Charging Station Analysis iCAST Task 21: Identify charging station

Task 21
Final Report
Charging Station Analysis
iCAST
Task 21: Identify charging station sites
July 27, 2012
Abigail Clarke-Sather
Sarah Blok
Nathan Knowles
Diane Hildebrand
David Rogers
Sidharth Modi
Ryan Citroen
Kevin Brooks
James Tyson
1
Executive Summary
2
Introduction and Initial Assumptions
3
Electric Vehicle Sales Projections
3.1
Methodology for EV Sales Projections
3.2
EV Sales Projections Used in This Report
4
Charging Station Projections of Numbers and Distribution by
Location Category
4.1
Allocation of Charging Stations by Location Category
4.2
Distribution of Charging Stations at Home
4.3
Distribution of Charging Stations at Work
4.4
Distribution of Charging Stations at Public Attractions
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Distribution Maps of Charging Station Projections by Census
Tract, Zip Code and County
5.1
6
Current EVSE Locations in Colorado
Resources Cited
6.1
Other Resources of Interest
1 Executive Summary
This report makes projections of the numbers and distribution of electric vehicle
charging stations (EVSE) in Colorado for the years 2015 and 2025. The projected
distribution of EVSE is divided into three categories: home, work, and public, and
mapped by county, Zip code, and census tract. Three scenarios are used to forecast the
number of charging stations based on low, medium, and high adoption rates of plug-in
electric vehicles (PEVs). In this report, the terms EV and PEV are synonymous and
include battery electric vehicles (BEV) and plug-in hybrid electric vehicles (PHEV).
Charging station projections developed in this report are summarized in Table 1:
Table 1: Summary of the projected number of charging stations by adoption scenario and location
category
2015
2025
Low
Medium
High
Low
Medium
High
Home
28,120
34,766
Public
3,596
4,512
5,481
13,787
38,500
62,775
Work
2,989
3,682
4,491
11,039
30,321
47,380
Total
34,705
42,960
42,392 104,026 288,156 471,507
52,364 128,852 356,977 581,662
As Table 1 indicates, about 80% of charging stations will be located at home, where
most charging will occur. Most of the charging stations are projected to be distributed
along the I-25 and I-70 corridors and concentrated in the nine-county territory of the
Denver Regional Council of Governments.
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The myriad and complex factors that affect where and how many charging stations will
be installed in Colorado in 2015 and 2025 include the following:









Charging station technology, cost, and accessibility
Electric vehicle technology, range, and cost
Commuting and travel patterns of EV owners
Demographic profiles of EV owners
Population growth
Fuel prices
Government policies and incentives
Automakers’ priorities and marketing strategies
Other market drivers
To account for these factors, this report relies on numerous models of EV sales
projections and extensive research on the demographics of EV owners, charging station
technologies, and government and commercial EV development strategies. The EVSE
projections are also derived from extensive data on current charging station locations
and hybrid vehicle registrations, regional travel patterns, demographic statistics, and
census data and growth rates of population, employment, and business establishments.
The data sources, assumptions, and methodologies are described in this report.
In the methodology developed by iCAST, the distribution of the projected number of
charging stations was determined by first mapping the estimated distribution of EV
ownership over the forecast period. This was calculated by applying a demographic
profile to census data to estimate the probability of EV ownership by census tract. Next,
information about projected travel patterns, commuting distances, and employment
densities was used to map commuting zones by Zip code around the areas of high EV
ownership. The projected distribution of charging stations was mapped according to the
probability of EV ownership in the commuting zones, as well as public attractions, such
as airports, major highways, and state and national parks. This report assumes that, for
every 100 plug-in electric vehicles, there will be 100 homes with charging stations and,
on average, 10 private commercial charging stations, and 20 public charging stations.
This report assumes those ratios will stay the same over the forecast periods.
The charging station projections were mapped into a geographic information system.
The distribution maps and tables of the charging station projections are presented at the
end of the report according to forecast year and EV adoption rate scenario for each
location category (home, work, and public).
The projected distribution of the charging stations is resolved into 64 Colorado counties
for all scenarios. Except for the 2025 High adoption rate scenario, the projected
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distribution of household charging stations is resolved into 1249 Colorado census tracts,
whereas the distribution of public and work-based stations is resolved into 460 Colorado
Zip codes to maintain consistency with the data sources. No attempts were made at
“micro-siting” the electric vehicle supply equipment beyond the census tracts and Zip
codes. Forecast calculations for 2025 include county-level growth rate projections for
population and employment, but 2015 forecasts apply EV adoption rate projections to
2009 and 2012 population and employment statistics without applying county-level
growth rate projections.
Forecasts of the numbers and distribution of EVSE can be used to estimate the
requirements for grid upgrades, coordinate transportation strategies, and aid in
developing EV incentive programs on a regional basis. EV and EVSE technologies are
considered to be in the early adoption stage and developing rapidly, especially with
respect to vehicle range and rapid charging technologies and standards, which could
have the greatest impact on requirements for grid upgrades. The large uncertainties
inherent in predicting technological advancement translate into the wide differential in
EV sales projections and the corresponding number of charging stations in 2025. The
low scenario for 2025 represents an optimistic baseline projection with high oil prices,
while the high scenario represents an aggressive forecast that requires supportive
policies and EV market stimulus.
In all scenarios, household charging stations comprise at least 80% of all EVSEs, but no
distinction is made of how many of those will include dedicated EV supply equipment,
whereas most owners may simply plug in to a standard electrical outlet. Projections of
the numbers and distribution of public and work-based charging stations are most
important for the purposes of public planning. Combined projections of public and workbased charging stations in Colorado range from 6,600 to 10,000 in 2015, and 25,000 to
110,000 in 2025.
Of particular interest in this project is the forecasted number of public charging stations
based on trip purpose, presented in
Table 2. These forecasts are derived from data in the Front Range Travel Counts
survey, provided by DRCOG. The projections are based on trip frequency by purpose,
dwell time, and other assumptions as described in section 4.4, which also breaks down
the numbers and distribution of EVSE in the transit category according to highways,
airports, and RTD Park-n-Rides. The estimates in
Table 2 assume that public charging stations will primarily utilize a technology like DC
fast charging (DCFC) that will charge an electric vehicle to 80% of capacity in under 30
minutes. This assumption may be too optimistic for 2015 since fast charging technology
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is still in the process of standardization and adoption by automakers, and access to
rapid charging stations may be very limited.
Table 2: Percentages and projected number of public charging stations in Colorado according to
trip purpose
2015
% of
EVSE
Shopping
Low
Medium
2025
High
Low
Medium
High
41%
1,482
1,857
2,257
5,661
15,825
25,776
4%
144
180
219
551
1,540
2,511
17%
611
767
932
2,344
6,545
10,672
Parks
4%
144
180
219
551
1,540
2,511
Health Care Facilities
9%
324
406
493
1,241
3,465
5,650
Civic and Religious
Organizations
4%
144
180
219
551
1,540
2,511
15%
539
677
822
2,068
5,775
9,416
6%
208
263
319
818
2,271
3,729
100%
3,596
4,512
5,481
13,787
38,500
62,775
Schools
Restaurants
Indoor Entertainment
Transit
Total
2 Introduction and Initial Assumptions
This report makes projections of the numbers and distribution of electric vehicle supply
equipment, also referred to as EVSE or charging stations, in Colorado to the years 2015
and 2025, and maps the projected distribution by county, Zip code, or census tract,
depending on the location category (home, work, or public) and data sources.
Projections of the number of EV charging stations are derived from sales projections
and the total number of electric vehicles expected to be in use in 2015 and 2025. The
EV sales projections include low, medium, and high sales scenarios. A report by the
Southwest Energy Efficiency Project (SWEEP) derives and explains the three sales
scenarios and the projections for Colorado, which are summarized in Section 3. Sales
projections include all light-duty vehicles that are also plug-in electric vehicles (PEV),
including battery electric vehicles (BEV), and plug-in hybrid electric vehicles (PHEV).
It is assumed that electric vehicles will spend most of the time charging at home, some
time charging at work, and the least time charging in public locations. The ratios of
charging times at private commercial and public charging stations are assumed to
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increase from 2015 to 2025 as the adoption of rapid charging technology increases, as
indicated in Table 3.
Table 3: Estimated percentage of time electric vehicles spend charging in each location category
Charging Location
2015
2025
Home
75-95%
60-75%
Work
5-20%
15-35%
Public
0-5%
5-10%
Despite these ratios, research indicates that planning agencies expect more charging
stations to be located in public locations than private commercial (work-based)
locations. In this report, forecasts to 2015 and 2025 assume that there will be one
household charging station for each electric vehicle, one public charging station for
every five EVs, and one private commercial charging station for every ten EVs. Workbased and public charging stations are assumed to have only dedicated EV charging
equipment, although no such distinction is made for home charging stations, where
most owners may simply plug in to a standard electrical outlet. Nevertheless, these
household stations are included in the collective references to electric vehicle supply
equipment and the projected numbers of household EVSE.
The future of technological development in electric vehicles and EVSE plays a critical
role in the projections in this report. Electric vehicles are still a nascent technology in
several important ways, including rapid charging technologies. The progress of rapid
charging technologies like DC Fast Charging (DCFC), which appears to be emerging as
an industry standard, will strongly influence EV adoption rates, requirements for gird
upgrades, and access to charging stations, particularly in public locations. It is assumed
that widespread adoption of DCFC technology would enable a much larger number of
public charging stations, as in the High sales scenario. Table 4 shows PEV models
available in the U.S. market today, with the supported charging technologies. Level I
charging includes standard, 120 V AC electric outlets. Level II includes 240 V AC
electric outlets.
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Table 4: Current PEV models
Make
Model
Vehicle
Class
Year
Introduced
Charging
Level
Support1
Cost
Type
Ford2
Focus
Hatchback
Early 2012
$41,000
I/ II
EV
Mitsubishi3
i (iMiev)
Hatchback
Dec-2011
$29,125
I/ II/ DCFC
EV
Nissan4
Leaf
Hatchback
Dec-2010
$35,200
I/ II/ DCFC5
EV
Tesla6
Model S
Full Size
Mid 2012
$57,400
I/ II
EV
Tesla7
Roadster
Small
Dec-2011
$109,000
I/ II
EV
Chevrolet8
Volt
Compact
Dec-2011
$44,600
I/ II
PHEV
Toyota9
Prius
Hatchback
Jan-2012
$32,000
I
PHEV
Section 4 describes how the EV sales projections were translated into the projected
distribution of charging stations by county, Zip code, and census tract. Calculations of
the final projections of the numbers and distribution of EV charging stations in Colorado
are based on numerous data sources and assumptions. Research on the demographic
characteristics of hybrid vehicle owners was combined with demographic data and
population growth projections to map the projected distribution of household charging
stations by census tract. Census data on employment and business growth patterns
was used to map the projected distribution of work-based charging stations by Zip code.
These data were combined with a study on travel patterns and traffic projections in
Colorado to map the projected distribution of public charging stations by Zip code.
Section 5 presents maps of the projected distributions by year, location category (home,
work, and public) and projection scenario (low, medium, and high).
1
http://www.azuredynamics.com/products/transit-connect-electric.htm
http://www.ford.com/electric/focuselectric/2012/
3
http://www.mitsubishi-motors.com/special/ev/
4
http://www.nissanusa.com/leaf-electric-car/tags/show/range#/leaf-electriccar/theBasicsRange/index
5
http://www.nissanusa.com/leaf-electric-car/tags/show/charging#/leaf-electric-car/
6
http://www.teslamotors.com/models/features#/performance
7
http://www.teslamotors.com/roadster/specs
8
http://www.chevrolet.com/volt-electric-car/features-specs/
9
http://www.toyota.com/prius-plug-in/trims-prices.html
2
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3 Electric Vehicle Sales Projections
The projected numbers of EV charging stations are derived from sales projections and
the total number of electric vehicles expected to be in use in 2015 and 2025. The EV
projections used in this report were developed in a report by the Southwest Energy
Efficiency Project (SWEEP)10 that includes projections of EV adoption rates for three
market scenarios for Colorado. Sales projections include low, medium, and high EV
adoption scenarios and comprise all plug-in electric vehicles (PEV) in the light-duty
vehicle fleet, including battery electric vehicles (BEV), and plug-in hybrid electric
vehicles (PHEV). SWEEP derived the three EV adoption scenarios from reports by the
Energy Information Administration (EIA), the Environmental Protection Agency (EPA),
and the California Air Resources Board (ARB).
3.1 Methodology for EV Sales Projections
SWEEP initially examined five scenarios for EV adoption rates in Colorado, which were
developed from three government reports that evaluated national trends, policies, and
strategies in EV sales and markets, and distilled them into the three EV adoption
scenarios used in this report. Table 5 and Table 6 respectively show projections of the
Colorado annual electric vehicle sales and the total number of electric vehicles in the
Colorado light-duty vehicle fleet, based on the five scenarios.
The Baseline and High Oil Price scenarios from the EIA are derived from the 2011
Annual Energy Outlook report, which assumes that the corporate average fuel economy
(CAFE) standards and other policies will remain the same throughout the projection
period. To convert the EIA’s projections for the Mountain Census Division to Colorado
projections, SWEEP determined the number of registered vehicles in each state of the
mountain division and calculated the ratio of registered vehicles in Colorado (24.1%).
That ratio was applied to the EIA data to determine the projected EV sales and total
electric vehicles in Colorado for the Baseline and High Oil Price scenarios.
10
SWEEP. Robert E. Yuhnke and Mike Salisbury. 2011. “Electric Vehicles Can Buffer
Colorado From The Economic Shocks Of Rising Fuel Prices, Create Jobs And Reduce
Pollution Control Costs”. Southwest Energy Efficiency Project. Colorado Public Utilities
Commission Docket No.11I-704EG.
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Table 5: Colorado annual EV sales projections for five scenarios of EV adoption
2015
2020
2025
2030
2035
Baseline (EIA)11
2,482
3,211
6,307
9,298
11,780
High Oil Price (EIA)12
5,899
6,036
11,282
15,363
19,807
ZEV Proposal (ARB)13
4,914
20,436
33,281
37,133
40,372
Aggressive Marketing (EPA)14
5,899
25,941
61,236
97,604
133,409
Very Aggressive Marketing (EPA)15
8,642
46,929
96,227 159,421
224,522
Table 6: Projected number of EVs in Colorado’s light duty fleet
2015
2020
2025
2030
2035
8,365
21,583
45,887
80,788
121,811
High Oil Price (EIA)
26,130
53,702
98,073
146,754
208,428
ZEV Proposal (ARB)
8,512
71,030 217,481
391,773
539,960
Baseline (EIA)
Aggressive Marketing (EPA)
26,130 101,836 334,411
Very Aggressive Marketing (EPA)
28,872 172,379 557,716 1,191,218 2,074,903
701,807 1,241,887
The ZEV Proposal scenario is derived from California’s Zero Emissions Vehicle (ZEV)
Program, which requires an increasing percentage of annual vehicle sales to be PEVs,
according to the following schedule:
11
EIA. 2011 AEO Supplemental Tables: Light-Duty Vehicle Sales by Technology Type:
Table 55: Mountain. http://www.eia.gov/forecasts/aeo/tables_ref.cfm
12
EIA. 2011 AEO Data Tables: High Oil Price: Table 48: Light-Duty Vehicle Sales by
Technology Type-Mountain.
http://www.eia.gov/forecasts/aeo/data_side_cases.cfm#summary
13
http://www.arb.ca.gov/msprog/zevprog/zevprog.htm
14
http://www.epa.gov/oms/climate/GHGtransportation-analysis03-18-2010.pdf , ff. 13.
15
Ibid.
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2012 to 2014:
Battery Electric
Vehicles
(BEV)
0.2%
Plug-in Hybrid
Electric Vehicles
(PHEV)
0.3%
2015 to 2017:
0.9%
1.1%
2018:
1.2%
4.1%
2025:
4.4%
7.0%
Final Report
To apply this schedule to Colorado EV sales projections, SWEEP used the EIA’s annual
sales projections for all light-duty vehicles in the Mountain Census Division to determine
annual per capita sales, and applied the ZEV Program schedule to the total projected
light-duty vehicle sales in Colorado.
The Aggressive Marketing and Very Aggressive Marketing scenarios were developed
by the EPA in their analysis of strategies to mitigate greenhouse gas emissions from the
transportation sector. In the EPA analysis, PEVs would compose 14% of the U.S. lightduty vehicle fleet by 2030 under the Aggressive Marketing scenario and 21% of the fleet
by 2030 under the Very Aggressive Scenario. SWEEP projected these estimates
backwards to calculate the percentage of vehicle sales and total vehicles in Colorado
consisting of PEVs for each year from 2012 to 2030.
3.2 EV Sales Projections Used in This Report
SWEEP simplified the five scenarios by applying the annual EV sales projections for the
EIA’s High Oil Price scenario to the Low EV adoption rate scenario, and applying the
annual EV sales projections for the EPA’s Aggressive scenario to the High EV adoption
rate scenario. The Medium EV adoption rate scenario is an average of the High and
Low scenarios. Table 7 depicts the projected annual EV sales and total number of
electric vehicles in Colorado as estimated by SWEEP.
Table 7: SWEEP's projections of EV sales and vehicles in Colorado
2015
Low
% of Ann. Sales
Total EVs
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Medium
2025
High
Low
Medium
High
2.3%
4.3%
6.3%
3.9%
13.0%
22.1%
27,677
34,747
41,818
103,881
287,679
471,477
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In SWEEP’s projections, the total number of electric vehicles in the High EV adoption
rate scenario represents 1.0% of all light-duty vehicles in Colorado in 2015 (4.2 million
vehicles) and 10.2% in 2025 (4.7 million vehicles).
To determine forecasts of the numbers and distribution of EV charging stations in
Colorado, iCAST used SWEEP’s projections of the total number of electric vehicles as
target values and mapped EV ownership across Colorado based on demographic
profiles of EV owners, census data, demographic projections, and growth rates. This
mapping process produced slightly different projections of EV ownership rates in
Colorado. iCAST used the new projections and mapping information to determine the
numbers and distribution of EV charging stations according to each location category
(home, work, or public). iCAST assumed that there will be one home-based charging
station for each electric vehicle, one public charging station for every five EVs, and one
work-based charging station for every ten EVs. Table 8 shows the total number of
home, work, and public charging stations (EVSE) in Colorado that were mapped for this
report.
Table 8: Total projected number of EV charging stations in Colorado
2015
Low
Total # of EVSE
34,705
Medium
42,960
2025
High
52,364
Low
128,852
Medium
356,977
High
581,662
4 Charging Station Projections of Numbers and Distribution by
Location Category
This section describes the results and methodologies used to forecast the regional
numbers and distribution of charging stations by year, location category (home, work,
and public) and projection scenario (low, medium, and high). Starting with the
projections of the total number of electric vehicles from SWEEP, iCAST developed a
methodology to map the projected distribution of EV ownership across Colorado on a
regional basis along with the corresponding supply equipment for each location
category. The methodology is based on research that indicates that owners of plug-in
electric vehicles, including BEVs and PHEVs, will match the demographic profile of
early adopters of hybrid electric vehicles. The research also indicates that, for every 100
plug-in electric vehicles, there will be 100 homes with charging stations and, on
average, 10 private commercial charging stations, and 20 public charging stations. This
report assumes those ratios will stay the same over the forecast periods, although
access to rapid charging stations in public locations is expected to be very limited in
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2015 since rapid charging technology is still in the process of standardization and
adoption by automakers. EV owners are expected to spend more time charging their
vehicles at work-based and public charging stations in 2025 than in 2015, especially as
the adoption of rapid charging technology increases, as indicated in Table 9.
Table 9: Estimated percentage of time electric vehicles spend charging in each location category
Charging Location
2015
2025
Home
75-95%
60-75%
Work
5-20%
15-35%
Public
0-5%
5-10%
The methodology developed by iCAST maps the projected distribution of the charging
stations for each location category and EV adoption scenario by census tract, Zip code,
and county, in accordance with the data sources for the projections. Forecast
calculations for 2025 combine county-level growth rate projections for population and
employment with the EV adoption rate projections, but 2015 forecasts apply EV
adoption rate projections to 2009 and 2012 census statistics without applying countylevel growth rate projections.
The methodology applied data from the following sources:






Demographic surveys from research institutions;
Business, employment, and demographic statistics from the U.S. Census and the
Colorado State Demography Office;
Voter registration data from the Colorado Secretary of State;
Vehicle registration data from the Colorado Department of Motor Vehicles;
Travel survey statistics from the Colorado Department of Transportation (CDOT)
and Federal Highway Administration; and
Various other statistics from CDOT, the Denver Regional Council of
Governments (DRCOG) and the Denver Regional Transportation District (RTD)
4.1 Allocation of Charging Stations by Location Category
Assumptions about the locations of charging stations heavily influence the projections of
the numbers and distribution of EVSE. Assumptions about the ratios of charging
stations among the household, work-based, and public charging station categories are
based on three primary sources.
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A report by Kurani et al16 indicates that the ability to charge electric vehicles at home is
an essential feature. Several other sources also indicate that most EV charging will
occur overnight at home. This report assumes that every electric vehicle will have an
associated home charging station, although no distinction is made between dedicated
electric vehicle supply equipment in the home and customers who simply plug in to a
wall outlet (AC Level I charging).
The U.S. Department of Energy’s Idaho National Laboratory has been collecting data
about EV charging station infrastructure and usage through projects such as the
ChargePoint America Program 17 . Data in the summary reports from this program 18
indicate that the ratio of the number of private commercial charging stations to the
number of electric vehicles in the dataset ranged from 8% to 12%. This report assumes
that there will be one private commercial (“work”) charging station for every 10 electric
vehicles and this ratio will remain constant over the forecasting period to 2025.
In a report by the California Energy Commission 19 , the California Public Utilities
Commission (CA PUC) states their assumptions for infrastructure planning purposes in
which two public charging stations will be installed per 10 electric vehicles. This report
uses the same ratio and assumes it will remain constant over the forecasting period.
Table 10 shows the projected number of charging stations by location category and
scenario as estimated by applying the above ratios to SWEEP’s EV sales projections.
iCAST used these numbers as target values to map the distribution of charging stations
16
Kurani, Kenneth S., Turrentine, Thomas and Daniel Sperling. 1996. “Testing Electric
Vehicle Demand in ‘Hybrid Households’ Using A Reflexive Survey” Transportation
Research Part D: Transport and Environment 1(2):131-150.
17
http://www.chargepointamerica.com/
18
http://avt.inl.gov/evproject.shtml
19
California Energy Commission, 2011. 2011-2012 INVESTMENT PLAN FOR THE
ALTERNATIVE AND RENEWABLE FUEL AND VEHICLE TECHNOLOGY PROGRAM,
Available at: http://www.energy.ca.gov/2011publications/CEC-600-2011-006/CEC-6002011-006-CMF.pdf [Accessed March 6, 2012].
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by location category across Colorado. The methodology used in mapping the
distribution of charging stations resulted in slightly different values for the number of
charging stations, shown in Table 11.
Table 10: Projected number of EVSE by location category, based on SWEEP’s EV sales
projections
2015
Low
Medium
2025
High
Low
Medium
High
Home
27,677
34,747 41,818 103,881 287,679 471,477
Public
5,535
6,949
8,364
20,776
57,536
94,295
Work
2,768
3,475
4,182
10,388
28,768
47,148
Total
35,980
45,171 54,364 135,045 373,983 612,920
Table 11: Total projected number of EVSE by location category, represented in the distribution
maps in this report
2015
Low
Medium
2025
High
Low
Medium
High
Home
28,120
34,766 42,392 104,026 288,156 471,507
Public
3,596
4,512
5,481
13,787
38,500
62,775
Work
2,989
3,682
4,491
11,039
30,321
47,380
Total
34,705
42,960 52,364 128,852 356,977 581,662
In the methodology developed by iCAST, the distribution of the projected number of
charging stations was determined by first mapping the estimated distribution of EV
ownership over the forecast period. This was calculated by applying a demographic
profile to census data to forecast the probability of EV ownership by census tract. The
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demographic profile was derived from a report by Scarborough Research 20 , which
characterizes owners of hybrid electric vehicles (HEV). This report assumes that,
throughout the forecast period, purchasers of plug-in electric vehicles will match the
demographic profile of HEV owners from the Scarborough report. The demographic
profile is summarized in Table 12.
Table 12: Demographic profile of HEV owners
Metric
21
Percentage Criteria
Income Level
42%
> $100,000
Education
56%
4-year college degree or higher
Age
55%
50 or older
Political Affiliation
38%
14%
34%
15%
Democrat
Republican
Independent
Unaffiliated
# of Vehicles
Most
2 or more
Physically Active
Most
Bicyclists and athletic club members
Once the projected distribution of EV ownership was forecasted by census tract,
information about projected travel patterns, commuting distances, and employment
densities was used to map commuting zones by Zip code around the areas of high EV
ownership. The projected distribution of charging stations was mapped by location
category according to the probability of EV ownership and employment in the
commuting zones, as well as the occurrence of public attractions, such as airports,
major highways, and state and national parks.
20
Scarborough Research. 2007. “Hybrid Vehicle Owners are Wealthy, Active, Educated,
Overwhelmingly Democratic, According to Scarborough Research”. Scarborough USA +
study, Release 1, 2007. http://scarborough.com/press_releases/Scarborough-HybridVehicle-Owner-Consumer-Profile.pdf.
21
Ibid.
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4.2 Distribution of Charging Stations at Home
In the methodology used to forecast the distribution of EV ownership, iCAST used the
demographic profile of hybrid vehicle owners from the Scarborough report to filter
demographic statistics and estimate the probability of electric vehicle ownership by
census tract. A threshold value was used to adjust the sensitivity of the data filter for
each EV adoption rate scenario to match the projected number of EV owners with the
EV sales projections developed by SWEEP.
Demographic statistics and growth projections were obtained from the U.S. Census
(2010 Census) and the State Demography Office (SDO) (2012 data) at the Colorado
Department of Local Affairs, and voter registration data were obtained from the
Colorado Secretary of State (2012 data).
According to the methodology, iCAST applied the percentages from the Scarborough
report to predict the census tracts with the highest occurrence of older, wealthy,
educated residents. For each of the 1,249 census tracts in Colorado, the number of
households with the appropriate income, education, and age were multiplied by the
corresponding percentages from the report. The least of the three resulting numbers
was selected for each tract. This number was multiplied by the percentage of Colorado
households with two or more cars, according to the 2010 U.S. Census. Next, the
resulting number was multiplied by the percentage of registered Democrats and
Democratic-leaning independents, the percentage of Republicans and Republicanleaning independents, and the percentage of all independent and unaffiliated voters.
The percentages of registered voters were added together to obtain a probability value
for each census tract. A threshold value was chosen for each EV adoption rate scenario
(low, medium, and high) to match closely the total calculated number of EV owners with
the total number of projected owners from SWEEP. If the probability value for a
particular census tract was smaller than the threshold value, that tract was assumed to
contain no EV owners.
This methodology was used to forecast the distribution of EV ownership and
corresponding household EVSE by census tract to 2015. For the 2025 forecast, annual
demographic data from the State Demography Office for years 2000 to 2010 were used
to predict population growth for each county to 2025. This county growth rate was
applied to each census tract and the methodology was repeated using the 2025
projections from SWEEP. This methodology could not calculate enough EV owners for
the 2025 High scenario. Consequently, iCAST added data for 2010 county-level hybrid
vehicle registrations from CDOT to forecast the distribution of EV owners and
household EVSE for the 2025 High scenario on a county-level basis only. For the 2025
iCAST
P a g e | 16
Task 21
Final Report
projections, if population growth-rate projections were negative, it was assumed the
number of EV owners would be the same as 2015.
4.3 Distribution of Charging Stations at Work
The projected distribution of private commercial charging stations was determined by
forecasting employee density by Zip code and mapping commuting zones around the
projected distribution of household charging stations.
Data on the average commuting distances were obtained from the 2009 National
Household Travel Survey by the Federal Highway Administration and the 2010 data
from the Front Range Travel Counts survey from the Colorado Department of
Transportation. The CDOT data was acquired from DRCOG. The average commuting
distances are summarized in Table 13. The average commuting distance for the Front
Range was applied to Zip codes in Front Range counties and the average commuting
distance for the U.S. was used for other counties in Colorado.
The projected distribution of business establishments was based on 2009 data from the
Zip Code Business Patterns database of the U.S. Census Bureau 22 . Employment
projections and distribution data used in the 2025 projections were obtained from the
2011 dataset of the State Demography Office at the Colorado Department of Local
Affairs23.
The distribution of private commercial charging stations by Zip code and commuting
zone is based on the distribution of household charging stations by census tract. County
boundaries coincide with census tract boundaries but Zip code boundaries and
commuting zones do not. The statistical contribution from the Zip code that overlapped
the county or commuting zone boundaries was allocated according to the proportional
area of the Zip code in the corresponding boundaries. The business and employment
statistics were used to forecast the probability value for private commercial charging
stations in each Zip code, which was then compared to a threshold value for each EV
adoption rate scenario. If the probability value for a particular Zip code was smaller than
22
http://www.census.gov/econ/cbp/
23
Colorado State Demography Office, The Economy and Labor Force, Economic
Forecasts. http://www.colorado.gov/cs/Satellite/DOLA-Main/CBON/1251593349151
iCAST
P a g e | 17
Task 21
Final Report
the threshold value, that Zip code was assumed to contain no workplace charging
stations.
Similarly to the 2025 projections for the distribution of household charging stations,
2025 projections for the distribution of private commercial charging stations included
employment growth projections by county from the 2012 dataset from the State
Demography Office24. These growth projections were used to forecast the number of
employees by Zip code for 2025, but not for 2015, which applied the target numbers to
the 2009 Zip Code Business Patterns data.
Table 13: Average commuting distances collected by various Colorado Metropolitan Planning
Organizations (MPOs)
Location
US
North Front
Range MPO
Denver
(DRCOG)
Pikes Peak
Area (PPACG)
Pueblo
(PACOG)
Average Front
Range
Miles25
12.09
8.2
8.2
7.0
6.8
8.0
Information Source
Highlights of the 2009
National Household
Travel Survey (NHTS)
Front Range Travel
Counts survey data
Front Range Travel
Counts survey data
Front Range Travel
Counts survey data
Front Range Travel
Counts survey data
Front Range Travel
Counts survey data
Details
p.48 Table 2726
From 6/20/2011 Media Release
written by Kitty Clemens27
From 6/20/2011 Media Release
written by Kitty Clemens28
From 6/20/2011 Media Release
written by Kitty Clemens29
From 6/20/2011 Media Release
written by Kitty Clemens30
From 6/20/2011 Media Release
written by Kitty Clemens31
24
Ibid.
One-way commuting distance in miles
26
http://nhts.ornl.gov/2009/pub/stt.pdf
27
Media release acquired from Suzanne Childress of DRCOG via email
28
Ibid
29
Ibid
30
Ibid
31
Ibid
25
iCAST
P a g e | 18
Task 21
Final Report
4.4 Distribution of Charging Stations at Public Attractions
Public attractions were defined using data from the Front Range Travel Counts survey
data about trip purpose and duration of time parked, which is also called dwell time (
iCAST
P a g e | 19
Task 21
Final Report
Table 14). Although this data only represents residents of DRCOG territory, it is
assumed that their trip purposes and durations were applicable to all of Colorado. Trip
purposes were translated into locations. Only trips with adequate average dwell times to
charge a Nissan Leaf using rapid charging32 were deemed sufficient to warrant the use
of an EVSE. Trip purposes were ignored if they lacked a definable destination.
32
Dwell time of more than 24 minutes, based on the time needed to charge 80% of the capacity
of a 24 kWh battery bank using Level 3 DC fast charging.
iCAST
P a g e | 20
Task 21
Final Report
Table 14: Trip purpose, percentage of total trips and duration of trips from Front Range Travel
Counts survey
Trip Purpose
% of Total Vehicle
Trips
Average Dwell Time per
Purpose (Minutes)
Working at home
1.57%
565.6
Shopping (online, phone, etc.)
0.05%
563.0
Online School Activities
0.12%
517.8
All other Home Activities
32.44%
443.0
Attending Class
0.91%
403.5
Other Specify
0.13%
388.5
Work/Job
13.85%
385.3
Loop Trip
0.03%
346.3
All other School Activities
0.10%
203.8
Visit Friends/Relative
2.58%
179.2
Work/Business Related
4.90%
149.0
All other Activities at Work
0.47%
113.3
Outdoor Rec/Entertainment
0.92%
110.3
Indoor Rec/Entertainment
3.64%
108.5
Personal Business
2.57%
105.6
Civic/Religious Activities
0.98%
104.4
Health Care
2.23%
85.9
Eat Outside of Home
4.10%
59.3
Shopping for Major Purchases
1.11%
33.8
Routine Shopping
9.82%
31.8
Household Errands
4.06%
21.5
Service Private Vehicle
1.47%
16.7
Other Activities While Traveling
0.10%
12.7
Picked Up Passenger
4.45%
10.9
Change Type of Transportation
0.98%
7.8
Drop off Passenger from Car
4.97%
6.7
Drive-Through
1.46%
6.2
iCAST
P a g e | 21
Task 21
Final Report
Table 15 lists the location categories that were selected as potential EVSE sites based
on suitable dwell times. The projected number of EVSE at each location category is
calculated from the percent of total vehicle trips. The Transit category was added to the
selected location categories to acknowledge the utility of having EVSE in places where
a driver can switch transit modes such as parking at an airport or parking at a park-nride. Transit received a similar percentage allocation of EVSE as the other categories
with low percentages (6%).
Table 15: Percentages and projected number of public charging stations in Colorado according to
trip purpose
2015
% of
EVSE
Shopping
Low
Medium
2025
High
Low
Medium
High
41%
1,482
1,857
2,257
5,661
15,825
25,776
4%
144
180
219
551
1,540
2,511
17%
611
767
932
2,344
6,545
10,672
Parks
4%
144
180
219
551
1,540
2,511
Health Care Facilities
9%
324
406
493
1,241
3,465
5,650
Civic and Religious
Organizations
4%
144
180
219
551
1,540
2,511
15%
539
677
822
2,068
5,775
9,416
6%
208
263
319
818
2,271
3,729
100%
3,596
4,512
5,481
13,787
38,500
62,775
Schools
Restaurants
Indoor Entertainment
Transit
Total
For all but two categories, the number of Colorado establishments by NAICS code, from
the 2009 Business Patterns Survey, were used to determine the number of
establishments in a certain zip code. For example, the NAICS categories, 44-45: Retail
Trade, were used to define the number of shops or retail establishments. The total
number of Shops EVSE were allocated to a particular zip code for each scenario by the
percentage of retail establishments in the zip code relative to all zip codes in Colorado.
Other relevant NAICS codes were identified for all categories except parks and transit
(Table 16).
iCAST
P a g e | 22
Task 21
Final Report
Table 16: Public Attractions categories and relevant NAICS codes from 2009 Zip Code Business
Patterns
NAICS
codes
Shops
44-45
NAICS code names
Retail Trade
Schools
61
Educational Services
Restaurants
72
Accommodation & Food Services
Health Care
Facilities
62
Healthcare
Civic and
Religious
Organizations
813
Religious; Political; Professional; Civic and Social;
and Social Advocacy organizations etc.
Indoor
Entertainment
71
Arts Entertainment Recreation
For the parks category, visitation numbers for National Parks in Colorado33, per vehicle
expenditures, and total expenditures for 2008 to 2009 in areas near Colorado State
Parks34 were used to roughly identify the number of vehicles visiting state parks. The
National Parks visitation data for 2009 was used instead of 2011 or 2012 (the most
recent data available) in order to better match the available state parks information. The
Mean Vehicle occupation for Social/Recreation purposes of 2.21 persons per vehicle
from the 2009 National Household Travel Survey was used to convert the National
Parks visitation statistics into number of vehicles visiting National Parks. The zip code of
each park was identified by their main mailing address. Parks EVSE were allocated by
the percentage of vehicles visiting a particular zip code relative to total visitation of state
and national parks in all zip codes in Colorado.
For the transit category, all available information was utilized. Transit EVSE can be
divided into three categories, highways, park-n-rides, and airports. Each of these
categories, had visitor or usage information available. Transit EVSE was assumed to
be located along Colorado highways, from interstates to local (Figure 1). Highway
33
http://www.nature.nps.gov/stats Reports tab YTD State Reports
Corona Research. COLORADO STATE PARKS MARKETING ASSESSMENT VISITOR
SPENDING ANALYSIS, 2008-2009 Available from parks.state.co.us
34
iCAST
P a g e | 23
Task 21
Final Report
mileage information and road types for Colorado came from CDOT 35 . It was assumed
that drivers would need to stop and recharge when their batteries were at 10% capacity.
Based on the Nissan Leaf, that is approximately every 63 miles. For the CDOT Function
Classes of roads 1 to 7, 144 Highway EVSE are required for the entire state of Colorado.
It is beyond the scope of this analysis to suggest actual sites for where these EVSE
would be located on Colorado highways. However, these highway EVSE can be
analogous to highway rest stops. The suggested distance between highway EVSE
roughly correlates to the average distance between Colorado rest stops, which is 50
miles 36. Additionally, if a driver was more cautious, they might stop earlier at 75%
battery capacity which would correspond to 52.5 miles. Every scenario was assumed to
have the same highway EVSE.
35
http://apps.coloradodot.info/dataaccess/GeoData/index.cfm?fuseaction=GeoDataMain&Menu
Type=GeoData Statewide Data Set selection Highways
36
Colorado average distance between rest stops provided by Mike Salisbury of SWEEP
iCAST
P a g e | 24
Task 21
Figure 1: Colorado Highway Functional Classes 1 (Interstate) to 7 (Local)
Final Report
37
Parking spaces at airports and park-n-rides were analyzed together. Park-n-ride
information such as the number of parking spaces available came from RTD 38 and
CDOT39. Only those park-n-rides that included parking information were included in the
analysis (88 park n rides total). Airport locations and their annual number of flights came
from CDOT40 . Annual flight numbers were converted into daily flight numbers. Since for
every EV, 0.2 public attraction EVSE are needed, 0.2 of park-n-ride spaces and 0.2 of
daily flight passengers require charging locations. No information was available on the
37
http://apps.coloradodot.info/dataaccess/GeoData/index.cfm?fuseaction=GeoDataMain&Menu
Type=GeoData Statewide Data Set selection Highways
38
http://www.rtd-denver.com/AlphabeticalList.shtml
39
http://www.coloradodot.info/travel/parknride
40
http://apps.coloradodot.info/dataaccess/GeoData/index.cfm?fuseaction=GeoDataMain&Menu
Type=GeoData Statewide Data Set selection Airports, airport zip codes came from airnav.com
iCAST
P a g e | 25
Task 21
Final Report
number of passengers on each flight, so the most conservative assumptions were made
which may slightly underestimate EVSE needs at airports. Conversely, this assumption
may slightly overestimate needs for EVSE at park-n-rides. The actual numbers of
Transit EVSE located by type can be seen in Table 17.
Table 17: Transit EVSE projections and categories
2015
Low
Medium
2025
High
Low
Medium
High
Highway
144
144
144
144
144
144
Airports
13
24
36
143
461
782
Park-n-Rides
51
95
139
531
1,666
2,803
Total Transit
EVSE
208
263
319
818
2,271
3,729
For 2025, the same approach used for work EVSE was used for the public attraction
EVSE. The number of establishments was assumed to increase or decrease according
to employment growth projections by county provided by the Colorado State
Demography Office 41. Zip code regions, unlike census tracts, do not directly correspond
to county boundaries. The growth percentage for employment for each zip code was
assigned from a single county or was assigned from an equal percentage from each
county that the zip code resided in. In summary, the growth percentages for zip codes
that lie in multiple counties are less accurate than the findings for zip codes that reside
in a single county. For the 2025 analysis, the growth percentages for each zip code
were multiplied by the number of establishments in each zip code to predict the 2025
number of establishments by zip code. Therefore, Colorado State Demography Office
growth projection numbers for employment were assumed to apply to the growth of
businesses (number of establishments) as well. This information was used because it
was the most relevant Colorado specific information found. Some zip codes had an
increasing number of establishments and thus increasing numbers of workplace EVSE,
and some had decreasing numbers of establishments and thus decreasing numbers of
41
Colorado State Demography Office Labor Force Supply and Demand
http://www.colorado.gov/cs/Satellite/DOLA-Main/CBON/1251593349151
iCAST
P a g e | 26
Task 21
Final Report
EVSE. However, all 2025 scenarios include the public attractions EVSE located in the
2015 scenarios.
5 Distribution Maps of Charging Station Projections by Census
Tract, Zip Code and County
This section shows the number of EVSE by type (Home or Household, Work or
Workplace, and Public Attractions) and by location in map figures. The maps are also
included in a larger size as appendices in separate pdf documents. The tables showing
numbers of EVSE by county and type are also available in Appendix D.
5.1 Current EVSE Locations in Colorado
Below, all currently known, publicly available EVSE in Colorado are mapped. In addition,
the 70-mile reach from these charging stations is included to show how far an EV driver
could get to or from these stations (Error! Reference source not found.). The data for
this map came from several sources. The Alternative Fuels & Advanced Vehicles Data
Center in the US Department of Energy keeps a list of alternative fueling stations for
vehicles, including EVSE, for each state42. Google Maps has created a category called
“Electric Vehicle Charging Station43. Several other charging stations were brought to
attention through conversations with a representative from Eaton44, a manufacturer of
EVSE.
Other sources of information for finding EVSE in Colorado that are not included are
carstations.com and plugshare.com. Their information is not available in an easily
downloadable form for the entire state of Colorado, although they both do have
smartphone applications, which make it easy for a driver to find an EVSE while on the
go. The ChargePoint Network also has a variety of information available about EVSE
that use its information technology across the country45.
42
http://www.afdc.energy.gov/afdc/fuels/electricity_locations.html
maps.google.com search term “Category: Electric Vehicle Charging Station”
44
David E. Altman, Government Sales Engineer for Eaton EVSE
45
http://www.chargepoint.net/
43
iCAST
P a g e | 27
Task 21
Final Report
6 Conclusions
This report develops projections of the numbers and distribution of electric vehicle
charging stations in Colorado for the years 2015 and 2025 for low, medium, and high
EV adoption rate scenarios. The projected distribution of EVSE is divided into three
categories: home, work, and public charging stations, and mapped by county, Zip code,
and census tract.
Forecasts of the numbers and distribution of EVSE can be used to develop an EVSE
implementation plan and estimate the requirements for grid upgrades, coordinate
transportation strategies, and aid in developing EV incentive programs on a local or
regional basis. A well-designed EVSE implementation plan could enable increased EV
adoption rates by increasing public awareness of, and access to EVSE in public and
commercial locations. Local planning agencies could use the forecasted EVSE numbers
and locations in this report to develop program budgets and incentive levels for EVSE
installations, and develop supportive policies and regulations to promote and ensure
access to EVSE. Planning agencies may also estimate the impacts of the EVSE
implementation plan on jobs, economic development, traffic patterns, PEV markets,
electric utilities, and EV charging service providers such as retailers. Private commercial
property owners may work with the planning agencies to determine appropriate
numbers of EVSE for their locations. Planning agencies and commercial developers
may also use this information to coordinate with EVSE technology providers and
installers for developing program budgets, specifying charging station technologies for
different location categories, and micro-siting charging station locations. Car dealers
may coordinate with the planning agencies to promote EV sales.
EV and EVSE technologies are considered to be in the early adoption stage and
developing rapidly, especially with respect to vehicle range and rapid charging
technologies and standards, which could have the greatest impact on EV adoption rates
and requirements for grid upgrades. The large uncertainties inherent in predicting
technological advancement translate into the wide differential in EV sales projections
and the corresponding number of charging stations in 2025. The low scenario for 2025
represents an optimistic baseline projection with high oil prices, while the high scenario
represents an aggressive forecast that requires supportive policies and EV market
stimulus.
In all scenarios, household charging stations comprise at least 80% of all EVSEs, but no
distinction is made of how many of those will include dedicated EV supply equipment,
whereas most owners may simply plug in to a standard electrical outlet. Most of the
charging stations are projected to be distributed along the I-25 and I-70 corridors and
iCAST
P a g e | 28
Task 21
Final Report
concentrated in the nine-county territory of the Denver Regional Council of
Governments.
Projections of the numbers and distribution of public and work-based charging stations
are most important for the purposes of public planning. Combined projections of public
and work-based charging stations in Colorado range from 6,600 to 10,000 in 2015, and
25,000 to 110,000 in 2025.
Of particular interest in this project is the forecasted number of public charging stations
based on trip purpose, presented in Table 18. These forecasts are derived from data in
the Front Range Travel Counts survey, provided by DRCOG. The projections are based
on trip frequency by purpose, dwell time, and other assumptions, as described in
section 4.4. The estimates in Table 18 assume that public charging stations will
primarily utilize a technology like DC fast charging (DCFC) that will charge an electric
vehicle to 80% of capacity in under 30 minutes. This assumption may be too optimistic
for 2015 since fast charging technology is still in the process of standardization and
adoption by automakers, and access to rapid charging stations may be very limited.
Table 18: Percentages and projected number of public charging stations in Colorado according to
trip purpose
2015
% of
EVSE
Shopping
Low
Medium
2025
High
Low
Medium
High
41%
1,482
1,857
2,257
5,661
15,825
25,776
4%
144
180
219
551
1,540
2,511
17%
611
767
932
2,344
6,545
10,672
Parks
4%
144
180
219
551
1,540
2,511
Health Care Facilities
9%
324
406
493
1,241
3,465
5,650
Civic and Religious
Organizations
4%
144
180
219
551
1,540
2,511
15%
539
677
822
2,068
5,775
9,416
6%
208
263
319
818
2,271
3,729
100%
3,596
4,512
5,481
13,787
38,500
62,775
Schools
Restaurants
Indoor Entertainment
Transit
Total
As an example of how the information in this report may be used, consider the map in
Figure 2 and the data in Table 19. The map in Figure 2 is color-coded to show the
projected density of public charging stations for the Low EV adoption scenario in 2025
iCAST
P a g e | 29
Task 21
Final Report
by Zip code. The number of public charging stations in Table 19 equates to 20% of the
projected number of EV owners in the corresponding county. If a local planning agency
in Arapahoe County, for example, chose to use the Low scenario for 2025
(corresponding to the EIA’s high fuel cost scenario) to develop an EVSE implementation
strategy, they could determine that they should plan for about 800 public charging
stations in the county. The high-resolution version of the map in Figure 2 would show
them how those stations should be distributed among zip codes in the county. The
ratios in the second column of Table 18 would indicate how the charging stations should
be distributed by trip purpose. For example, 48 public charging stations (6% of 800)
would be allocated in the implementation plan for Park-n-Rides, especially in the
western portion of the county. Similarly, public charging stations could be allocated for
other types of public locations, such as shopping malls, schools, and movie theaters.
The planning agency may then coordinate micro-siting, promotional marketing,
installation strategies, budgets, and incentives according to the allocation of the
charging stations.
iCAST
P a g e | 30
Task 21
Final Report
Figure 2: Public Charging Stations in Colorado by Zip Code for 2025 Low Scenario (Appendix AD)
Table 19: Numbers of Public Charging Stations by County
County Name Low
339
Adams
3
Alamosa
209
Arapahoe
6
Archuleta
0
Baca
8
Bent
iCAST
Public Attractions
2015
2025
Med High Low Med
428
518 1311 3669
4
4
12
36
256
317
798 2232
8
9
24
67
0
0
0
0
10
12
28
79
High
5630
58
3668
109
0
128
P a g e | 31
Task 21
Boulder
Broomfield
Chaffee
Cheyenne
Clear Creek
Conejos
Costilla
Crowley
Custer
Delta
Denver
Dolores
Douglas
Eagle
Elbert
El Paso
Fremont
Garfield
Gilpin
Grand
Gunnison
Hinsdale
Huerfano
Jackson
Jefferson
Kiowa
Kit Carson
Lake
La Plata
Larimer
Las Animas
Lincoln
Logan
Mesa
Mineral
iCAST
262
73
20
0
29
0
20
0
0
12
852
0
259
46
23
383
8
31
9
87
7
0
0
0
284
0
0
4
73
123
4
0
0
67
0
Final Report
Public Attractions
2015
2025
325
395
993 2762
4530
92
112
295
827
1359
27
31
75
208
342
0
0
0
0
0
36
44
111
316
518
0
0
0
0
0
24
29
76
214
350
0
0
0
0
0
0
0
0
0
0
15
16
41
118
192
1076 1304 3251 9109 14949
0
0
0
0
0
324
399
993 2760
4537
58
72
183
513
832
29
36
86
242
399
481
577 1502 4184
6867
10
12
30
88
143
35
43
108
302
492
12
15
37
109
178
108
130
324
900
1472
10
10
32
90
149
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
352
427 1041 2904
4768
0
0
0
0
0
0
0
0
0
0
5
6
11
34
56
90
110
275
756
1239
154
189
489 1347
2214
6
6
15
43
71
0
0
0
0
0
0
0
0
0
0
88
104
247
691
1133
0
0
0
0
0
P a g e | 32
Task 21
Moffat
Montezuma
Montrose
Morgan
Otero
Ouray
Park
Phillips
Pitkin
Prowers
Pueblo
Rio Blanco
Rio Grande
Routt
Saguache
San Juan
San Miguel
Sedgwick
Summit
Teller
Washington
Weld
Yuma
17
2
6
11
0
5
21
12
20
0
2
0
0
9
4
0
19
0
55
15
0
145
12
Public Attractions
2015
2025
21
27
63
177
2
3
9
27
9
10
20
56
14
18
41
114
0
0
0
0
8
9
25
69
25
31
82
233
15
18
46
127
27
36
89
253
0
0
0
0
5
6
13
39
0
0
0
0
0
0
0
0
12
15
38
107
4
7
17
50
0
0
0
0
22
28
72
197
0
0
0
0
67
82
204
560
19
24
57
158
0
0
0
0
184
223
580 1612
15
17
43
121
Final Report
292
43
92
189
0
115
380
209
414
0
62
0
0
173
81
0
320
0
918
261
0
2648
195
7 Resources Cited
Alternative Fuels & Advanced Vehicles Data Center, 2011. Federal & State Incentives &
Laws. Available at: http://www.afdc.energy.gov/afdc/laws/laws/HI/tech/3270 [Accessed
March 5, 2012].
Bohn, T., 2012. Plug-in Electric Vehicle (PEV) Standards, Upcoming PEVs/Features,
Charging System Overview.
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California Energy Commission, 2011. 2011-2012 INVESTMENT PLAN FOR THE
ALTERNATIVE AND RENEWABLE FUEL AND VEHICLE TECHNOLOGY PROGRAM,
Available at: http://www.energy.ca.gov/2011publications/CEC-600-2011-006/CEC-6002011-006-CMF.pdf [Accessed March 6, 2012].
CHAdeMO, 2010. CHAdeMO Chargers. Available at: http://www.chademo.com/
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Deloitte Consulting LLP, 2010. Gaining Traction: A Customer View of Electric Vehicle
Mass Adoption in the U.S. Automotive Market, Available at:
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DRCOG, 2011. 2035 Metro Vision Regional Transportation Plan. Figure 5. Available at:
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Electric Transportation Engineering Corporation (eTec), 2010. Long-Range EV
Charging Infrastructure Plan for Tennessee, Phoenix Arizona. Available at:
http://www.theevproject.com/downloads/documents/Long%20Range%20EV%20Chargi
ng%20Infrastructure%20Plan%20for%20the%20State%20of%20Tennessee%20Ver%2
04.1.pdf [Accessed March 5, 2012].
Friedman, Emily. “Colorado’s Climate, Landscape Helps Residents Stay Fit - ABC
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Heutel, G. & Muehlegger, E., 2010. Consumer Learning and Hybrid Vehicle Adoption,
John F. Kennedy School of Government, Harvard University. Available at:
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Kurani, K.S., Turrentine, T. & Sperling, D., 1996. Testing electric vehicle demand in
“hybrid households” using a reflexive survey. Transportation Research Part D:
Transport and Environment, 1(2), pp.131–150.
Office of Highway Policy Information (OHPI), 2010. FHWA Highway Statistics Series
2010 Table VM-2. Available at:
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2012].
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Scarborough Research, 2007. Hybrid Vehicle Owners are Wealthy, Active, Educated,
Overwhelmingly Democratic, According to Scarborough Research, Available at:
http://scarborough.com/press_releases/Scarborough-Hybrid-Vehicle-Owner-ConsumerProfile.pdf [Accessed March 5, 2012].
The EV Project & Ecotality, 2012. EV Project EVSE and Vehicle Usage Report: 4th
Quarter 2011, Available at:
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The EV Project, Idaho National Laboratory & Ecotality, 2012a. EV Project Chevrolet Volt
Vehicle Summary Report: October - December 2011, Available at:
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The EV Project, Idaho National Laboratory & Ecotality, 2012b. EV Project Nissan Leaf
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U.S. Census Bureau, 2012. State & County QuickFacts. Available at:
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2011. “Majority of Consumers Ready to Consider Buying Plug-in Electric Vehicles, But
Challenge Utilities with their Car Charging Demands, Accenture Study Finds” Accenture
Newsroom. http://newsroom.accenture.com/article_display.cfm?article_id=5205
2010. “The Electric Vehicle Study” Zpryme Research and Consulting and Airbiquity.
http://www.zpryme.com/SmartGridInsights/The_Electric_Vehicle_Study_Zpryme_Smart
_Grid_Insights_Airbiquity_Sponsor_December_2010.pdf
“Electric Vehicle Consumer Survey; Consumer Attitudes, Preferences, and Price
Sensitivity for Plug-in Electric Vehicles and EV Charging Stations” Pike Research 2012.
http://www.pikeresearch.com/research/electric-vehicle-consumer-survey
Colter, Aaron. 2011. “Green A Low Factor In Car Buying Decisions” Earth Techling.
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DeBolt, Daniel. 2011. “Despite ‘Range Anxiety,’ Electric Vehicle Owners Happy; How
Soon Will Global Warming Move the Tipping Point on Personal Transit?” Mountain View
Voice. http://mv-voice.com/news/show_story.php?id=4966
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Deloitte. 2010. “Gaining Traction: A Customer View of Electric Vehicle Mass Adoption in
the U.S. Automotive Market”. Deloitte Development LLC.
Ego Vehicles Inc. 2002. “Consumer Purchase Criteria for Personal Electric Vehicles”
Technical Note #60.
Flamm, Bradley and Asha Weinstein Agrawal. 2011. “An Investigation Into Constraints
to Sustainable Vehicle Ownership: A Focus Group Study” Mineta Transportation
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http://www.transweb.sjsu.edu/MTIportal/research/publications/documents/2903_1008.pdf
Gärling, Anita and John Thøgersen. 2001. “Marketing of Electric Vehicles” Business
Strategy and the Environment 10:53-65.
Gordon-Bloomfield, Nikki. 2011. “Ford Study: Gas Mileage Number One Criteria For
New Car Buyers” Green Car Reports.
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Gould, Jane and Thomas F. Golob. 1998. “Clean Air Forever? A Longitudinal Analysis
of Opinions About Air Pollution and Electric Vehicles” Transportation Research Part D:
Transport and Environment 3(3):157-169.
Groff, Garin. 2011. “E.V. Electric Vehicle Owners Say New Cars Exceed Expectations”
East Valley Tribune
http://www.eastvalleytribune.com/get_out/living_green/article_cfa528e0-e61d-11e090cb-001cc4c002e0.html
Kurani, Kenneth S., Turrentine, Thomas and Daniel Sperling. 1996. “Testing Electric
Vehicle Demand in ‘Hybrid Households’ Using A Reflexive Survey” Transportation
Research Part D: Transport and Environment 1(2):131-150.
Scarborough Research. 2007. “Hybrid Vehicle Owners are Wealthy, Active, Educated,
Overwhelmingly Democratic, According to Scarborough Research”. Scarborough USA +
study, Release 1, 2007. http://scarborough.com/press_releases/Scarborough-HybridVehicle-Owner-Consumer-Profile.pdf.
Sherlock, Tracy. 2012. “Owners of Electric Vehicle Charged up About Environment,
Lower Operating Costs; The Upfront Price Was High, But Couple Takes a Long-Term
View on Savings” The Vancouver Sun.
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http://www.vancouversun.com/cars/Owners+electric+vehicle+charged+about+environm
ent+lower+operating+costs/6129631/story.html
Turrentine, Tom, Garas, Dahlia, Lenta, Andy and Justin Woodjack. 2011. “The UC
Davis MINI E Consumer Study” Institute of Transportation Studies, University of
California Davis, Research Report.
http://pubs.its.ucdavis.edu/publication_detail.php?id=1470
Annual Energy Outlook. 2005. “Fuel Economy of the Light-Duty Vehicle Fleet”. Issues in
Focus, AEO2005.
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Environmental Protection Agency. 2010. “EPA Analysis of the Transportation Sector:
Greenhouse Gas and Oil Reduction Scenarios”
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Salisbury, Mike. “EIA Links.” Message to Abigail Clarke-Sather. January 25, 2012. Email.
Salisbury, Mike. “Scenario Question.” Message to Sarah Blok. February 3, 2012. E-mail.
SWEEP. Robert E. Yuhnke and Mike Salisbury. 2011. “Electric Vehicles Can Buffer
Colorado From The Economic Shocks Of Rising Fuel Prices, Create Jobs And Reduce
Pollution Control Costs”. Southwest Energy Efficiency Project. Colorado Public Utilities
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Analysis. “Annual Energy Outlook 2011, With Projections to 2025”. DOE/EIA0383(2011).
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7.1 Other Resources of Interest
Alternative Fuels & Advanced Vehicles Data Center: Location of EV charging stations
http://www.afdc.energy.gov/afdc/locator/stations/
US Department of Energy: Clean Cities program initiatives
http://www1.eere.energy.gov/cleancities/vehicle_competitions.html
http://www1.eere.energy.gov/cleancities/news_detail.html?news_id=18005
http://apps1.eere.energy.gov/news/daily.cfm/hp_news_id=298
http://www1.eere.energy.gov/vehiclesandfuels/
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