions including (1) all vehicles receiving a recommendation are 

replaced, (2) all vehicles travel the fleet average annual miles, and (3) the vehicles achieve the 

assigned fuel economy ratings.

Estimates for petroleum reduction, GHG emission reduction, and alternative fuel increase are 

summarized in Table 7, Table 8, and Table 9 respectively. Petroleum reductions range from 19 to 

30 percent for each fleet. GHG emission reductions closely mimic the petroleum reductions and 

range from 19 to 29 percent. Alternative fuel increases range from 18 to 84 percent. The large 
25

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

range in estimated alternative fuel increase is due to high variability in how well existing fleet 

inventory AFVs are aligned with available infrastructure. Those agencies that already had FFVs 

located near available E85 infrastructure would see lower gains in comparison to agencies that 

did not have many fleet FFVs near available E85 infrastructure.

Table 7. Estimates of Petroleum Reduction

Table 8. Estimates of GHG Emissions Reduction
26

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 9. Estimates of Alternative Fuel Increase

In practice, agencies replace just 10 to 30 percent of their fleet in a given year, and it is unlikely 

vehicles will all travel the same distance or achieve the rated fuel economy. However, when 

taken in context, these theoretical estimates allow for comparisons of vehicle replacement 

strategies and provide a scale for potential impacts.

As discussed above, E.O. 13514 requires federal fleets to achieve a two percent reduction in 

petroleum consumption per year. Assuming the percent of the fleet that is replaced in a given 

year is comprised of a mix of vehicle segments representative of the fleet in total, then the 

expected petroleum reduction after a year of following the vehicle replacement recommendations 

can be estimated by multiplying the percent of the fleet replaced by the model petroleum 

reduction-percentage estimate. Table 10 shows that by completing this effort for a range of 10 to 

30 percent the fleets could expect to meet or exceed the 2 percent petroleum reduction mandate 

by closely following the vehicle recommendations without additional fleet operations efforts to 

reduce petroleum consumption.
27

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table 10. Partial Fleet Replacement Petroleum Reduction

5.4 Sources of Impact

Estimated petroleum reductions are derived from three primary segments of vehicle 

recommendations including (1) efficient FFVs able to use available E85 50 percent of the time, (2) 

highly efficient HEVs using gasoline 100 percent of the time, and (3) efficient FFVs and traditional 

gasoline vehicles in locations without available E85 and using gasoline 100 percent of the time.
28

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 8. Sources of petroleum reduction

Figure 8 shows that while the advanced technologies of FFVs regularly using E85 and HEVs 

efficiently using gasoline reduce petroleum consumption, considerable petroleum savings are 

achieved simply by using more efficient traditional vehicles operating on gasoline. In total, 

across all agencies studied, efficient FFVs and traditional vehicles using gasoline 100 percent of 

the time accounted for 44 percent of the overall petroleum reduction. FFVs using E85 50 percent 

of the time accounted for an additional 44 percent of the petroleum reduction. This share of the 

total would be greater if E85 fueling infrastructure were more widely available nationwide. The 

final 12 percent of overall petroleum reduction was due to HEVs. 

Figure 9 breaks out the petroleum reduction for each agency, and includes the AFV surcharges 

for each agency. The surcharges are a measure of how much an agency spends on the acquisition 

of AFVs per vehicle per month in the inventory. Those agencies that have higher AFV 

surcharges, and therefore larger per vehicle budgets to cover the high incremental costs 

associated with HEVs, are often able to acquire relatively higher numbers of HEVs that can 

contribute significantly to petroleum reduction.
29

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 9. Sources of petroleum reduction by agency

The broader lesson learned from this study is that to efficiently take advantage of the three 

primary sources of petroleum reduction, agencies would be best served by: (1) Targeting FFVs 

in locations where E85 is available. (2) Targeting HEVs when budget allows, where E85 is not 

available, and when driving routes involve stopping and starting that enables HEVs to achieve 

their full fuel economy benefit. (3) Targeting the most efficient traditional gasoline vehicles or 

FFVs available where E85 is not available and the budget is a constraint.
30

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

6 Conclusions

Federal agency fleets can make progress toward fuel use goals through strategic vehicle 

acquisitions that efficiently meet mission requirements and achieve mandated acquisition goals 

while staying under budget. The results of this study show the theoretical benefits of following 

the vehicle recommendations of an optimized vehicle acquisition. 

However, fleet management has been challenged to implement the specific vehicle 

recommendations of NOVA. A variety of non-energy factors make specific choices challenging, 

such as organizational structure, mission nuances, vehicle availability, and user preferences—all 

of which vary widely among fleets, both nationally and locally.

The model assumes a fleet with a centralized organizational structure could place one order for all 

vehicles in the fleet. In practice, many agency fleet organizations are decentralized and can submit 

orders at various times for portions of the fleet. Further there can be extensive back and forth 

within a fleet organization as well as with GSA representatives before orders are finalized. This 

more complex ordering process makes it challenging for a fleet to follow the vehicle 

recommendations in their entirety.

Federal fleets can benefit most from an optimization model decision-support tool during the vehicle 

ordering process in instances where the fleet management structure is centralized and national 

management can distribute vehicle recommendations to all levels of the fleet organizational structure. 

Additionally agencies can define specific vehicle mission requirements to ensure the appropriate 

constraints are included in the model and results provide an appropriate recommendation.

Findings from this study provided generalized vehicle ordering guidance appropriate until there 

are significant changes in vehicle technology availability and cost. The study shows that to 

efficiently meet mandates, agencies should prioritize placing FFVs in locations where E85 

infrastructure exists and regularly fuel the FFVs with E85. HEVs are most beneficial in locations 

where E85 does not exist, when the budget allows for increased AFV incremental costs, and 

when driving routes involve stopping and starting—enabling HEVs to achieve their full fuel 

economy benefit. Efficient traditional gasoline vehicles should be targeted where alternative fuel 

does not exist and budget dollars are tight. CNG and electric vehicles were not widely available 

across federal fleet vehicle segments and carried high incremental costs. These technologies 

were viewed as best suited for specialized applications or pilot efforts where budget is available 

and unique local conditions were favorable to the technology success.

Federal fleets are subject to a myriad of sustainability mandates ranging from high-level goals to 

specific operational targets. While these mandates are often complementary, an optimized fleet is 

likely to contain a different composition of vehicles depending on the mandate that is given 

priority. Helwig and Deason (2007) showed that by varying the prioritization of mandates, the 

scope of vehicles defining an optimal fleet could be drastically affected. 

In this study, the NOVA model optimized the reduction of GHG emissions based on the 

guidance of E.O. 13514. The goal of reducing GHG emissions is achieved through the 

complementary mandated goals of acquiring AFVs, increasing the use of alternative fuels, and 

reducing petroleum use. Any mandate changes that affect this prioritization could have a 

significant impact on how fleets meet the mandated goals.
31

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

7 References

DOE 2010. Guidance for Federal Agencies on E.O. 13514, Section 12, Federal Fleet 

Management. Available from:

https://federalfleets.energy.gov/sites/default/files/static_page_docs/fleetguidance_13514.pdf, 

accessed December 27, 2012. 

DOE 2014. Comprehensive Federal Fleet Management Handbook. Available from:

https://federalfleets.energy.gov/sites/default/files/static_page_docs/eo13514_fleethandbook.pdf, 

accessed January 28, 2015. 

Daley, R., et al (2014). Refueling Behavior of Flexible Fuel Vehicle Drivers in the Federal Fleet. 

NREL/TP-5400-61777. Golden, CO: National Renewable Energy Laboratory. Accessed June 4, 

2014: http://www.nrel.gov/docs/fy14osti/61777.pdf. 

Helwig, M., and Deason, J. (2007). “The Energy Policy Act of 1992 and Executive Order 13149: 

Proposed compliance strategies and process improvements for federal agencies.” Energy Policy,

Vol. 35, Issue 5. Accessed June 4, 2014: 

http://www.sciencedirect.com/science/article/pii/S030142150600406X.

Deason, K., and Jefferson, T. (2010). “A systems approach to improving fleet policy compliance 

within the US Federal Government.” Energy Policy, Vol. 38, Issue 6, pages 2865 - 2874 (2010).

Accessed June 4, 2014: http://www.sciencedirect.com/science/article/pii/S030142151000025X.

White House 2009. Federal Leadership in Environmental, Energy and Economic Performance -

EXECUTIVE ORDER 13514. Available from: 

http://www.whitehouse.gov/administration/eop/ceq/sustainability. Accessed July 22, 2014.

White House 2010. Federal Greenhouse Gas Accounting and Reporting Guidance: Technical 

Support Document. Available from:

http://www.whitehouse.gov/sites/default/files/microsites/ceq/technical_support_document_1.pdf.

Accessed December 28, 2012. 

White House 2011. Presidential Memorandum – Federal Fleet Performance. Available from:

http://www.whitehouse.gov/the-press-office/2011/05/24/presidential-memorandum-federal-fleetperformance. Accessed December 28, 2012. 

White House 2012. Federal Greenhouse Gas Accounting and Reporting Guidance. Available 

from:

http://www.whitehouse.gov/sites/default/files/microsites/ceq/revised_federal_greenhouse_gas_ac

counting_and_reporting_guidance_060412.pdf. Accessed December 28, 2012. 
32

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Appendix A. Federal Fleet Requirements

Table 11. Summary of Primary and Supporting Federal Fleet Requirements

Statute or 

Exec. Order Requirement

Primary Federal Fleet Requirements

GHG Reduction E.O. 13514 Sets a percentage reduction target for reductions of Scope 1 and 2 GHG 

emissions from FY 2008 to FY 2020

Petroleum

Reduction

E.O. 13514 Requires 2 percent annual reduction from FY 2005 to FY 2020

E.O. 13423 Requires 2 percent annual reduction from FY 2005 to FY 2015

EISA § 142 Requires 20 percent total reduction from FY 2005 to FY 2015

Supporting Federal Fleet Requirements

Agency 

Sustainability Plan E.O. 13514 Establishes the fleet component of an overall agency plan to achieve E.O. 

13514 sustainability goals and targets for FY 2011 to FY 2021

Alternative Fuel 

Use Increase

E.O. 13423 Requires 10 percent annual increase (from previous year), starting from 

the FY 2005 baseline through FY 2015

EISA § 142 Requires 10 percent total increase from FY 2005 to FY 2015

Alternative Fuel 

Use

EPAct 2005 §

701 Requires all dual-fueled AFVs to use alternative fuel unless waivered

Renewable Fuel 

Infrastructure EISA § 246 Requires every federal fueling center without renewable fuel availability to 

install a renewable fuel pump

Vehicle Acquisition

EPAct 1992 Requires 75 percent of light-duty vehicles acquired in metropolitan 

statistical areas to be AFVs

EISA § 141 Prohibits agencies from acquiring vehicles that are not low GHG-emitting 

vehicles

E.O. 13423 Requires agencies to use plug-in hybrid electric vehicles (PHEVs) when 

commercially available at a cost reasonably comparable to non-PHEVs

Agency Fleet Plan EISA § 142 Establishes an agency plan to meet required petroleum reduction and 

alternative fuel-use increase requirements

Reporting EPAct 1992, 

ECRA 1998 Requires agencies to report to Congress annually on their compliance with 

the federal fleet requirements (by February 15 of each year)