A national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

National Renewable Energy Laboratory 

Innovation for Our Energy Future 

Costs and Emissions 

Associated with Plug-In 

Hybrid Electric Vehicle 

Charging in the Xcel Energy 

Colorado Service Territory 

K. Parks, P. Denholm, and T. Markel

Technical Report 

NREL/TP-640-41410 

May 2007 

NREL is operated by Midwest Research Institute ● Battelle Contract No. DE-AC36-99-GO10337 
Costs and Emissions 

Associated with Plug-In 

Hybrid Electric Vehicle 

Charging in the Xcel Energy 

Colorado Service Territory 

K. Parks, P. Denholm, and T. Markel

Prepared under Task No. WR61.2001 

Technical Report 

NREL/TP-640-41410 

May 2007 

National Renewable Energy Laboratory

1617 Cole Boulevard, Golden, Colorado 80401-3393 

303-275-3000 • www.nrel.gov 

Operated for the U.S. Department of Energy 

Office of Energy Efficiency and Renewable Energy 

by Midwest Research Institute • Battelle 

Contract No. DE-AC36-99-GO10337
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Table of Contents 

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

2. Study Methods and Assumptions................................................................................ 2 

2.1 Utility System ........................................................................................................... 2 

2.2 Modeling................................................................................................................... 5 

2.3 Vehicle Assumptions................................................................................................ 6 

2.4 Vehicle Charging ...................................................................................................... 7 

2.5 Overall Vehicle Performance.................................................................................. 11

3. Results.......................................................................................................................... 12 

3.1 Net PHEV Load and Load Shape ........................................................................... 12 

3.2 Generation Source................................................................................................... 15 

3.3 Charging Costs........................................................................................................ 17 

3.4 Emissions................................................................................................................ 19

4. Conclusions.................................................................................................................. 23 

 iii
1. Introduction 

The combination of high oil costs, concerns about oil security and availability, and air 

quality issues related to vehicle emissions are driving interest in “plug-in” hybrid electric 

vehicles (PHEVs). PHEVs are similar to conventional hybrid electric vehicles, but 

feature a larger battery and plug-in charger that allows electricity from the grid to replace 

a portion of the petroleum-fueled drive energy. PHEVs may derive a substantial fraction 

of their miles from grid-derived electricity, but without the range restrictions of pure 

battery electric vehicles. 

As of early 2007, production of PHEVs is essentially limited to demonstration vehicles 

and prototypes. However, the technology has received considerable attention from the 

media, national security interests, environmental organizations, and the electric power 

industry.1,2 In 2006, the Bush administration announced the U.S. Advanced Energy 

Initiative, which includes the goal of developing a PHEV capable of traveling up to 40 

miles on a single electric charge.3

 For many U.S. drivers, a PHEV-40 could reduce 

average gasoline consumption by 50% or more.4

The economic incentive for drivers to use electricity as fuel is the comparatively low cost 

of fuel. The electric equivalent of the “drive energy” in a gallon of gasoline delivering 

25-30 miles in a typical midsized car is about 9-10 kWh, assuming a vehicle efficiency of 

2.9 mile/kWh.5 The cost of this electricity using the U.S. average residential rate for 2005 

(9.4 cents/kWh)6

 is under $1, and could be even less when using off-peak power at 

preferential rates. This cost is directly comparable to the end-user cost of gasoline, which 

nationally averaged $2.60 for regular-unleaded in the 12-month period ending August 

2006.7 Given these potential cost advantages, a study by the Electric Power Research 

Institute (EPRI) found a significant potential market for PHEVs, depending on vehicle 

cost and the future cost of petroleum.8 Furthermore, several researchers have noted that 

by adding “vehicle-to-grid” (V2G) capability, where the vehicle can discharge as well as 

charge, PHEV owners may also receive substantial revenue by using the stored energy in 

 

1

 “Plugging into the Future,” The Economist, June 8, 2006. Via 

http://www.economist.com/displaystory.cfm?story_id=7001862

2

 Plug-In Partners, via http://www.pluginpartners.com/ 3

 National Economic Council (2006) “Advanced Energy Initiative.” Via 

http://www.whitehouse.gov/stateoftheunion/2006/energy/ 4

 Electric Power Research Institute (2001). “Comparing the Benefits and Impact of Hybrid Electric Vehicle 

Options,” EPRI, Palo Alto, Calif., 10003496892. 

5

 Electric Power Research Institute (2001). 

6

 U.S. Department of Energy (2006). Annual Energy Outlook September 2006 With Data for June 2006, 

DOE/EIA-26(2006/09), Energy Information Administration, Washington, D.C. Via. 

http://www.eia.doe.gov/cneaf/electricity/epm/epm_sum.html 7

 Energy Information Agency “Retail Gasoline Historical Prices” 

http://www.eia.doe.gov/oil_gas/petroleum/data_publications/wrgp/mogas_history.html

8

 Electric Power Research Institute, 2002. “Comparing the Benefits and Impacts of Hybrid Electric Vehicle 

Options for Compact Sedan and Sport Utility Vehicles,” EPRI, Palo Alto, Calif., 1006891 

 1
their vehicles to provide high-value electric system services such as regulation, spinning 

reserve, and peaking capacity.9,10

The use of PHEVs would represent a significant potential shift in the use of electricity 

and the operation of electric power systems. Electrification of the transportation sector 

could increase generation capacity and transmission and distribution (T&D) 

requirements, especially if vehicles are charged during periods of high demand. Other 

concerns include emissions impacts including regulated emissions (NOX and SO2) and 

currently unregulated greenhouse gas emissions. Utilities are interested in the net costs 

associated with this potential new load, including possible benefits of improved system 

utilization enabled by controlled PHEV charging. 

This study is designed to evaluate several of these PHEV-charging impacts on utility 

system operations within the Xcel Energy Colorado service territory. We performed a 

series of simulations in which the expected electricity demand of a fleet of PHEVs was 

added to projected utility loads under a variety of charging scenarios. The simulations 

provide some basic insight into the potential grid impacts of PHEVs, focusing on the 

following issues: 

• How do various PHEV-charging scenarios affect the total system load? 

• What are the emissions associated with PHEV charging, and what are the 

combined emissions from both generator and vehicle? How do these emissions 

compare to a conventional vehicle? 

• What are the marginal costs associated with PHEV charging? 

• What are the quantifiable system benefits associated with controlled PHEV 

charging? 

2. Study Methods and Assumptions 

2.1 Utility System 

The study area for this analysis is the Xcel Energy Colorado service territory. This utility 

serves about 55% of the state’s population including Denver and most of the surrounding 

suburbs. 

This analysis used data from a variety of public sources, along with proprietary system 

data from Xcel Energy Colorado (we considered generation capacity available in 2007). 

While it will likely be some time until PHEVs are deployed on a large scale, using 

current data allows for a “baseline” analysis with a high level of certainty, as opposed to 

a “future” analysis where the generation mix is less certain. 

 

9

 Kempton, W. and S. E. Letendre (1997). “Electric Vehicles as a New Power Source for Electric Utilities.” 

Transportation Research D 3: 157-175. 10 Kempton, W. and J. Tomic (2005). “Vehicle-to-grid power fundamentals: Calculating capacity and net 

revenue.” Journal of Power Sources 144(1): 268-279. 

 2
Table 1 provides a summary of the Xcel Energy service territory compared to the entire 

state. 

Table 1: Characteristics of the Xcel Energy Service Territory 

Xcel Energy Colorado 

Electricity Customers (2005)11 1,296,200 2,349,921 

Estimated Population (2000)12 2,347,000 4,301,000 

Annual Electricity Demand 

(GWh – year)13 26,481 48,353 

Estimated Number of Vehicles 

(2000)12 1,730,000 3,135,000 

Figure 1 illustrates the Xcel Energy service territory within Colorado, as well as the 

major power plants in Colorado operated by Xcel Energy. 

Figure 1: Xcel Energy Colorado Service Territory and Major Generation Facilities14

 

11 Energy Information Agency (2005), “Form EIA-861 Database” Via 

http://www.eia.doe.gov/cneaf/electricity/page/eia861.html 12 U.S. Census Bureau. “Annual Estimates of the Population for the United States, Regions, States, and for 

Puerto Rico: April 1, 2000, to July 1, 2006” (NST-EST2006-01) 

13 Energy Information Agency (2005), “Form EIA-861 Database” 

14 Xcel Energy “Power Generating Facilities – Colorado.” Via 

http://www.xcelenergy.com/XLWEB/CDA/0,3080,1-1-1_1875_4797_4010-3475-2_261_448-0,00.html 

 3
Xcel Energy’s electricity supply is dominated by fossil fuels, with small amounts of 

hydro and some wind. Figures 2 and 3 provide estimates of the current capacity mix and 

average energy supply for the entire state. 

Natural Gas

45%

Renewables

2%

Petroleum

2%

Hydroelectric

9%

Coal

42%

Figure 2: Distribution of Electric Generation Capacity within Colorado in 200515

Coal

71%

Hydroelectric

3%

Renewables

2%

Natural Gas

24%

Figure 3: Distribution of Electric Generation Energy, by Source, within Colorado in 200516

 

15 U.S. Department of Energy (2005). Electric Power Annual 2006, DOE/EIA-0348(2005), Energy 

Information Administration, Washington, D.C. Via 

http://www.eia.doe.gov/cneaf/electricity/epa/epat2p2.html 16 U.S. Department of Energy (2005). Electric Power Annual 2006, DOE/EIA-0348(2005), Energy 

Information Administration, Washington, D.C. Via 

http://www.eia.doe.gov/cneaf/electricity/epa/epat1p1.html

 4
2.2 Modeling 

To simulate charging of PHEVs in the Xcel Energy service territory, we used a model 

that simulates the dispatch and operation of an electric power system on an hourly basis 

for an entire year. This type of tool is commonly referred to as a “production cost,” “unit 

commitment and dispatch,” or “chronological dispatch” model.17

Production cost models use a forecast of hourly system loads, and optimally dispatch all 

generators available based on each generator’s variable cost. When calculating variable 

cost, the model considers fuel, O&M, and startup costs. The model also considers 

constraints of emissions permits, individual power plant performance limits including 

ramping rates and minimum loading, and transmission system limits. 

The particular tool used (PROSYM) was provided by Global Energy Decisions18 and is 

one of about four tools used by the nation’s utilities to simulate their systems. PROSYM 

includes an extensive database of most power plants in the United States, along with a 

reduced-form approximation of the transmission system. 

A base case model “run” involves dispatching the utilities’ power plant fleet to a forecast 

load, including projected wholesale purchases and sales. Once a base case is established, 

the modeled electric power system may then be redispatched to any number of scenarios 

desired. In this study, the additional load from PHEVs was added to the base load, and 

then the incremental generation associated with PHEV charging was identified, along 

with its associated cost and emissions. 

 

While PROSYM can produce a large number of outputs, we focused on the following 

parameters for this study: 

• Net System Load 

• Generation Mix 

• Fuel Cost 

• Variable O&M Cost 

• Additional Generator Startups and Startup Costs 

• CO2 Emissions 

• SO2 Emissions 

• NOX Emissions 

 

17 J.H. Eto. 1990. “An Overview of Analysis Tools For Integrated Resource Planning” Energy 15 (11) 969-

977. 

18 Global Energy Decisions. Via http://www.globalenergy.com/products-enerprise-overview.asp 

 5
2.3 Vehicle Assumptions 

There is considerable uncertainty regarding the most economical size and configuration 

of marketable PHEVs.19 A PHEV represents a tradeoff between various components 

including the battery size (both energy and power), electric motor size, and internal 

combustion (IC) engine size. The vehicle’s electric range20 is variable (PHEV-20, PHEV40, etc.) and so is the instantaneous fraction of drive energy derived from the battery. 

While the PHEV-20 nomenclature implies that the vehicle drives for the first 20 miles on 

electricity and then switches to gasoline, this clean switch from one mode of operation to 

the other is only one of several possible operating strategies. Another is “blended” 

operation where the electric motor supplies low-speed operation, supplemented by the 

combustion engine at high speed. With this mode of operation, the maximum power draw 

on the batteries and electric drivetrain is reduced, which reduces the cost of the hybrid 

vehicle system. The fraction of miles displaced by electricity for a specific PHEV size is 

also uncertain, given the significant variation in driving habits and PHEV operational 

modes. Figure 4 provides one estimate of the potential miles displaced by electricity for 

a variety of PHEV ranges, assuming a single charge per day.21 

0%

10%

20%

30%

40%

50%

60%

70%

80%

0 5 10 15 20 25 30 35 40 45 50 55 60

PHEV Electric Range (miles)

Fraction of Vehicle Miles from 

Electricity

Figure 4: Fraction of PHEV Miles Derived from Electricity 

We chose a midsize PHEV-20 for our base case vehicle. The vehicle design 

characteristics and performance were generated using the ADvanced VehIcle SimulatOR 

 

19 Markel, T.; O’Keefe, M.; Simpson, A.; Gonder, J.; Brooker A. (2005) “Plug-in HEVs: A Near-term 

Option to Reduce Petroleum Consumption FY05 Milestone Report,” National Renewable Energy 

Laboratory, Golden, Colorado, August 2005. 

20 The PHEV electric performance is designated by the nomenclature of “PHEV-XX”, with the XX 

representing the vehicles battery storage capacity in miles, such as PHEV-20. 

21 Electric Power Research Institute (2001). 

 6
(ADVISOR) tool,22 and are very close to those described in detail in a previous 

analysis.23 The actual performance of the vehicle fleet for this study is based on actual 

driving-pattern data from 227 vehicles tracked with a global positioning system (GPS) in 

St. Louis in 2002.24 The GPS data and vehicle simulations provide an estimate of total 

fleet miles traveled, electricity requirements, and gasoline consumption. An overall 

penetration of 500,000 vehicles was assumed, equal to roughly 30% of light-duty 

vehicles in the Xcel Energy service territory. Table 2 summarizes the fleet-average 

vehicle assumptions used in this study. 

Table 2: Assumed Vehicle Parameters 

Vehicle Size Conventional 

Vehicle (CV) 

Hybrid Electric 

Vehicle (HEV) 

Plug-In Hybrid 

(PHEV-20)25

Miles per Year 13,900 13,900 13,900 

Gasoline Mode Efficiency 26 mpg 36 mpg 37 mpg 

Electric Mode Consumption 

Rate 

NA NA 0.36 kWh/ mile 

Battery Size (Usable 

Capacity) 

0 2 kWh (charged 

from IC engine) 

7.2 kWh 

2.4 Vehicle Charging 

We developed four vehicle-charging scenarios for evaluation. The four scenarios chosen 

are not necessarily the most likely, but instead represent boundary cases and perhaps 

some probable charging scenarios. In each of the four scenarios, we developed an 

aggregated hourly charging profile for a fleet of vehicles. This hourly load was then 

added to the base case load to evaluate the incremental system impacts. The four 

scenarios, described in additional detail as follows, are summarized in Table 3. 

Case 1: Uncontrolled Charging 

The uncontrolled charging case considers a simple PHEV scenario where vehicle owners 

charge their vehicles exclusively at home in an uncontrolled manner. The PHEV begins 

charging as soon as it is plugged in, and stops when the battery is fully charged. This can 

be considered a reference or “do nothing” case, because it assumes a business-as-usual 

infrastructure requirement (no charging stations at work or other public locations). In 

addition, it requires no intelligent control of how or when charging occurs, or incentives 

(such as time-of-use rates) to influence individual consumer behavior. The case might 

 

22 T. Markel, A. Brooker, T. Hendricks, V. Johnson, K. Kelly, B. Kramer, M. O'Keefe, S. Sprik and K. 

Wipke, “ADVISOR: a systems analysis tool for advanced vehicle modeling,” Journal of Power Sources, 

Volume 110, Issue 2, August 22, 2002, Pages 255-266. 

23 Electric Power Research Institute (2001). 

24 Jeffrey Gonder, Tony Markel, Andrew Simpson, Matthew Thornton. “Using GPS Travel Data to Assess 

the Real World Driving Energy Use of Plug-in Hybrid Electric Vehicles (PHEVs).” (In Progress)

25 For a PHEV, the “Electric Mode” describes operation when the vehicle is using stored electricity as its 

“primary” driving energy source. “Gasoline Mode” is operation after the battery has been depleted to the 

point where the vehicle is operating essentially as a conventional hybrid. The actual performance depends 

largely on the driving profile and the amount of “blended mode” operation. 

 7
also be considered a boundary (worst-case) scenario, given the high coincidence of 

normal electric system loads and likely consumer vehicle-charging patterns. 

For this case, we assumed a constant charging rate of 1.4 kW, which is conservatively 

based on a common household 110/120 volt, 20A circuit, with a continuous rating of 

about 1.8-2.0 kW. Despite this low charging rate, the charge time for a completely 

discharged battery is still less than six hours. 

Figure 5 illustrates the daily charging profile, which ramps up rapidly from 4-6 p.m. at 

the end of the normal workday. The actual time that vehicles arrive home is based on the 

St. Louis vehicle data set, and we assume that driving patterns are not significantly 

different in the study region. Data for this study was available only for a weekday, so this 

study assumes weekend travel patterns are identical to weekday patterns. In this scenario, 

most charging occurs in the mid- to late evening, with little charging occurring after 

midnight. 

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour Ending

kW/100 Vehicles

Figure 5: Fleet Average Charging Profile in the Uncontrolled Charging Case 

Case 2: Delayed Charging 

The delayed charging case is similar to Case 1, in that all charging occurs at home. 

However, it attempts to better optimize the utilization of low-cost off-peak energy by 

delaying initiation of household charging until 10 p.m.26 This requires only a modest 

increase in infrastructure, i.e., a timer in either the vehicle or in the household charging 

station. This case is considered a more likely scenario than the uncontrolled charging, 

given existing incentives for off-peak energy use – many utilities (including Xcel Energy) 

already offer time-of-use rates to residential customers, and several California utilities 

 

26 “Off-peak” is generally defined as the period of relatively low electricity demand, typically during 

overnight hours. 

 8
have previously initiated special time-of-use rates for electric vehicles.27 The charging 

rate (1.4 kW) is identical to the uncontrolled case. 

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour Ending

kW/100 Vehicles

Figure 6: Fleet Average Charging Profile in the Delayed Charging Case 

Case 3: Off-Peak Charging 

The off-peak charging scenario also assumes that all charging occurs at home in the 

overnight hours. However, it attempts to provide the most optimal, low-cost charging 

electricity by assuming that vehicle charging can be controlled directly or indirectly by 

the local utility. This allows the utility to precisely match the vehicle charging to periods 

of minimum demand, allowing the use of lowest-cost electricity, and improving overall 

utility system performance. With direct control, the utility would send a signal to an 

individual vehicle or a group of vehicles to start or stop charging as conditions merit. 

Such a concept is already in place through other load-control programs used for water 

heaters, air conditioners, etc. The direct control could also be established through an 

aggregator that sells the aggregated demand of many individual vehicles to a utility, 

regional system operator, or a regional wholesale electricity market. 

An alternative option – indirect control – would have each vehicle responding 

intelligently to real-time price signals or some other price schedule to buy electricity at 

the appropriate time. In either control scheme, the vehicles would be effectively 

“dispatched” to provide the most economic charging and discharging. 

We developed a separate charging algorithm that dispatches vehicle charging and “fills 

the valley” of minimum overnight demand.28,29 All charging must be completed by 7 

a.m. 

 

27 Pacfic Gas & Electric. Via 

http://www.pge.com/docs/pdfs/about_us/environment/electric_vehicles/ev4pt2.pdf#search=%22pge%20ev

%20rate%22 

 9
To allow for maximum system optimization, we increased the allowable fleet average 

charge rate to 3.2 kW. This is greater than the continuous charge rate of a common 

household (120V) circuit, and assumes that at least 20% of all charging is on 240V 40A 

circuits. (These are also common household circuits used for heavy-duty appliances such 

as clothes dryers.) 

Unlike the previous cases, the daily charging load pattern is not constant in this case – it 

varies in accordance with the weekly and seasonal load pattern. Figure 7 illustrates the 

charging profile from one typical day in this case. 

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour Ending

kW/100 Vehicles

Figure 7: Fleet Average Charging Profile in the Off-peak Charging Case 

This case is essentially a boundary case to contrast to Case 1, representing a likely “leastcost” charging scenario. 

Case 4: Continuous Charging 

The continuous charging scenario is similar to Case 1, in that it assumes that charging 

occurs in an uncontrolled fashion (at 1.4 kW) whenever the vehicle is plugged in. 

However, it also assumes that public charging stations are available wherever the vehicle 

is parked. As a result, the vehicle is continuously charged whenever it is not in motion, 

(limited by the battery capacity). The advantage of this scenario is that it maximizes 

electric operation, and minimizes both petroleum use and vehicle emissions. 

 28 Ideally, the production cost model would itself optimally dispatch the vehicle charging. However, 

PROSYM’s optimization routines are based on a weekly dispatch instead of a 24-hour cycle. While 

PROSYM does include a pumped storage optimization routine, it was easier to perform the charging 

optimization in this separate routine. 

29 Denholm, P.; Short, W. (2006). “Evaluation of Utility System Impacts and Benefits of Optimally 

Dispatched Plug-In Hybrid Electric Vehicles.” NREL Report No. TP-620-40293. Via 

http://www.nrel.gov/docs/fy07osti/40293.pdf 

 10
 

Figure 8 illustrates the daily charging pattern in the continuous charging case. 

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour Ending

kW/100 Vehicles

Figure 8: Fleet Average Charging Profile in the Continuous Charging Case 

The charging pattern can be best understood starting at 4 a.m., when all vehicles are fully 

charged. Recharging begins after the morning commute and other morning activities, 

with the charging rate staying fairly uniform due to the large number of midday trips. 

Late-day charging peaks after the evening commute, but drops off more rapidly than in 

the uncontrolled charging case, because the midday charging results in a higher state of 

charge before the evening commute begins. As a result, there is even less off-peak 

charging than in the uncontrolled charging case. 

2.5 Overall Vehicle Performance 

The combined vehicle assumptions and charging scenarios describe the overall vehicle 

performance, including total electricity demand and gasoline consumption. Table 3

summarizes the vehicle parameters for the four PHEV charging cases, compared to nonplug-in vehicles. The first three charging cases are considered “once per day” charging 

scenarios, and produce the same average-vehicle electricity demand and miles driven 

electrically. With continuous charging, a much larger fraction of miles are driven 

electrically, because the battery is “topped off” at the end of each trip. 

 11
Table 3: Vehicle Performance Under Various Charging Scenarios 

Charging Scenario Conventional 

Vehicle 

HEV PHEV Cases 1-

3 (Charging 

Once per day) 

PHEV 

(Continuous 

charging)30

Miles from Electricity 

(Daily/Annual) 

0 0 14.6 / 5,356 19.9 / 7,260 

Percent of Miles from 

Electricity 

0 0 39% 52% 

Electricity 

Requirement (kWh) 

(Daily/Annual) 

0 0 5.3 / 1,944 9.4 / 3,530 

Annual Gasoline Use 

(gallons) 

535 386 237 145 

Annual Fuel Cost31 $1,375 $993 $778 $614 

The major benefit of PHEVs to owners (assuming no additional benefits from V2G 

operation) is the reduction in gasoline use and resulting reduction in operational costs. 

Compared to a base conventional vehicle, a PHEV can reduce gasoline consumption by 

more than 70%, given the availability of daytime charging. It is important to note that 

much of this efficiency gain is associated with the hybrid drivetrain. The annual gasoline 

savings associated with plug-in technology is equal to the HEV gasoline use minus the 

PHEV gasoline use, about 150 to 240 gallons per year using our vehicle assumptions. 

Assuming fuel prices of $2.57/gallon and 8.6 cents/kWh, the use of plug-in technology 

would save its owner from $200 to $450/year in fuel costs. 

3. Results 

Results were generated by first running a base case without PHEVs, and then running the 

individual PHEV cases. The difference between the base case and each PHEV scenario 

case establishes the net system impacts. Four general impact categories were examined: 

total electricity load and load shape, charging generation source, total charging costs, and 

emissions. 

3.1 Net PHEV Load and Load Shape 

The net PHEV loads provide a visual indication of the basic impacts on utility load 

patterns and provide some quantitative information such as the change in utility load 

factor, such as the need for additional capacity. 

 

30 The vehicle performance (fuel and electricity consumption rates) in the continuous charging case is 

slightly different than the performance described in Table 2. This is due to the increased use of blended 

mode operation made possible by continuous charging. 

31 Includes the cost of gasoline and electricity. Using the average price of gasoline for Denver in the year 

ending November 2006 ($2.57/gallon) and the average retail price of electricity during the same time 

periods (8.64 cents/kWh). The actual price of electricity purchased for vehicles is actually considerably less 

than this value since the average price includes fixed billing charges. Gasoline costs from 

http://www.eia.doe.gov/oil_gas/petroleum/data_publications/wrgp/mogas_history.html. Electricity costs 

from http://www.eia.doe.gov/cneaf/electricity/epm/table5_6_a.html. 

 12
Summer Load Impacts 

Like most of the United States, the Xcel Energy system peaks in the summer, driven by 

midday and early evening air-conditioning demand. Figure 10 illustrates summertime 

load patterns for three days, including the normal load and the load with PHEV charging. 

The overall annual peak occurs on day 3. 

3000

3500

4000

4500

5000

5500

6000

6500

7000

7500

0 12 24 36 48 60 7

Hour

Total System Demand (MW)

2

Continuous

Uncontrolled

Delayed

Off-Peak

Normal

Off-Peak

Continuous

Delayed

Uncontrolled

Figure 10: Summertime Load Patterns with PHEV Charging 

The uncontrolled and continuous charging cases add considerable load coincident with 

periods of high demand, and add to the peak capacity requirements. Delayed charging 

dramatically improves the situation by avoiding charging during the peak demands in late 

afternoon and early evening, while the optimal charging case fills the overnight demand 

minimum. As a result, delayed or optimal PHEV charging avoids any need for additional 

generation capacity. 

Winter Load Shape Impacts 

Figure 11 illustrates the impact of PHEV loading on wintertime demand patterns. 

Wintertime peak demand is driven largely by heating and lighting requirements. There is 

a strong evening demand peak, largely coincident with the time when PHEVs would 

begin charging in the uncontrolled charging scenario. As with the summer case, delayed 

charging and optimal charging avoids charging during the evening lighting peak. 

 13
3000

3500

4000

4500

5000

5500

6000

6500

7000

7500

0 12 24 36 48 60 7

Hour

Total System Demand (MW)

2

Continuous

Off-Peak

Delayed

Uncontrolled

Normal

Continuous

Uncontrolled

Off-Peak

Delayed

Figure 11: Wintertime Load Patterns with PHEV Charging 

Total Load Impacts 

The total impact of PHEVs on an annual basis can be observed in a load duration curve 

(LDC). An LDC is created by reordering the hourly demand data from greatest to least 

demand for all 8,760 hours in a year, and provides insight into the overall utilization of a 

utility’s power plant fleet. 

Figure 12 illustrates the LDCs for each of the four charging scenarios. 

 14
2500

3000

3500

4000

4500

5000

5500

6000

6500

7000

0 1000 2000 3000 4000 5000 6000 7000 8000

Hour

Total System Demand (MW)

Continuous

Uncontrolled

Delayed

Off-Peak

Normal

Continuous

Uncontrolled

Off-Peak

Delayed

Figure 12: System Load Duration Curve with PHEV Charging 

Figure 12 demonstrates that, on an annual basis, the uncontrolled charging and 

continuous charging cases require a large fraction of PHEV charging to occur during 

periods of moderate to high loads. The time-delayed and off-peak charging cases show an 

improvement in the distribution of additional charging. The majority of the increased 

load occurs in the lower demand region. A noticeable benefit of off-peak charging is the 

increased minimum load. 

Table 4 summarizes several of the load impacts resulting from the 500,000 PHEV 

scenario. 

 

Table 4: Impacts of Various Charging Cases on System Capacity and 

Energy Requirements 

Charging 

Scenario 

Increase in Total 

Load (%) 

Increase in Peak 

Demand (%) 

Uncontrolled 2.7 2.5 

Delayed 2.7 0 

Off-peak 2.7 0 

Continuous 4.8 4.6 

3.2 Generation Source 

Because PROSYM tracks each generation unit on an hourly basis, it is possible to 

determine exactly which generators would likely provide the incremental generation 

necessary for PHEV charging. Generators of each type (coal, gas combined cycle, etc.) 

 15
can be aggregated to provide a breakdown of the generator or fuel type providing energy 

for PHEVs.32

Figure 13 provides an estimate of the fraction of energy provided for incremental energy 

for each of the charging scenarios. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Uncontrolled Delay to 10pm Off-Peak Continuous

% of Energy from Generator Type

Simple Cycle

and Other Gas

Combined

Cycle Gas

Coal

Figure 13: Generation Mix Serving Additional Load of 500,000 PHEVs33 

In each case, the distribution graph represents the fractional source of energy for all 

PHEV charging. The marginal generation mix is the most important factor in both the 

overall charging costs and the net emissions. In this particular case, natural gas provides 

the marginal fuel more than 80% of the time, due to the particular characteristics of the 

current Xcel Energy system. It should be emphasized that the marginal fuel mix is very 

system dependent, and can change over time. While natural gas is “at the margin” for 

most of the West, coal may provide a greater fraction of the marginal fuel in the Eastern 

United States, especially during off-peak periods.34 While moving to off-peak charging in 

the Xcel Energy system allows a modest increase in coal use, the greatest benefit to 

delayed and off-peak charging cases is increased use of more efficient combined-cycle 

units. 

 

32 Certain resources such as wind and hydro are considered “must run” units, and do not contribute to the 

incremental generation requirements of PHEV charging. PHEVs could provide a dispatchable load that 

allows increased use of wind in the long term, but that application is not considered in this work. For 

additional discussion of this application, see: Short, W.; Denholm, P. (2006). Preliminary Assessment of 

Plug-in Hybrid Electric Vehicles on Wind Energy Markets. 41 pp.; NREL Report No. TP-620-39729. Via 

http://www.nrel.gov/docs/fy06osti/39729.pdf 33 “Other Gas” refers to reciprocating and steam units. 

34 Global Energy. Coal: America’s Energy Security Insurance. Global Energy Monthly Briefing, March 

2005. Via http://www.globalenergy.com/BR05/BR05-coal-americas.pdf 

 16
3.3 Charging Costs 

Figure 14 illustrates the incremental generation costs associated with vehicle charging 

for each of the four charging scenarios. Costs are broken out in the three evaluated 

categories: fuel costs, variable operation and maintenance (O&M), and unit starts. 

-$10

$0

$10

$20

$30

$40

$50

$60

$70

$80

Uncontrolled Delayed Off-Peak Continuous

$/MWh

Total Cost

Fuel Cost

Start Cost

VOM Cost

Figure 14: Incremental Cost of Electricity for PHEV Charging 

From the uncontrolled charging to the delayed charging cases, the reduction in fuel cost 

occurs by moving from lower efficiency units to higher efficiency combined-cycle units. 

Moving to the off-peak charging case reduces costs further by shifting some generation to 

coal units. The large fuel costs associated with continuous charging results from the 

extensive use of the low efficiency gas units. 

The actual decrease in cost associated with off-peak charging is limited in a system with 

natural gas at the margin during the majority of hours. Much greater cost savings are 

available in systems with available coal generation. The variable fuel cost associated with 

coal generation (assuming $1.60/mmBTU fuel and a 10,500 BTU/kWh heat rate) is 

$17/MWh. This value represents the potential lower bound of generation costs in an 

optimal charging scenario, excluding the additional benefits of avoided starts. 

The negative cost associated with avoided starts is an interesting benefit associated with 

PHEV charging. By filling the valley of overnight off-peak demand, PHEVs reduce the 

number of times plants must be shut down, only to be restarted in the morning. In the 

modeled scenarios, the change in power plant startups ranged from about 30 fewer 

 17
startups per month in the off-peak charging case to about 130 additional startups per 

month in the continuous charging case.35 This increases motivation for utilities to 

implement a program of off-peak vehicle charging. In addition to the lower fuel costs, the 

vehicle owner that allows for (or demands) utility-controlled charging incurs a system 

benefit of about 0.2 cents/kWh due to improved system performance. 

Figure 15 translates the cost of electric generation into more common vehicle 

equivalents. The cost of generating PHEV-charging electricity is somewhat analogous to 

the “wholesale” cost of gasoline, or the cost of producing electric fuel. Assuming the 

vehicle parameters in Table 2, a PHEV requires about 13 kWh to displace 1 gallon of 

gasoline used in an HEV. As a result, the electric equivalent of gasoline is produced for 

as little as 62 cents per gallon, equivalent to fuel costs of less than 2 cents per mile in the 

off-peak charging case. 

$0.00

$0.20

$0.40

$0.60

$0.80

$1.00

Uncontrolled Delayed Off-Peak Continuous

Electric "Gasoline" Production Cost ($/Gallon)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Electric Mode Fuel Production Cost (Cents/Mile)

Figure 15: PHEV Electric-Mode Fuel Production Costs 

The annual savings associated with moving from the uncontrolled charging to controlled 

charging scenarios could be compared with the cost of implementing charging-control 

technologies. Using previously stated vehicle assumptions, compared to uncontrolled 

charging, the annual benefit of delayed charging is about $23/vehicle, while off-peak 

charging reduces annual generation cost by about $44/vehicle. As mentioned before, the 

benefits of optimal charging in the Xcel Energy system are largely due to the efficiency 

gains associated with more efficient gas generation. The ability to switch from natural gas 

 

35 The ability to optimally control PHEV charging and limit power plant starts depends on a number of 

factors, including accurate forecasting of the amount of charge remaining in the PHEV fleet each evening. 

 18
to coal during off-peak hours could potentially double the annual savings associated with 

optimal charging.36 These values also can be expressed as an equivalent to a gasoline 

“discount” equal to about 15 cents per gallon for delayed charging, and about 29 

cents/gallon for off-peak charging, both compared to uncontrolled charging. 

It should be noted that all costs in this section are variable generation costs, and do not 

include the cost of transmission and distribution. The costs associated with PHEV 

charging also do not consider the capacity costs associated with increased peak demand. 

Both the uncontrolled charging case and the continuous charging case increases peak 

demand – about 0.3 kW per vehicle in the uncontrolled case and about 0.7 kW per 

vehicle in the continuous charging case. If PHEV owners were responsible for this 

incremental capacity, charging costs would increase. Alternatively, charging could be 

restricted during the few hours per year when PHEVs would add to peak demand. – 

about five hours/year in the uncontrolled charging case and 20 hours/year in the 

continuous case. If PHEVs were unable to charge during these times, their annual electric 

miles would be reduced by less than 1%. 

3.4 Emissions 

We examined major sources of emissions of nitrogen oxides (NOX), sulfur dioxide (SO2), 

and carbon dioxide (CO2). These sources include vehicles, electric generation, and 

refinery operations; but do not include all life-cycle factors, such as fuel extraction and 

transport, vehicle manufacturing, etc. 

NOX emission results from high-temperature combustion processes and is produced by 

both coal and gas-fired plants. SO2 is emitted as a result of the oxidization of sulfur 

contained in coal and petroleum, with about 67% of SO2 emissions originating in the 

electric sector.37 CO2 is emitted as the result of the oxidization of carbon in all fossil 

fuels. 

Figure 16 illustrates the electricity-related emissions rates for the various PHEV 

charging scenarios. 

 

36 We did not examine any potential “feedback” effects on the cost of electricity due to the increased use of 

natural gas for PHEV charging. 

37 U.S. EPA. “SO2: What is it? Where does it come from?” 

http://www.epa.gov/air/urbanair/so2/what1.html 

 19
0.00

0.20

0.40

0.60

0.80

1.00

1.20

Uncontrolled Delayed Off-Peak Continuous

Emission Rate (lbs/MWh)

SO2

NOX

CO2 (000s)

Figure 16: Emission Rates of SO2, NOX, and CO2 Associated with PHEV Charging 

The SO2 emission rate associated with PHEV charging is strongly correlated with the 

amount of coal generation, because natural gas combustion produces very little SO2

emissions. As a result, the off-peak charging case produces the highest SO2 emission rate. 

The NOX emission rate also correlates strongly with the amount of coal generation, 

although significant NOX emissions may be produced by natural gas units. The increased 

use of coal in the off-peak case is balanced by the increased use of more efficient 

combined-cycle units, resulting in approximately equal CO2 emissions rates in all four 

charging scenarios. In all cases, incremental generation for PHEV charging is much less 

dependent on coal than the system average, resulting in much lower emission rates. The 

Xcel Energy system average emission rates in 2004 were about 2.9 lbs/MWh for NOX, 

3.1 lbs/MWh for SO2, and 1,950 lbs/MWh for CO2.

38

Figure 17 illustrates the total net NOX emissions from several vehicle types including 

conventional vehicles and PHEVs under various charging scenarios. The net NOX

emissions include vehicle tailpipe emissions, power plant emissions, and refinery-related 

emissions.39 The composite per mile emissions can be estimated by dividing by the 

annual number of miles traveled – in this case, equal to 13,900. 

 

 

38 U.S. EPA eGRID2006 Version 2.0. http://www.epa.gov/cleanenergy/egrid/index.htm 39 Vehicle CO2 emissions from U.S. Environmental Protection Agency. Compilation of Air Pollutant 

Emission Factors, AP-42, 5th ed.; U.S. Environmental Protection Agency, U.S. Government Printing 

Agency: Washington, D.C., 1996; Volume I: Stationary Point and Area Sources. AP-42. Vehicle NOx from 

tier 1 and tier 2 stds, equal to 0.3 gms/mile and 0.7 gms/mile. From: Transportation Energy Data Book: 

Edition 25, (2006). Stacy C. Davis, Susan W. Diegel, Oak Ridge National Laboratory, ORNL-6974. 

Refinery emissions from GREET at http://www.transportation.anl.gov/software/GREET/ 

 20
0

2

4

6

8

10

12

14

Current CV

Future CV

HEV

Uncontrolled

Delayed

Off-Peak

Continuous

Annual NOX Emission Rate (lbs per vehicle)

Upstream - Refinery

Upstream - Utility

Vehicle

Figure 17: Net Vehicle NOX Emissions Rates 

Among the more important aspects of this chart is the dramatic reduction in new vehicle 

NOX emissions mandated by current regulations. Currently, about 55% of all NOX

emissions nationwide are from motor vehicles, with only about 22% emitted from electric 

utilities.40 As a result of reduced future vehicle emissions, net emissions from PHEVs 

could be somewhat higher than from conventional vehicles or HEVs, especially if more 

coal generation was available for charging. This also means NOX emissions from refinery 

operations will become a greater fraction of vehicle-related emissions, although relatively 

small on an absolute basis. The refinery emissions are based on current national average, 

and rates are expected to decrease under existing and pending EPA regulations. There are 

also regulations that will substantially reduce NOX emissions from the electric sector.41

Ultimately, a meaningful net comparison of NOX emissions is difficult, given the issues 

associated with emissions transport and air quality modeling. Major air quality issues and 

health concerns related to NOX are from emissions in populated areas. Many of the 

upstream NOX emissions do not occur in populated areas, reducing their impact. Also, 

“blended mode” PHEV NOX emissions are less likely to occur in populated areas, and 

PHEVs are far more likely to be operated almost exclusively in zero-emissions EV-only 

mode in urban centers. In addition, because many of the marginal generators used for 

PHEV charging do not currently have post-combustion controls, there are significant 

opportunities to reduce generation-related NOX emissions. 

Because there is so little sulfur in motor gasoline, gasoline vehicle SO2 emissions are 

very small, and net vehicle related emissions are largely from the upstream processes, 

 

40 U.S. EPA “NOx: What is it? Where does it come from?” Via 

http://www.epa.gov/air/urbanair/nox/what.html 41 U.S. Environmental Protection Agency. Clean Air Interstate Rule. 

Available at http://www.epa.gov/cair 

 21
either from the refinery or the power plant. This is illustrated in Figure 18, which shows 

the net SO2 emission rates for various vehicle types and charging scenarios. 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Current CV

Future CV

HEV

Uncontrolled

Delayed

Off-Peak

Continuous

Annual SO2 Emission Rate (lbs per vehicle)

Vehicle Upstream - Utility Upstream - Refinery

Figure 18: Net Vehicle SO2 Emissions Rates 

Depending on the amount of coal in the marginal generation mix, net SO2 emissions from 

a PHEV may be greater than a conventional vehicle or HEV. This comparison is clearly 

very sensitive to both assumed refinery emissions rate and the use of coal for PHEV 

charging. However, any SO2 comparison must be placed in context of the national cap on 

SO2 emissions, which does not allow a net increase in SO2. As a result, any increase in 

SO2 emissions resulting from additional load created by PHEV charging must be offset 

by a decrease in emissions elsewhere – so while PHEVs will not increase the amount of 

SO2 emissions, they could slightly increase the cost of coal-generated electricity. 

Figure 19 illustrates the net CO2 emissions on a per-vehicle basis. In all cases, there are 

significant reductions in net CO2 emissions from PHEVs. 

 22
0

1

2

3

4

5

6

7

Current CV

Future CV

HEV

Uncontrolled

Delayed

Off-Peak

Continuous

Annual CO2 Emission Rate (tons per vehicle)

Upstream - Refinery

Upstream - Utility

Vehicle

Figure 19: Net Vehicle CO2 Emissions Rates 

4. Conclusions 

• The actual electricity demands associated with PHEV charging are quite modest 

compared to normal electricity demands. Replacing 30% of the vehicles currently 

in the Xcel Energy service territory with PHEV-20s deriving 39% of their miles 

from electricity would increase total load by less than 3%. 

• A very large penetration of PHEVs would place increased pressure on peaking 

units if charging is completely uncontrolled. There is a large natural coincidence 

between the normal system peaks and when significant charging would occur 

during both the summer and winter seasons. 

• No additional capacity would be required for even a massive penetration of PHEV 

if even modest attempts were made to optimize system charging. Simple time-ofday charging could easily place all end-of-day charging requirements into offpeak periods. Utility-controlled charging would create additional net benefits in 

terms of utilization of existing plants. 

• In the near term, the Xcel Energy system uses gas for marginal generation most of 

the time. Coal is used for less than 20% of all PHEV charging, even in scenarios 

that use exclusively “off-peak” electricity. 

• Because most near-term PHEV charging will likely be derived from gas units in 

the evaluated scenarios, the cost of natural gas drives the cost of PHEV charging. 

 23
• The incremental cost of charging a PHEV fleet in the overnight charging cases 

ranges from $90 to $140 per vehicle per year. This translates to an equivalent 

production cost of gasoline of about 60 cents to 90 cents per gallon. 

• Total NOX emissions from PHEVs in the evaluated scenarios are equal or slightly 

less than from non-plug-in HEVs. Although total NOX reductions may be 

relatively small, tailpipe NOX is significantly reduced as more miles are 

electrically driven. Without the use of an air quality model, it is difficult to 

quantify the net benefit of reducing tailpipe NOX while increasing generator NOX

emissions. In addition, there are significant opportunities for further NOX

reductions in the electricity sector as many units are not fitted with the latest 

emission control technology. 

• Because gasoline contains little sulfur (having been taken out at the refinery), the 

most important factors for net SO2 emissions are emissions from refinery 

operations and from marginal coal generation. For the evaluated daytime and 

delayed charging scenarios, total PHEV-related SO2 emissions are expected to be 

less than from conventional and hybrid vehicles. In the off-peak charging case, or 

any case where coal is at the margin a large fraction of the time, SO2 emissions 

are expected to be greater. Any emissions comparison must be placed in context 

of the national cap on SO2 emissions, which does not allow a net increase in SO2. 

As a result, any increase in SO2 emissions resulting from additional load created 

by PHEV charging must be offset by a decrease in emissions elsewhere. 

• In all cases, there are significant reductions in net CO2 emissions from PHEVs. 

• Further analysis is needed to design and analyze several potentially improved 

charging scenarios. A more optimal charging scenario would likely combine offpeak charging to minimize costs, while including some midday (continuous) 

charging to increase gasoline savings. This would potentially provide both Xcel 

Energy and its customers with the greatest overall mix of PHEV benefits. 

 24
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2. REPORT TYPE

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3. DATES COVERED (From - To)

 

5a. CONTRACT NUMBER

DE-AC36-99-GO10337 

5b. GRANT NUMBER

4. TITLE AND SUBTITLE

Costs and Emissions Associated with Plug-In Hybrid Electric Vehicle 

Charging in the Xcel Energy Colorado Service Territory 

5c. PROGRAM ELEMENT NUMBER

5d. PROJECT NUMBER

NREL/TP-640-41410 

5e. TASK NUMBER

WR61.2001 

6. AUTHOR(S)

K. Parks, P. Denholm, and T. Markel 

5f. WORK UNIT NUMBER

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National Renewable Energy Laboratory 

1617 Cole Blvd. 

Golden, CO 80401-3393 

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REPORT NUMBER

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14. ABSTRACT (Maximum 200 Words)

The combination of high oil costs, concerns about oil security and availability, and air quality issues related to vehicle 

emissions are driving interest in “plug-in” hybrid electric vehicles (PHEVs). PHEVs are similar to conventional hybrid 

electric vehicles, but feature a larger battery and plug-in charger that allows electricity from the grid to replace a 

portion of the petroleum-fueled drive energy. PHEVs may derive a substantial fraction of their miles from grid-derived 

electricity, but without the range restrictions of pure battery electric vehicles. As of early 2007, production of PHEVs is 

essentially limited to demonstration vehicles and prototypes. However, the technology has received considerable 

attention from the media, national security interests, environmental organizations, and the electric power industry. 

The use of PHEVs would represent a significant potential shift in the use of electricity and the operation of electric 

power systems. Electrification of the transportation sector could increase generation capacity and transmission and 

distribution (T&D) requirements, especially if vehicles are charged during periods of high demand. This study is 

designed to evaluate several of these PHEV-charging impacts on utility system operations within the Xcel Energy 

Colorado service territory. 

15. SUBJECT TERMS

NREL; plug-in hybrid electric vehicles; PHEVs; vehicle technologies; Xcel Energy Colorado; electric charging; 

transmission and distribution; T&D; transportation; vehicle emissions; utility system; electric generation; Paul 

Denholm; Keith Parks; Tony Markel 

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