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 

An Evaluation of Utility System 

Impacts and Benefits of 

Optimally Dispatched Plug-In 

Hybrid Electric Vehicles 

P. Denholm and W. Short 

Technical Report 

NREL/TP-620-40293 

Revised October 2006 

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Technical Report 

NREL/TP-620-40293 

Published July 2006 

Revised August 2006 

Revised October 2006 

An Evaluation of Utility System 

Impacts and Benefits of 

Optimally Dispatched Plug-In 

Hybrid Electric Vehicles 

P. Denholm and W. Short 

Prepared under Task No. FC03.0120 
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ERRATA SHEET 

NREL REPORT/PROJECT NUMBER: NREL/TP-620-40293 

DOE NUMBER: None 

TITLE: An Evaluation of Utility System Impacts and Benefits of Optimally Dispatched 

Plug-In Hybrid Electric Vehicles 

AUTHOR(S): P Denholm and W. Short 

ORIGINAL PUBLICATION DATE: July 2006; Revised August 2006 

DATE OF CORRECTIONS: October 2006 

The following corrections were made to this report/document: 

Page 1 (Abstract, line 15): 

Based on existing electricity demand and driving patterns, a 50% penetration of PHEVs 

would increase the per capita electricity demand by around 5-10%, depending on the 

region evaluated. 

Page 13: 

New Figure 5: Relationship Between PHEV Penetration and Per Capita Electricity 

Demand Related to PHEV Charging 

Page 16: 

New Figure 9: Increase in Total Electric Demand as a Function of PHEV Penetration 

Page 17: 

New Figure 10: Utility Load Factors with PHEV Charging 

Page 17: 

New Figure 11: Regional Increase in Utility System Annual Minimum Load with PHEV 

Charging 

Page 18: 

New Figure 12: Regional Decrease in Relative System Cycling with PHEV Charging 
Table of Contents 

Abstract............................................................................................................................... 1 

1) Introduction .................................................................................................................... 2 

2) Possible Impacts of PHEVs on the Existing Electric Power System ............................. 3 

3) Analysis Methods Using the PHEV-load Tool............................................................... 6 

3.1 Evaluated Regions .................................................................................................... 6 

3.2 Vehicle Assumptions................................................................................................ 7 

3.3 Vehicle Charging ...................................................................................................... 9 

3.4 Vehicle Discharge Capacity.................................................................................... 10 

4) Results .......................................................................................................................... 12 

4.1 Impacts of PHEV Charging. ................................................................................... 13 

4.2 Potential PHEV Peaking Capacity.......................................................................... 19 

5) Conclusions and Discussion ......................................................................................... 21 

6) Future Work.................................................................................................................. 22 

Appendix: Vehicle Capacity Credit Using IC Engine Run .............................................. 23 

 iii
Abstract 

Hybrid electric vehicles with the capability of being recharged from the grid may provide 

a significant decrease in oil consumption. These “plug-in” hybrids (PHEVs) will affect 

utility operations, adding additional electricity demand. Because many individual 

vehicles may be charged in the extended overnight period, and because the cost of 

wireless communication has decreased, there is a unique opportunity for utilities to 

directly control the charging of these vehicles at the precise times when normal electricity 

demand is at a minimum. We evaluated the effects of optimal PHEV charging, under the 

assumption that utilities will indirectly or directly control when charging takes place, 

providing consumers with the absolute lowest cost of driving energy. By using low-cost 

off-peak electricity, PHEVs owners could purchase the drive energy equivalent to a 

gallon of gasoline for under 75 cents, assuming current national average residential 

electricity prices. We evaluated six geographic regions in the United States and found 

that under cases where PHEVs derive 40% of their miles from electricity, penetrations up 

to 50% of the vehicle fleet require no new electric generation capacity under optimal 

dispatch rules. Based on existing electricity demand and driving patterns, a 50% 

penetration of PHEVs would increase the per capita electricity demand by around 5-10%, 

depending on the region evaluated. While increasing total electrical energy consumption 

(but without requiring additional generation capacity), the optimal dispatch of the 

additional PHEV demand would increase loading of baseload power plants built to meet 

the normal demand. This also would substantially decrease the daily “cycling” of power 

plants, both of which would translate into lower operational costs. 

We also considered the ability of PHEVs to discharge into the grid to replace 

conventional capacity that provides peaking and peak reserve capacity. While the ability 

of PHEVs to provide short-term ancillary services has been previously analyzed, their 

ability to provide “long-term” energy and capacity services on a regional basis is not as 

well understood. If utilities use conservative estimates for the availability of PHEVs, and 

require vehicles to provide continuous discharge for extended periods, then the effective 

planning capacity of an individual PHEV could be quite small (well under 1 kW). While 

it appears that PHEVs are much better suited for short-term ancillary services such as 

regulation and spinning reserve, a large fleet of PHEVs could possibly replace a moderate 

fraction (perhaps up to 25%) of conventional low-capacity factor (rarely used) generation 

used for periods of extreme demand or system emergencies. Overall, the ability to 

schedule both charging and very limited discharging of PHEVs could significantly 

increase power system utilization. 

 1
1) Introduction 

The “plug-in” hybrid electric vehicle is a potentially significant technology for reducing 

vehicle emissions and reliance on petroleum for transportation. As currently offered by 

several major auto manufacturers, conventional hybrid electric vehicles (HEVs) add a 

battery and electric motor to an internal combustion (IC) engine. This combination 

increases fuel economy by allowing the IC engine to operate more efficiently, shutting 

off the engine during stops, and recapturing otherwise discarded kinetic energy through 

regenerative braking. Though the overall vehicle efficiency is increased, all of the energy 

that HEVs use is still derived from petroleum. A “plug-in” or “pluggable” HEV (PHEV) 

uses the same technology, but it also features a larger battery and plug-in charger that 

allows electricity from the grid to replace a portion of the petroleum-fueled drive energy. 

PHEVs combine the benefits of HEVs and pure electric vehicles (EVs): They are less 

reliant on petroleum than conventional HEVs, and they are a more practical alternative to 

pure electric vehicles because they avoid the challenges presented by EVs’ battery-only 

operation (prohibitive cost, long charge times, and limited range.) 

A PHEV may also be designated by its effective “all-electric” range, such as PHEV-20, 

referring to a vehicle that may be driven 20 miles from its batteries. Beyond this range, 

the vehicle operates as a conventional “charge-sustaining” HEV. It should be noted that 

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 unlikely. More likely is “blended” operation where the electric motor supplies 

low-speed operation, supplemented by the IC engine at high speed. With this mode of 

operation, the maximum power draw on the batteries and electric drivetrain is reduced, 

and the size distribution between electric and IC power plants is more optimized. The use 

of plug-in hybrid technology results in substantial reduction in gasoline use. For many 

U.S. drivers, a PHEV-40 could reduce average gasoline consumption by 50% or more.1

 

As of 2006, relatively few PHEVs have been built, essentially as demonstration vehicles 

and prototypes. While no major manufacturer has yet produced PHEVs, 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.2

 The economic incentive for 

drivers to use electricity as fuel is the comparatively low cost. 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.3 The cost of this 

electricity using the U.S. average residential rate for 2003 (7.6 cents/kWh)4 is less than 

$1, and could be less than 50 cents when using off-peak power at preferential rates. 

 

1

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

Options,” EPRI, Palo Alto CA, 10003496892. 

2

 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 3

 Electric Power Research Institute (2001). 

4

 U.S. Department of Energy (2005). Electric Power Annual 2004, DOE/EIA-0348(2003), Energy 

Information Administration, Washington, D.C. 

 2
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 providing high-value electric system services such as 

regulation, spinning reserve, and peaking capacity.5,6

The use of PHEVs represents a significant potential shift in the use of electricity and the 

operation of electric power systems. Electrification of the transportation sector will create 

additional loads on generators and transmission and distribution (T&D) systems. Wellpublicized failures of the electric grid have increased concerns regarding grid reliability 

and the need for additional transmission and generation capacity. Widespread acceptance 

of PHEVs may require assurance that this technology will neither result in decreased 

electric system reliability nor require massive new unsightly and unpopular 

infrastructure. Previous studies of pure electric vehicles (EVs) have demonstrated that 

existing capacity can meet the overnight charging loads of a modest penetration (up to 

20%) of these vehicles.7 The emergence of commercially viable HEVs, and the reemergence of realistic electric vehicles via PHEVs, warrants a new look at vehicle 

impacts on utility loads. The “new” capabilities of a modern PHEV fleet include almost 

ideal charging dispatch made possible by wireless communications and improvements in 

power electronics, and the possibility of V2G for peaking and reserve capacity. 

We present the results of a study where the electricity demand of a hypothetical fleet of 

PHEVs was added to actual recorded utility loads under an optimal charging strategy. 

The impact of the use of PHEVs for peaking generation and reserve capacity was also 

considered. The resulting daily and yearly generation and demand profiles were then 

examined to provide some basic insight into the potential grid impacts of PHEVs. 

2) Possible Impacts of PHEVs on the Existing Electric Power System 

Electric power systems are designed to respond to instantaneous consumer demand, 

which constantly varies as a function of time of day and season, depending on the 

requirements for heat, light, and other services provided by electricity. Figure 1 shows 

three hourly demand curves from one Midwestern U.S. utility. Each curve illustrates 

seven days’ worth of data, from three different seasons in 2002.8

 These curves illustrate 

the significant variation in electric demand, with the annual peak demand driven by airconditioning requirements in late afternoons on hot summer days. On a daily basis, 

minimum demand occurs in the early morning, with the annual minimum generally 

occurring in the spring. 

 

5

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

Transportation Research D 3: 157-175. 6

 Kempton, W. and J. Tomic (2005). “Vehicle-to-grid power fundamentals: Calculating capacity and net 

revenue.” Journal of Power Sources 144(1): 268-279. 7

 Ford, A. (1995). “The Impacts of Large-Scale Use of Electric Vehicles in Southern California.” Energy 

and Buildings, 22(3): 207-218. 8

 Federal Energy Regulatory Commission. “Northern States Power Form 714 - Annual Electric Control and 

Planning Area Report,” http://www.ferc.gov/docs-filing/eforms/form-714/data.asp 

 3
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 24 48 72 96 120 144 168

Hour

Load (% of Annual Peak Load)

Summer Maximum

Winter

Spring Minimum

Figure 1: Typical Hourly Electric Demand Patterns 

The significant variation in daily and seasonal demand illustrated in Figure 1 creates 

significant burdens on the generating utility and also costs, which are ultimately passed 

on to consumers. These costs result from underutilized baseload power plants, large 

capacity requirements for peak demand, and demands of power plant cycling. 

The effective utilization of a utility’s power plant fleet can be illustrated in a load 

duration curve (LDC), created by reordering the hourly demand data from greatest to 

least demand for all 8760 hours in a year and illustrated in Figure 2. The load at any point 

may be expressed as a fraction of annual peak load, and any load above minimum 

represents power plants that are not fully utilized. The low-demand hours on the right 

side of the LDC generally occur during overnight hours and result in underutilized 

baseload plants. (Any decrease in a plant’s capacity factor results in an increase in the 

average price of electricity in order to recover the plant’s fixed costs.) The average 

capacity factor for U.S. power plants is about 60%, while well-run power plants can 

achieve capacity factors well above 90%.9

 

9

 U.S. Department of Energy (2005). 

 4
0.0

0.2

0.4

0.6

0.8

1.0

1.2

0.000 0. 000. 00. 0.

Hours at Load

Load (% of Peak)

200 4 60 800

Underutilized 

baseload capacity

Rarely used peaking 

capacity (20% of capacity 

meets 1% of load) 

Reserve capacity

 0 2000 4000 6000 8000 

Figure 2: Utility Load Duration Curve 

The capacity requirements for peak load also add substantial costs to the electric power 

system. The far left side of the LDC illustrates the peak demand that occurs during a 

small number of hours of the year. This peak demand, generally associated with airconditioning loads on hot days requires utilities to install large amounts of generation that 

is seldom used. Figure 2 illustrates this scenario: The top 20% of load-serving capacity 

effectively runs less than 5% of the time and provides less than 1% of the system’s 

electricity demand. The sharp “super peak” of the top 2% of demand hours requires the 

bulk of this peaking capacity – in this year about 13% of the capacity is used to meet load 

for less than 200 hours. In addition, utilities employ an additional peak reserve margin, 

which is typically an extra 10-20% of capacity over projected peak demand. This 

required reserve capacity ensures system reliability by serving as a contingency against 

system failures and any unexpected increase in peak demand. 

In addition to the fixed costs associated with underutilized capacity, the significant 

cycling that occurs on a daily basis creates additional costs for plants that actually do run. 

The large swings in daily demand requires utilities to start up and shut down plants at 

considerable cost, and the constantly varying loads often require generators to operate 

well below the “design point” of optimum efficiency.10 Power plant cycling also 

increases operation and maintenance requirements. 

We examined two general impacts that PHEVs had on the performance of electric power 

systems: increased demand from PHEV charging, and PHEV discharging for peaking 

capacity. PHEVs may function as a source of dispatchable demand that utilities can use 

to increase plant loading during low-demand periods, given that PHEV owners will 

 

10 Lefton, S., Grimsrud, P., and P. Besuner (1997). “Cycling Fossil-Fired Units Proves Costly Business.” 

Electric Light & Power, 75(7): 19-20. 

 5
probably not care when their vehicles actually charge during an overnight period, as long 

as the vehicle is charged when needed in the morning. Utilities could “ramp up” vehicle 

charging in the late evening, with maximum charging occurring at normal system 

minimum. In this manner, utilities increase minimum load while substantially reducing 

power plant cycling during the charge period. In addition, PHEVs may provide a resource 

for meeting peak capacity requirements by discharging stored energy. While PHEVs will 

not themselves reduce midday loads, they could potentially be an economic alternative to 

conventional generators. PHEVs would have the advantage of being distributed around 

load centers, reducing burdens on T&D systems, making them a possible substitute for 

centralized peaking plants. Overall, optimally dispatched PHEVs could flatten electricity 

demand patterns, increase power plant utilization, and reduce overall system costs. 

In addition to the energy demands illustrated in Figures 1 and 2, utility systems also 

require short-term ancillary services such as frequency regulation and spinning reserves. 

These high-value services are an almost ideal application of PHEVs and may be an 

important source of value for PHEV owners. This application has been previously 

evaluated,11 and because the focus of this analysis is on bulk generation and capacity 

impacts, the use of PHEVs for ancillary services was not analyzed in this work. 

 

3) Analysis Methods Using the PHEV-load Tool 

A “PHEV-load” tool was developed to examine the potential impacts of large-scale 

deployment of PHEVs on a given electric power system. The PHEV-load tool consists of 

several components: an hourly demand database to which PHEV loads are added, a set of 

vehicle parameters which establishes the performance of the PHEV fleet, and a demand 

dispatch algorithm which attempts to optimally charge and discharge the PHEV fleet. 

To maximize the usefulness of this study, we used data from several geographical 

regions, and evaluated a range of possible PHEV scenarios to enable sensitivity analysis 

to electricity load variation and market penetration. Each of the PHEV-load tool 

components and study assumptions are described in further detail in the following 

sections. 

3.1 Evaluated Regions 

To account for differences in electricity use and driving patterns, we evaluated six 

different geographical regions in the United States. Because the primary goal of the study 

was to evaluate impacts on electric power systems, each geographical region evaluated 

was a utility power control area or other region for which hourly electric load data is 

available. 

Table 1 lists the regions and corresponding utility control area. The average per capita 

electricity use for each region is assumed to be equivalent to the state average (total state 

 

11 Kempton, W. and J. Tomic (2005). 

 6
electricity use12 divided by state population13). This assumption should be reasonably 

accurate because the chosen service territories are a large fraction of the entire state. The 

population served in the utility control area was estimated by dividing the annual 

electricity consumption in the region by the state average consumption. 

Table 1: List of Regions Used for PHEV Analysis (year 2003 data) 

Region 

(State) 

Utility Control 

Area 

Utility Share 

of State 

Demand 

Per Capita 

Electricity Use 

(MWh/person/yr) 

Estimated 

Population 

(million) 

Northwest 

(Oregon) 

Portland Gas & 

Electric 

44 12.68 1.56 

Southwest 

(California) 

Southern Cal. 

Edison 

41 6.73 14.45 

Central 

(Missouri) 

Union Electric/ 

AMEREN 

74 12.98 4.23 

Southeast 

(Florida) 

Florida Power & 

Light 

50 12.79 8.47 

North East 

(New York) 

Consolidated 

Edison 

40 7.5 7.7 

Midwest 

(Minnesota) 

Northern States 

Power/Xcel 

69 12.46 3.47 

3.2 Vehicle Assumptions 

There is considerable uncertainty in the most economical size and configuration of 

marketable PHEVs.14 A PHEV represents a tradeoff between various components 

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

size. The vehicle’s electric range is variable (PHEV-20, PHEV-40, etc.) and so is the 

fraction of drive energy derived from the battery while operating in blended mode at 

higher speeds. One previous study evaluated PHEVs with ranges from 20 to 60 miles,15

while the current goal of the Advanced Energy Initiative is a PHEV-40.16 At high 

penetration, it is likely that a variety of PHEV ranges will become available. 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 3 provides 

two estimates of the potential miles displaced by electricity for a variety of PHEV 

ranges.17 We chose a base case where the overall PHEV fleet derives 40% of its miles 

 

12 U.S. Department of Energy (2004). Electric Power Annual 2003, DOE/EIA-0348(2003), Energy 

Information Administration, Washington, D.C. 

13 U.S. Census Bureau (2005). Annual Estimates of the Population for the United States and States, and for 

Puerto Rico: April 1, 2000 to July 1, 2005 (NST-EST2005-01) http://www.census.gov/popest/states/NSTann-est.html 

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

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

Laboratory, Golden, Colorado August, 2005 

15 Electric Power Research Institute (2001). 

16 National Economic Council (2006) “Advanced Energy Initiative,” via 

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

17 Electric Power Research Institute (2001). 

 7
from electricity. Based on the values in Figure 3, this electric fraction represents a vehicle 

sized between a PHEV-20 and a PHEV-40. 

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

Method 1 (Mileage

Weighted Probability)

Method 2 (Utility Factor)

Figure 3: Fraction of PHEV Miles Derived from Electricity 

To calculate the impacts on utility loads, the PHEV characteristics and regional VMT 

assumptions were combined to derive a per capita electricity demand associated with 

PHEV charging. 

Table 2 provides our assumptions for the regional vehicle and PHEV charging 

characteristics. The regional VMTs and vehicle ownership data is derived from statelevel transportation statistics.18,19 As stated previously, we assumed that 40% of all 

PHEV VMTs are derived from electricity. This value was multiplied by the average daily 

per- vehicle miles traveled in each of the six regions to derive a value for the average per 

PHEV daily “electric transportation” demand (miles driven electrically per day for the 

average PHEV). Finally, the average daily miles driven electrically is converted to PHEV 

electricity demand, using the assumed average vehicle efficiency of 0.34 kWh/mile (2.9 

miles/kWh).

20

 

18 U.S. Department of Transportation (2004), Federal Highway Administration, Highway Statistics 2003 , 

Washington, D.C.: http://www.fhwa.dot.gov/policy/ohpi/hss/index.htm 

19 U.S. Department of Transportation (2004), State Transportation Statistics 2004. 

http://www.bts.gov/publications/state_transportation_profiles/state_transportation_statistics_2004/ 

20 Electric Power Research Institute (2001). 

 8
Table 2: Regional Vehicle Characteristics and PHEV Electricity Demand for a PHEV with 

40% Electric VMTs 

Region Avg daily per 

vehicle VMT 

(miles) 

Vehicles 

per 

capita 

Avg per 

capita VMT 

(miles) 

Avg. daily 

PHEV 

electric miles 

Avg. PHEV daily 

electricity 

demand (kWh) 

Northwest 32.2 0.84 27.0 12.9 4.4 

Southwest 29.8 0.84 25.0 11.9 4.1 

Central 42.2 0.77 32.7 16.9 5.8 

Southeast 35.7 0.84 29.9 14.3 4.9 

Northeast 35.0 0.55 19.3 14.0 4.8 

Midwest 33.9 0.88 29.9 13.6 4.6 

3.3 Vehicle Charging 

The PHEV-load tool “dispatches” the charging and discharging of a fleet of PHEVs on an 

optimized 24-hour cycle. To maximize the economic value of the PHEV to the consumer, 

we assume that vehicle charging and discharging will be controlled directly or indirectly 

by the utility system, allowing the use of lowest-cost electricity. With direct control, the 

utility would send a signal to an individual vehicle or a group of vehicles. 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 or sell 

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

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

The base-case assumption for the PHEV-load tool is overnight charging during the 

periods of least-cost electricity. Determining the precise period of lowest-cost electricity 

would require knowledge of the mix of power plants and fuel prices in each territory. 

However, because power plants are generally dispatched in a merit order reflecting 

increasing variable costs, there is a strong correlation between load and electricity prices. 

Therefore, vehicle charging can be assumed to be most economical during periods of 

minimum demand. The PHEV-load tool uses a valley-fill algorithm that identifies the 

hour of minimum overnight demand and adds a small amount of additional load to this 

hour. The tool then repeats this process, finding the minimum demand hour, and adds 

additional load, until the total additional electric demand is met. 

There is an important caveat related to this method of dispatch. Because the PHEV load 

tool uses historical load data,21 it has prior knowledge of both the total system load 

during each hour of the year and the total additional energy demand of the PHEV fleet. 

This prior knowledge allows it to perfectly forecast system demand and to optimally 

 

21 Federal Energy Regulatory Commission. “Form 714 - Annual Electric Control and Planning Area 

Report,” http://www.ferc.gov/docs-filing/eforms/form-714/data.asp 

 9
dispatch generators without error. Because utilities can generally predict short-term loads 

(less than 24 hours in advance) with a high degree of accuracy (often less than 5% 

error),22 we assume that this perfect forecasting assumption will not significantly impact 

our results. 

3.4 Vehicle Discharge Capacity 

For utilities to realize the potential benefits of PHEVs, it is important to establish the 

“dependable” capacity an aggregated number of vehicles could provide for peaking 

generation or reserves. Estimating the potential peaking capacity provided by PHEVs is 

somewhat challenging, given the important time-sensitive (how many cars are plugged in 

and when) nature of PHEV capacity. The power capacity of an individual PHEV is a 

function of many factors: the energy capacity of the battery, whether or not it is plugged 

in, the capacity of the plug circuit, the state of charge of the battery at the initiation of 

discharge, and the amount of time that vehicle discharge is required. For a reasonable 

number of vehicles deployed, each of these factors can be expressed as a distribution, or 

average, which may or may not vary over time. In our base-case analysis, we assume that 

the IC engine may not be turned on to provide electricity; however, this possibility is 

discussed in the Appendix. 

Battery Capacity: The size of the vehicle’s usable battery capacity depends on the 

electric range and the vehicle electric drive efficiency. Estimates of efficiencies for 

simulated vehicles range from 0.25 kWh/mile for compact vehicles to 0.42 kWh/mile for 

large SUVs (this assessment uses a fleet average of 0.34 miles/kWh or 2.9 miles/kWh). 

As a result, the usable battery capacity over this range of vehicles would be 5.0 kWh for a 

compact PHEV-20 to 14.4 kWh for a large SUV PHEV-40. We assumed a fleet average 

usable battery capacity of 10.2 kWh. 

PHEV plug-in factor: Data from the U.S. Department of Transportation23 indicates that 

only a small fraction of vehicles (fewer than 20%) are on the road at any one time. 

However, it is less clear what fraction of stationary vehicles are in places likely to be 

plugged in, including home, work, and other locations during times that a utility will 

require capacity “services” from PHEVs. The “capacity credit” (the amount of reliable 

electricity generation capacity available from a PHEV fleet) would likely be based 

largely on vehicle availability during peak periods.24 In most of the United States, peak 

demand occurs in late afternoons during summer weekdays. One previous PHEV 

assessment assumed very high plug-in factors (75%) resulting in part from financial 

incentives to individual PHEV owners.25 This would also likely require development of 

charging infrastructure at many places of work, or public parking facilities. 

 

22 PJM (2006). “PJM System Operator Seminar Spring – 2005” 

http://www.pjm.com/services/training/downloads/20050607-seminar-state-pjm-system.pdf 

23 U.S. Department of Transportation (2004), 2001 National Household Travel Survey at 

http://nhts.ornl.gov/2001/index.shtml 

24 Milligan, M. (2002).”Modeling Utility_Scale Wind Power Plants, Part 2: Capacity Credit” NREL, TP500-29701. 

25 Kempton, W. and J. Tomic (2005). 

 10
Maximum circuit capacity: A PHEV could have an internal electric capacity that 

exceeds 100 kW.26 However, the capacity actually accessible to the grid for planning 

reserves will be limited by the grid connection. We assume that most PHEVs will be 

plugged into conventional residential and commercial electric circuits at 120V or 240V. 

At these voltages, the line capacity is the bottleneck on power flow to and from the grid. 

However, many customers (such as fleet owners) may choose to utilize much highercapacity circuits for maximum economic benefits. The overall range of likely circuits is 

about 2 kW (120V @ 20A) to perhaps 20 kW (240V @ 100A).27,28 

Discharge Time and Battery Capacity: To assign a usable capacity credit to a PHEV 

fleet (and have the PHEV fleet actually replace conventional peaking generation), the 

total discharge time requirements must be established. As indicated in Figure 1, typical 

afternoon peaks last 2-6 hours. However, peak reserve generators are also used to replace 

the output from failed generators or transmission lines. These contingencies can last 

considerably longer. We could find no clear guidelines on what a typical utility might 

expect in terms of continuous output needed for reliable planning capacity. However, 

PHEVs might be compared to other utility storage systems in terms of reliable 

capacity.29,30 If a vehicle cannot run the IC engine to provide electricity, a PHEV’s 

dependable capacity will be limited by battery capacity. 

The relationship between battery discharge time and reliable capacity for a plugged-in 

PHEV can be defined by 

Vehicle Capacity = The minimum of 

Line capacity 

OR 

Stored Battery energy / Discharge Time Required

 

Figure 4 provides an example of this relationship for three vehicles: a compact PHEV-20, 

a full-size PHEV-40 SUV, and our assumed fleet average. Each curve represents the 

discharge capacity of a vehicle with a fully charged battery, when connected to a 9.6 kW 

circuit. (In all cases in this document, battery capacity is considered useful capacity, 

meaning the battery can be cycled over its “usable” capacity affecting useful life.) For 

short-term events (30 minutes or less), the vehicle is limited by the plug circuit capacity, 

but still provides significant per-vehicle capacity for operating reserve and other ancillary 

services. At an aggregated level, the capacity credit of a fleet would be derived by 

multiplying the per-vehicle capacity credit by the number of vehicles plugged in at a 

given time. 

 

26 2006 Toyota Motor Sales, U.S.A., Inc. http://toyota.com/highlander/specs_hybrid.html 27 The continuous rating of a plug circuit is less than its peak capacity. 

28 National Electric Code (1999). Section 210-23(a). 

29 Utilities do provide capacity credit to pumped hydro storage systems (the only utility-scale energy 

storage system widely deployed), which typically have a full-rated discharge time of eight hours or more. 30 Denholm, Paul, and G.L. Kulcinski. (2004). ”Life-Cycle Energy Requirements and Greenhouse Gas 

Emissions from Large-Scale Energy Storage Systems,” Energy Conversion and Management. 45, 2153-

2172. 

 11
0

1

2

3

4

5

6

7

8

9

10

02468

Discharge Time Required (Hours)

PHEV Discharge Capacity Credit 

(kW)

Large PHEV-40

(14.4 kWh)

Assumed Fleet

Average (10.2 kWh)

Compact PHEV-20

(5.0 kWh)

Figure 4: Capacity of a Fully-Charged PHEV as a Function of Discharge Time Required 

4) Results 

The effects of PHEV charging and discharging were evaluated separately in each region, 

with a PHEV penetration of up to 50%. It will be some time before PHEVs penetrate the 

market. To avoid the need to pick a specific year to evaluate, and to maximize the 

usefulness of the study in considering sensitivities, a flexible PHEV penetration metric 

was developed. The penetration of PHEVs in this analysis is measured as a function of 

per capita electric transportation demand in each region. Also, electric power system 

impacts are measured in comparative terms, not as absolutes. This measurement system is 

described in more detail as follows. 

The impact of PHEVs can be measured by comparing the relative change in a utility 

system’s performance with and without PHEV loads. The actual PHEV load can be 

measured as a function of per capita electric transportation demand, based on the values 

in Table 2. This per capita electric transportation demand can then be added to the base 

per capita electricity demand, and the resulting impacts can be measured. 

The per capita PHEV electricity demand in this report is evaluated up to the point of a 

50% penetration (50% of all vehicles are PHEVs). Figure 5 establishes the relationship 

between per capita daily PHEV electricity demand and PHEV penetration for the six 

evaluated regions. 

 12
0%

10%

20%

30%

40%

50%

0.0 0.5 1.0 1.5 2.0 2.5

Per Capita PHEV Electricity Demand (kWh/person/day)

PHEV Penetration (%)

Northeast

Southwest

Northwest

Midwest

Southeast

Central

Figure 5: Relationship Between PHEV Penetration and Per Capita Electricity Demand 

Related to PHEV Charging 

When applied to future scenarios, the relationship shown in Figure 5 is independent of 

population growth, because it evaluates the system on a per capita basis. However, it does 

assume the per capita electricity use and per capita VMTs remain constant over time. 

However, the relationship in Figure 5 can be shifted to evaluate the impacts of different 

growth rates or PHEV performance. For example, if the fleet average efficiency of 

PHEVs is 20% less than the stated assumption, the per capita electricity demand would 

increase by 20%, holding all other variables constant. 

4.1 Impacts of PHEV Charging 

Figure 6 illustrates the daily load profiles from Figure 1 with the added PHEV loads. The 

added PHEV loads represent a 50% penetration of PHEVs. In this case, the added 

optimized charging has both increased the minimum overnight load, and flattened the 

load during this time period. Comparing the daily demand peak and daily demand 

minimum in Figure 1 and Figure 6 illustrates the substantial reduction in cycling of the 

generation fleet. 

 13
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 24 48 72 96 120 144 168

Hour

Load (% of Annual Peak Load)

Summer Maximum

Winter

Spring Minimum

Figure 6: Daily Demand with PHEVs at 50% Penetration (Midwestern Region) 

To achieve the nearly flat loads in the overnight hours, the overall charging rate must 

vary considerably. Figure 7 indicates the PHEV fleet charging requirements for the same 

case. 

0

0.05

0.1

0.15

0.2

0 24 48 72 96 120 144 168

Hour

Load (% of Annual Peak Load)

Summer Maximum Winter

Spring Minimum

Figure 7: PHEV System Load at 50% Penetration (Midwestern Region) 

The per-vehicle peak charging rate varies somewhat based on the optimal charging 

window, which is generally shorter in the summer and longer in the spring. The systemwide peak charging rate occurs at the daily system minimum, typically around 4 a.m., and 

 14
requires a total capacity equal to between 10% and 20% of the system peak capacity. 

Preliminary driving-pattern data obtained by NREL indicates that this optimal peak 

charging rate at around 4 a.m. coincides well with vehicle availability (4 a.m. appears to 

be the time when the maximum number of vehicles are parked at home).31 On a pervehicle basis, the peak charging rate in this scenario is well under 2 kW. As noted 

previously, the smallest common household circuit (120V, 20A) has a continuous rating 

of about 2 kW,32 which implies limited requirements for charging infrastructure. 

 

To achieve a flat overnight load and optimize overall charging at high PHEV penetration, 

we found some modification of our charging assumptions was necessary. During some 

days, low loads occur in the mid to late morning. If all vehicles must be fully charged by 

8 a.m., we observed a drop-off in load after the morning charge requirement was met, 

resulting in a less than optimal dispatch. To increase the optimization, we allowed up to 

20% of the total PHEV demand to be met by charging between 8 a.m. and 11 a.m. In 

practical terms, this would require some consumers to delay some charging until later in 

the morning. However, this also means that there is substantial opportunity for some 

early- to late-morning recharging for many commuters. Further analysis of consumer 

driving patterns may allow a more detailed analysis of potential benefits of midday 

charging. 

Figure 8 provides modified load duration curves for the Midwestern utility system with 

different levels of PHEV penetration. It is clear that the majority of PHEV charging 

energy is supplied by baseload units, and that there is a significant increase in the system 

minimum load. A very small amount of electricity is provided by intermediate load 

plants, mostly during summer nights when air-conditioning demand stays high until late 

in the evening as illustrated in Figure 1. However, in all systems even at 50% PHEV 

penetration, greater than 80% of the charging electricity is derived from units meeting the 

bottom two-thirds of the LDC. Perhaps even more important, there is no need for 

additional generation capacity, even at 50% PHEV penetration. 

 

31 Markel, T.; O’Keefe, M.; Simpson, A.; Gonder, J.;Brooker A. (2005) 

32 National Electric Code (1999). 

 15
0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 2000 4000 6000 8000

Hours at Load

Load (% of Peak)

50%

30%

10%

No PHEVs

Additional load on 

baseload units 

No additional load 

during peak demand 

periods

Figure 8: Load Duration Curves With PHEV Charging (Midwestern Region) 

The impacts on the electric power system can be quantified for each region. Figure 9 is 

the increase in total electricity demand as a function of PHEV penetration for each 

system. The difference in demand increase between systems is a function of base 

electricity demand and the per capital transportation demand. In systems with low per 

capita electricity use, such as California, adding PHEVs results in a proportionally larger 

increase in electricity demand. 

0%

3%

5%

8%

10%

0 10 20 30 40 5

Penetration of PHEVs (%)

Increase in Total Electricity Demand

0

Northeast

Southwest

Central

Southeast

Midwest

Northwest

Figure 9: Increase in Total Electric Demand as a Function of PHEV Penetration 

Because the additional PHEV load does not require an increase in generation capacity, 

PHEVs will increase the system’s load factor (defined as the average load divided by 

 16
peak load). The normal load factors for the six regions ranged from 54% to 67%. The 

fractional increase in load is also equal to the fractional increase in utility load factor, 

illustrated in Figure 10. 

50%

55%

60%

65%

70%

75%

0 10 20 30 40 50

Penetration of PHEVs (%)

Utility Load Factor (%)

Northwest

Southeast

Midwest

Northeast

Southwest

Central

Figure 10: Utility Load Factors with PHEV Charging 

Figure 11 illustrates the increase in minimum system load, which results from the 

increased overnight load demonstrated in Figure 6. 

0%

10%

20%

30%

40%

50%

0 10 20 30 40 5

Penetration of PHEVs (%)

Increase in Minimum Load (%)

0

Southeast

Northwest

Northeast

Southwest

Central

Midwest

Figure 11: Regional Increase in Utility System Annual Minimum Load with PHEV Charging 

The shape of the curves in Figure 11 results largely from daily and seasonal demand 

patterns. An examination of Figure 1 indicates that the “valley” of overnight load widens 

 17
as the minimum load increases. This fact produces the decreasing slope in all cases in 

Figure 11. Ultimately, the addition of overnight load does not increase the minimum load, 

because the overnight valley is completely filled in one or more days of the year. This 

results in a new annual minimum load, typically occurring on a spring day with normally 

low demand. This can be observed in Figure 6, where the new minimum load occurs in 

the afternoon. 

The shape of Figure 11 is driven largely by our assumption that vehicles must be charged 

mostly in the overnight hours, with no charging allowed during the afternoon. In reality, 

some low-cost charging opportunities will be available during the day in low-demand 

seasons. This probably means even greater electrification of the transportation system, 

because some drivers will be able to partially or fully recharge after the morning 

commute without negative impacts on the system as a whole. As noted previously, 

optimal charging of a PHEV fleet will require greater understanding of driving patterns 

and the marginal cost of electricity on an hourly basis. 

The increased overnight minimum load substantially decreases power plant cycling, 

illustrated in Figure 12. In this case, we measure system cycling as the average difference 

between daily peak and daily minimum demand, normalized by the annual peak demand. 

This reduction in cycling will translate into decreased power plant start-up and operations 

and maintenance (O&M) costs.33 

0%

5%

10%

15%

20%

25%

30%

35%

0 10 20 30 40 50

Penetration of PHEVs (%)

Average Daily Cycling

 (% of Peak Load)

Southeast

Northwest

Southwest

Midwest

Northeast

Central

Figure 12: Regional Decrease in Relative System Cycling with PHEV Charging 

 

33 Lefton, S., Grimsrud, P., and P. Besuner (1997). 

 18
4.2 Potential PHEV Peaking Capacity 

A number of previous studies have estimated the significant value of PHEVs in offering 

short-term ancillary services such as spinning and regulation reserve.34,35 By offering 

these services, PHEVs would free-up traditional capacity and improve system efficiency. 

These high-value services would probably be the “first” application of PHEV discharge 

capacity. Because previous studies have addressed in detail the significant value of 

PHEVs in providing regulation reserve, we only assess here their capacity to provide 

peaking power or peak reserve capacity. PHEVs would only replace traditional peaking 

capacity if the payment to the vehicle owner were less than what utilities would pay for a 

conventional generator (or if PHEVs offer other attributes superior to traditional 

capacity) and utilities could be assured of PHEV reliability and availability. 

Determining how much capacity PHEVs could economically replace would require 

knowledge of future electric power system costs. As an alternative to a cost-based 

analysis, we compared total PHEV capacity to the installed utility capacity with an 

effective capacity factor of 2%. This capacity roughly approximates the “super peak” 

capacity best suited for PHEVs, since it represents a significant fraction of installed 

utility capacity, but it is very rarely used.36 For the six cases evaluated, this represented 

from 10% to 16% of the effective load-serving capacity. An additional amount of 

capacity (equivalent to 10% or more of the load-serving capacity) represents the peak 

reserve capacity, which also could be replaced with PHEVs. As a result, we evaluated 

cases where the PHEV fleet potentially replaces up to about 25% of a utility system’s 

generation capacity. While representing a significant amount of generation capacity, 

these generators would be expected to run less that 200 hours per year, and provide well 

under 0.5% of the total energy demand. 

Figure 13 establishes a baseline comparison between the per-vehicle capacity 

requirements, PHEV penetration, and super-peak capacity replacement. This graph 

demonstrates the per-vehicle amount of capacity needed to replace 100% of the system’s 

combined super-peak capacity and peak reserve capacity as a function of PHEV 

penetration. (As mentioned previously, super-peak capacity is defined as capacity that 

effectively runs up to 2% of the time, with peak reserve capacity defined as equal to 10% 

of the capacity required at annual peak demand. This is equivalent to a peak reserve 

margin of 10%.) 

 

34 Kempton, W. and S. E. Letendre (1997). 

35 Kempton, W. and J. Tomic (2005). 

36 There appears to be no industry-wide standard for the amount of load in the “peak” or “super peak” 

demand regions. For this analysis, we define the “super peak” as demand that requires capacity, which 

effectively runs less than 2% of the time (175 hours per year). As noted in Figure 2, much of the peaking 

capacity in a utility system is used to meet the sharp “super peak” demand occurring less than 200 hours 

per year. 

 19
0

2

4

6

8

10

0% 10% 20% 30% 40% 50%

PHEV Penetration (%)

Per Vehicle Capacity Needed to 

Replace Super-Peak Capacity 

with PHEVs (kW/vehicle)

Central

Northeast

Midwest

Southeast

Northwest

Southwest

Figure 13: PHEV Capacity Needed to Replace All Super-Peak and Peak Reserve Capacity 

To provide an estimate of the range of individual PHEV capacity credits available to a 

PHEV, we established four cases, defined in Table 3. 

Table 3: Effective Capacity of a PHEV 

Vehicle Use Case 1 Case 2 Case 3 Case 4 

% Reliably Plugged in at 

Planning Peak 

40 40 50 60 

Average Battery SOC at 

Planning Peak 

40 40 50 50 

Discharge Time Required for 

“Dependable” Capacity (hours) 

8 6 6 4 

Base Dependable Capacity 

(kW per PHEV) 

0.20 0.27 0.43 0.77 

The assumptions used in Table 3 result in a relatively low per-vehicle capacity. These 

assumptions are fairly conservative, in an attempt to capture the uncertainty utilities may 

apply to generators they do not own. However, as PHEVs penetrate the market, utilities 

may become more comfortable with “relying” on PHEVs to provide firm capacity, and 

increase the per-vehicle capacity used for planning purposes. Of particular importance 

will be establishing reliability criteria for electric power systems that rely, in part, on 

energy storage systems with limited continuous discharge. 

To provide some estimate of the total peaking and peak reserve capacity offered by a 

PHEV fleet, we combined the capacity requirements in Figure 13 with a potentially 

conservative estimate of individual PHEV capacity at 0.25 kW, slightly lower than Case 

2 in Table 3. This estimate is provided in Figure 14, the fraction of this peaking capacity 

that PHEVs could serve as a function of PHEV penetration for each region. 

 20
0%

5%

10%

15%

20%

25%

30%

0% 10% 20% 30% 40% 50%

PHEV Penetration (%)

Fraction of Super-Peak Capacity 

Served by PHEVs (%)

Southwest

Northwest

Southeast

Midwest

Northeast

Central

Figure 14: Fraction of Super-Peak and Peak Reserve Capacity Replaced by a PHEV Fleet 

While Figure 14 provides an indication of the amount of capacity replaced by a fleet of 

PHEVs, further analysis will be required to determine the actual dispatch of the vehicles. 

5) Conclusions and Discussion 

Based on results from the PHEV-load tool, we conclude that large-scale deployment of 

PHEVs will have limited, if any, negative impacts on the electric power system in terms 

of additional generation requirements. As demonstrated by utility system load duration 

curves, current electric power systems have large amounts of underutilized capacity. This 

excess capacity could potentially provide electricity to PHEVs provided the utilities have 

some control over when charging occurs. We did not evaluate system-wide effects of 

uncontrolled charging; however, we would anticipate significant negative impacts if this 

were allowed at a large scale. Typical summer peak for much of the United States occurs 

in the late afternoon (4-6 p.m.), and this time has a strong coincidence with the end of the 

daily work cycle, and possible beginning of an “uncontrolled” PHEV charge cycle. It is 

possible that the first generation of PHEVs will not have utility-controlled or “smart” 

charging, especially in areas where customers are on simple flat rates. While it is likely 

that utilities will quickly address this possibility, this issue adds even more incentive to 

create electricity pricing structures that actually reflect the marginal costs of electricity. 

The dispatchable load offered by PHEVs could increase the minimum system load, 

increase the utilization of baseload units, and decrease plant cycling all without 

increasing the need for new generation assets. It is assumed that if a utility can add load 

to existing generators, these “marginal” sales can be made at just the variable cost of fuel 

and O&M, which can be quite low. In this manner, the system benefits would (and 

probably should) go to PHEV owners. However, some of the benefits, such as decreased 

O&M from decreased cycling, might potentially be spread across all consumers. 

Additional study is required to assess the appropriate distribution of the economic 

 21
benefits of PHEVs in customer rate structures in regulated and deregulated electric power 

systems. 

It is more difficult to make general conclusions about the discharge benefits of PHEVs. 

While PHEVs are ideally suited for short-term ancillary services, their use for firm 

peaking capacity may be restricted by their limited battery capacity and uncertainty about 

availability. Utilities may be unwilling to replace traditional generation capacity with 

PHEVs, unless they can be assured of reliable availability over extended periods. 

However, even at relatively low per-vehicle capacity, moderate penetration of PHEVs 

could replace a substantial fraction of the capacity currently in place to meet system 

“super peak” and the peak reserve margin. This could facilitate the retirement of older 

peaking units with high emissions and low efficiency such as diesel generators and older 

gas, oil, and coal-fired steam plants. 

6) Future Work 

This report provides an overview of possible utility system impacts of large-scale 

deployment of PHEVs. However, it does not quantify these possible financial benefits of 

improved utility system operation to the utility, ratepayers, or PHEV owners. Future 

analysis projects at NREL will include detailed modeling of a specific utility system 

under various scenarios of PHEV penetration. This analysis will quantify the financial 

benefits described above, examine implications for existing electricity rates, and 

potentially provide guidance for development of rate structures appropriate for PHEV 

owners. 

This analysis also does not evaluate various environmental impacts of PHEVs. PHEVs 

will reduce emissions from combustion of gasoline, and increase emissions from 

baseload electricity generation units. One previous analysis demonstrated positive net 

emissions impacts from PHEVs when charging electricity is derived from advanced, 

high-efficiency gas-fired generators.37 However, much of the off-peak capacity available 

for PHEVs in the United States is in existing coal-fired units.38 Future analysis at NREL 

will investigate emissions impacts of PHEVs where electricity is derived from a variety 

of current and future generation technologies. 

Another issue raised by potential large-scale deployment of PHEVs is the potential 

enabling of large-scale deployment of intermittent renewables such as solar and wind. 

We have performed a preliminary analysis of the synergism between distributed PHEV 

energy storage and intermittent renewables39 and will continue to analyze the possibility 

of reducing the use of fossil fuels for both the transportation and electric power sectors 

via the use of intermittent energy sources. 

 

37 Electric Power Research Institute (2002). 

38 Denholm, Paul, and T. Holloway. (2005). “Improved Accounting of Emissions from Utility Energy 

Storage System Operation,” Environmental Science and Technology. 39(23), 9016-9022. 39 Short, W. and P. Denholm (2006).”A Preliminary Assessment of Plug-in Hybrid Electric Vehicles on 

Wind Energy Markets,” NREL, TP-620-39729. 

 22
Appendix: Vehicle Capacity Credit Using IC Engine Run 

Given the limited battery capacity and potentially limited state of charge at demand peak, 

utilities would probably apply a relatively small capacity credit to individual vehicles. 

The limitation imposed by battery capacity can be partially eliminated by allowing the 

PHEV IC engine to run. Because most peaking generators are run for a very small 

number of hours per year, it may be acceptable for some fraction of vehicles to run their 

engines to provide firm capacity. 

Allowing a utility to remotely start and control privately owned vehicles raises many 

concerns that are not trivial and easily dismissed. Implementing this capability will 

require addressing safety issues, such as adequacy of ventilation in open parking garages 

and the need for potentially costly interlocks required to prevent vehicle operation in 

closed garages. Vehicle operation in enclosed garages raises issues of home and vehicle 

security, and the large amount of heat generated by the IC engine. The cooling systems of 

vehicles may have to be upgraded to reject the heat that would be produced while 

operating as a stationary generator, especially because the planning capacity of the 

vehicles would most likely be rated at their capacity on hot summer days. While these 

issues may not be insurmountable, they may restrict the availability of peak reserve 

capacity from IC engine operation. 

Using the base capacity values from Table 3, Figure A.1 illustrates how the average pervehicle capacity credit increases as a function of the fraction of vehicles allowed to run 

their IC engines. This chart assumes that the continuous thermal limit of the IC engine is 

5 kW. 

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0% 5% 10% 15% 20%

Fraction of Vehicles that Can Run IC Engine

Per Vehicle Capacity Credit (kW)

Case 4

Case 3

Case 2

Case 1

Figure A.1: PHEV Per-Vehicle Capacity Credit 

Figure A.1 illustrates that IC engine run capability could substantially increase the system 

peaking capacity offered by PHEVs. However, additional analysis is required to evaluate 

 23
the economics and overall systems benefits. Of particular importance would be the hours 

of IC engine operation and the number of utility-initiated engine starts. Also, while it will 

require a detailed regional analysis, it is possible that using modern distributed gasoline 

IC engines located close to load centers could be cleaner than alternatives used for 

extreme peak and emergency conditions. 

 24
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4. TITLE AND SUBTITLE

An Evaluation of Utility System Impacts and Benefits of Optimally 

Dispatched Plug-in Hybrid Electric Vehicles 

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 NREL/TP-620-40293 

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P. Denholm and W. Short 

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14. ABSTRACT (Maximum 200 Words)

Hybrid electric vehicles with the capability of being recharged from the grid may provide a significant decrease in oil 

consumption. These “plug-in” hybrids (PHEVs) will affect utility operations, adding additional electricity demand. 

Because many individual vehicles may be charged in the extended overnight period, and because the cost of 

wireless communication has decreased, there is a unique opportunity for utilities to directly control the charging of 

these vehicles at the precise times when normal electricity demand is at a minimum. This report evaluates the effects 

of optimal PHEV charging, under the assumption that utilities will indirectly or directly control when charging takes 

place, providing consumers with the absolute lowest cost of driving energy. By using low-cost off-peak electricity, 

PHEVs owners could purchase the drive energy equivalent to a gallon of gasoline for under 75 cents, assuming 

current national average residential electricity prices. 

15. SUBJECT TERMS

plug-in hybrid electric vehicle; PHEV; analysis; transportation; carbon emissions; energy; oil; gasoline; fuel; fuelefficient vehicles; utilities; gasoline; electricity demand; PHEV charging; Walter Short; Paul Denholm. 

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