Electric power requirement in California for large-scale production of hydrogen fuel

Electric power requirement in California for large-scaleproduction of hydrogen fuel

Paul Kruger*

Civil Engineering Department, Stanford University, Stanford, CA 94305, USA

Abstract

Substitution of hydrogen for fossil fuels in motor vehicles will require a signi®cant growth of electric energyconsumption, especially in high growth rate states such as California. A major concern is the magnitude of theadditional electric power capacity necessary to build a large-scale hydrogen fuel industry in California to

accommodate the fuel demand of a 30-million vehicle ¯eet. Electrolysis of water may be the only practical means toproduce hydrogen in su�cient quantity without use of fossil fuels for so large a vehicle ¯eet. A dynamic model wasused to estimate the increasing annual electric energy requirement to sustain long-term growth of adequate

hydrogen fuel production in two time sequences. The ®rst extrapolates historic data on population, vehicle, andenergy statistics from California State agencies to the year 2010 when a fuel-cell engine vehicle industry could beginto expand rapidly. The second time sequence uses the 2010 values as the initial conditions to examine a range of

growth scenarios to the year 2050 when a signi®cant fraction of the total California vehicle ¯eet could be operatedwith hydrogen fuel. The results of the model calculations show that even with improved energy consumptione�ciency of electrolytic production facilities, the additional electric energy demand to sustain replacement growth ofhydrogen fuel in the ¯eet will require installation of additional generating capacity. # 2000 International

Association for Hydrogen Energy. Published by Elsevier Science Ltd. All rights reserved.

1. Introduction

The potential for public acceptance of hydrogen as amotor vehicle fuel has increased markedly as a result

of two major environmental desires: (1) a reduction in

global emission of carbon dioxide from combustion of

fossil fuels; and (2) a reduction in local emission ofnitrogen oxides in automobile exhaust gas. The ®rst

concern enhances the broad potential for hydrogen as

a non-carbon fuel to the extent that the reduction in

carbon-fuel combustion can be achieved with an accep-table level of economic cost. The second concern

resulted in a mandate by the State of California to

introduce zero-emission vehicles into the state's vehicle

¯eet. The mandate requires that 10% of all new ve-

hicles starting in the year 2003 be zero-emission ve-

hicles. Although, currently only electric-battery

powered vehicles qualify as zero-emission vehicles,

large-scale substitution of gasoline as the primary

transportation fuel in the future will likely involve

large numbers of essentially zero-emission fuel-cell

powered vehicles that use hydrogen as fuel. Large-scale

production of hydrogen by electrolysis of water as an

expanding industry could o�set the reduction in gaso-

line and diesel fuels for transportation. The replace-

ment of fossil fuels by hydrogen produced with non-

International Journal of Hydrogen Energy 25 (2000) 395±405

0360-3199/00/$20.00 # 2000 International Association for Hydrogen Energy. Published by Elsevier Science Ltd. All rights reserved.

PII: S0360-3199(99 )00056-7

* Tel.: +1-650-493-4284; fax: +1-650-493-5122.

fossil energy sources would alleviate both environmen-

tal concerns in the State of California.As the technology for fuel-cell engines develops

rapidly in the automobile industry, a concomitant

industry for large-scale production of hydrogen isneeded with technology advances in hydrogen pro-

duction methods, storage and delivery systems, safety,and economics. Improvements in these technologiesare reported periodically, for example, annually by the

National Hydrogen Association (e.g. [14]) and bi-annually by the International Association for Hydro-gen Energy (e.g. [13]). Although several chemical and

physical processes are under study for production ofhydrogen, other than reforming with natural gas, elec-

trolysis of water currently appears to be the only prac-tical means to produce hydrogen in large quantity as afuel. In California alone, where the vehicle ¯eet might

reach some 30 million vehicles by the year 2010,achieving a signi®cant reduction in gasoline and dieselfuels will require an intensive growth of an alternate

fuel industry.The use of hydrogen as a motor vehicle fuel has

been encouraged by environmental groups that antici-pate generation of the necessary electric power for fuelproduction by alternate energy resources (such as

solar, wind, biomass, and geothermal). However, amajor concern becomes the magnitude of the ad-ditional electric power necessary to build a large-scale

alternate fuel industry in California to accommodatethe growth of a 30-million vehicle ¯eet. The fraction of

the ¯eet that could run on hydrogen fuel depends notonly on the production rate of fuel-cell engine vehicles,but also on the widespread availability of su�cient

hydrogen fuel in a distribution infrastructure compar-able to that of gasoline today. The energy requirementto create and sustain a fuel demand for so large a ve-

hicle ¯eet could be much greater than any single pri-mary energy resource could provide. Thus, an estimate

of the potential magnitude of the total power require-ment is desirable to assist in the long-range planningneeded to ensure an adequate fuel supply into the

future.An estimate of the electric power capacity that

would be needed to sustain long-term growth of ade-quate hydrogen production as a motor-vehicle fuel wasmade with a dynamic model which incorporates fore-

cast growth of population and vehicle ¯eet in Califor-nia over the next ®fty years in two time sequences. The®rst uses historic data from State of California

agencies on population, vehicle ¯eet composition,mean annual travel, and fuel economy to derive the in-

itial conditions for the year 2010 when the growth ofhydrogen fuel-cell engine production is expected toaccelerate rapidly. The second time sequence examines

a range of possible fuel-cell vehicle growth rates overthe next 40 years, to 2050, to estimate the magnitude

of the hydrogen fuel demand for large-scale substi-tution of gasoline and the necessary electric power ca-

pacity to achieve it based on anticipated electric-energye�ciency of hydrogen production by water electrolysis.

2. The HZEV-¯eet electric energy demand model

The model to extrapolate existing conditions to 2010

and examine potential electric energy shortfall through2050 was prepared with the commercially availableStella II dynamic modeling software [10]. The model

speci®es the relationships between the dynamic com-ponents of the system and describes the processes thatdetermine future properties of the components from

the initial conditions. Equations in the system are ®nitedi�erence equations, solved by Euler's method or 2ndor 4th-order Runga±Kutta methods. A schematic dia-gram of the model for the ®rst time sequence (1990±

2010) is shown in Fig. 1.Inputs of population and per-capita vehicle owner-

ship data, in the ®rst column of the diagram, are used

to calculate the annual vehicle ¯eet size. The popu-lation component extrapolates existing census data.Extrapolation of vehicle registration data is more com-

plex due to (1) the fast-changing mean annual growthrate in vehicle registrations; and (2) the change in a�u-ence in California with a corresponding change in ve-

hicle ownership. The model calculates initial andfuture ¯eet size by the product of the steady growingpopulation and a small saturation growth rate attribu-ted to a�uence. For the model, the actual 1990 vehicle

¯eet for California was grouped into four applicationcategories based on the assumption that introductionof hydrogen fuel in large-scale quantities would be by

application type of vehicle, in order of easiest-to-im-plement by vehicle type. The applications consider therelative importance of such factors as range of travel

from central refueling locations, total mileage, fueleconomy, and emission factors of exhaust gases. Thefour vehicle types in the fuel-demand model consist of

the following.

. Autos Ð small vehicles that travel for convenienceof individuals (e.g. private cars, taxis, motorcycles).

. Vans Ð delivery vehicles that routinely carry sta�

and passengers (e.g. to airports, hospitals, sites forrepair services) or goods (e.g. small packages, mail,appliances).

. Buses Ð large vehicles (including trailers and mobilehomes) that transport people within de®ned areas(e.g. school district, city, state).

. Trucks Ð all other large vehicles that carry heavygoods and materials or perform work within thestate.

P. Kruger / International Journal of Hydrogen Energy 25 (2000) 395±405396

Fig.1.Schem

aticdiagram

oftheHZEV-Fleet

electric

energydem

andmodel

P. Kruger / International Journal of Hydrogen Energy 25 (2000) 395±405 397

The results of the estimates for the vehicle ¯eet are

combined with the input for vehicle tra�c and fuel

economy (for the four vehicle types) to calculate the

total fuel demand for the ¯eet. Data from the several

manufacturers of electrolyser systems were used to pre-

pare an input function for the electric power demand

component. Data for total electric energy demand,

peak power demand, and system capacity requirements

were extrapolated to estimate electric energy consump-

tion and anticipated additional power capacity, if any,

needed to meet the expected ¯eet fuel demand.

3. Input data for the State of California

The data for the model components were obtained

from the State of California agencies, except for the

electrolyser energy consumption data, which were pre-

pared from data provided by four electrolyser equip-

ment manufacturers. The speci®c data are discussed

for each component.

3.1. Population

Data for the population of California and its growth

are well documented. Historic census data since 1940(http://www.census.gov/population/censusdata, 1998)are shown in Table 1 in comparison to US population

data. California population shows a steady fractionalgrowth from 5.2% in 1940 to 12% in 1990. The popu-lation mean annual growth rate (m.a.g.r.), shown as a

regression line in Fig. 2, was 2.84%/a over the 50-yearperiod. A forecast of population from 1996 to 2020,used in Caltrans [2] to estimate future transportationdata, is shown in Fig. 3. The data were quoted from

the California Department of Finance who assumedthat the population annual growth rate would declinefrom 1.8% in 1997 to 1.4% in 2020. The resulting

m.a.g.r. was 1.6%/a, about 56% of the historicm.a.g.r. In setting initial conditions for 2010, it wasnoted that the population would be 52.5 million people

based on historic growth rate data compared to 40.9million people based on the CDOF-assumed growthrate data. The more conservative value of 40.9 millionpeople was selected for the model initial population in

2010.

3.2. Vehicle Fleet

Data for the vehicle ¯eet in California were obtained

from several state agency sources, each having speci®cinterest in accumulating the data. A primary sourcewas the California Department of Motor Vehicles

(CDMV), responsible for licensing the vehicles thattravel within the state. The major record is containedin the annual report on Èstimated Fee-Paid Vehicle

Registrations by County'. Data were provided byCDMV from 1980 to 1997 for vehicle categories ofautomobiles, trucks, trailers, and motorcycles. As a®nancial report, the annual data also list in addition to

Fig. 2. Historic population of California (from US census

data).

Fig. 3. Forecast population data from 1996 to 2020 (from

Caltrans [2]).

Table 1

California populationa

Year California (106) United States (106) Fraction (%)

1940 6.907 132.165 5.23

1950 10.586 151.326 6.70

1960 15.717 179.323 8.76

1970 19.971 203.302 9.82

1980 23.668 226.542 10.45

1990 29.760 248.710 11.97

a Source: http://www.census.gov/population/censusdata

(1998).


the data for all counties in the state, vehicles with feespaid as òut-of-state' registrations and vehicles based

in other states which pay fees to operate in California.A second source of data from CDMV was the `Statisti-cal Record on Motive Power, Body Type and Weight

Division, for Automobiles, Motorcycles, CommercialTrucks and Trailers'. The data summarized for ®le sta-tus of 28 February 1998 [3] characterizes the regis-

tration data by many body types identi®ed by codeletter and description. The report does not includeregistrations of mobile homes (body type CCHMP)

which are performed by the California Department ofHousing and Community Development.Another major source of vehicle ¯eet data was the

California Department of Transportation (Caltrans).

The report California Motor Vehicle Stock, Travel andFuel Forecast [2] provides forecasts from 1996 to 2020for California population and a�uence factors, as well

as vehicle data and mean annual travel and fuel econ-omy. The vehicle data were summarized by the fourapplication types for the model vehicle types. The

report also provided data for annual travel (in 109 ve-hicle miles travel), mean ¯eet vehicle fuel consumption(in gal/year), and mean ¯eet fuel economy (in mi/gal).

The data from CDMV show a rapid change in theannual growth rate of vehicle registrations. Fig. 4shows the historic data for the period 1980±1997. Them.a.g.r. was 1.89%/a for automobiles and 2.16%/a for

the total ¯eet. Regression analysis of the data for theperiod 1985 to 1997 showed a m.a.g.r. of 1.19%/a forautomobiles and 1.35%/a for the ¯eet. Fig. 5 shows

the data for the most recent 7 years in which them.a.g.r. decreased further to 0.21%/a for automobilesand 0.43%/a for the ¯eet. In contrast, Fig. 6 shows the

forecast data from Caltrans [2] through 2010 in whichthe m.a.g.r. from 2000 to 2020 is 2.04%/a for auto-mobiles and 2.07%/a for the ¯eet. Because of the greatuncertainty in estimating the ìnitial' ¯eet size in 2010,

the model is designed to calculate the ¯eet size basedon the steadily growing population and an estimate ofa�uence given by a conservative saturation growthrate (in vehicles per capita, VpC) patterned after the

observed history of essentially constant 0.55 VpC forthe Los Angeles metropolitan area over the periodfrom 1980 to 1990 [11]. The model imposes a maxi-

mum value of 0.65 VpC on the growth rate of auto-mobiles over the initial and scenario periods. Theother three application-type vehicles, with much less

impact on the totals, have smaller maximum fractionalincreases.

3.3. Vehicle tra�c

The vehicle travel activity data for the model were

obtained from the Caltrans [2] forecast by groupingthe many vehicle-type data into mean values for thefour application-type vehicles. The initial values for1990 were based on proportionate fractions of the in-

State registration totals for each type. The data for the

Fig. 5. Vehicle registrations in California, 1990±1997 (from

CDMV [3]).

Fig. 6. Forecast vehicle ¯eet from 1996 to 2020 (from Cal-

trans [2]).

Fig. 4. Vehicle registrations in California, 1980-1997 (from

CDMV [3]).


total ¯eet were compiled from their forecast data ontotal statewide vehicle miles traveled, vehicle fuel con-

sumption, and vehicle fuel economy.

3.3.1. Vehicle miles traveledThe forecast data for vehicle miles traveled on Cali-

fornia roads were given annually by Caltrans [2] for1996±2020 based on estimated vehicle sales and on-road vehicle ¯eet fuel economy. The forecast annual

increments ranged from 3.6% in 1998 decreasing to1.9% by 2020. The annual VMT data were summar-ized for air quality conformity analysis purposes in 5-year increments from 1990 to 2020. These data, given

in Table 2, were used for graphic input to the modelthrough 2010 with the initial value for 1990.

3.3.2. Vehicle fuel consumption

Statewide fuel consumption represents total gasolineand diesel fuel used on all public roads. The value for1996 was 15.2 billion gallons and is expected toincrease for autos and all types of trucks, but with

slowly decreasing annual percentage changes. The totalfuel consumption for the four application type vehiclescan be estimated in the model, but the vehicle tra�c

component requires only the vehicle miles traveled andthe fuel economy data.

3.3.3. Vehicle fuel economyForecast fuel economy was made in Caltrans [2]

with explicit assumptions on the fuel economy of newvehicles entering the ¯eet each year using CDMV ve-hicle population pro®les and the EPA gas mileage

guides. Motorcycles were maintained at a constantvalue of 50 mpg. The data were compiled as harmonicaverage fuel economy by weighting the number of ve-

hicles by stratum and by the annual miles of traveland fuel economy of the stratum. The value for thetotal ¯eet for 1996 was 18.34 mpg and is expected toimprove steadily through the forecast period on the

assumption that new car ¯eet fuel economy will remainat 27.5 mpg while replacing older and lower fuel e�-ciency vehicles. These data were used in the model by

a graphic input curve based on linear regression of the

data through 2010 and extrapolated back annually to

1990 for the initial value.

3.4. Electrolyser energy consumption

The overall electric energy consumption in future

electrolysis plants for large-scale industrial production

of hydrogen becomes a major economic parameter for

its success as a replacement for gasoline. Energy con-

sumption, in turn, depends upon many design par-

ameters, such as cell size and voltage, current density,

and process temperature. Several processes are avail-

able for water electrolysis ranging from established al-

kaline (AWE) systems to developing advanced

methods, such as inorganic membrane (IME), solid

polymer (SPE), and high-temperature (HTE) electroly-

ser systems. A review of these processes is given by

Dutta [8].

For estimation of future electric energy demand, two

energy consumption values are needed: (1) an initial

value for the mean energy consumption in current-

technology electrolyser equipment designed for large-

scale installations; and (2) a basis for extrapolating the

value from technology improvements in the future.

Data for selecting these values in the model were com-

piled from several sources, including literature refer-

ences and direct communications with electrolyser

manufacturers. A summary of the data is given in

Table 3.

The Fluor Daniel Inc. [9] report to the Bonneville

Power Administration provided a range of current

values for alkaline and other electrolyser technologies.

In their design system for a 100 MW plant producing

21,788 Nm3/h, the energy consumption value was 4.4

kWh/Nm3. The Norsk Hydro data (A. Cloumann, pri-

vate communication, 1998) was based on the paper by

Cloumann et al. [7] for a 265 MW plant producing 396

million Nm3/yr. The value of 4.9 kWh/Nm3 was noted

to be for a high current density system which provides

a lower energy unit cost. The Teledyne Brown Engin-

eering data (C. Williams, private communication,

1998) was for their HP size hydrogen generating plant.

The data from Stuart Energy Systems Inc. (W. Cutler,

private communication, 1998) was based on their

report to the Ford Motor Company, `FCV Fuel

Supply Infrastructure: The Electrolysis Option', which

examined a central electrolysis plant producing 38 tons

of hydrogen per day. A value of 4.5 kWh/Nm 3 was

obtained from earlier data of Stuart and Fairlie [16]

based on a 100 MW-size plant producing 2 metric tons

of hydrogen per hour. For the model, input data was

provided as a graphic function in time with a linear

gradient of the model values listed in Table 3.

Table 2

Total statewide travel distancea

Year Travel distance (109 VMT)

1990 259.0

1995 277.0

2000 314.9

2005 358.5

2010 399.7

a Source: Caltrans [2].


3.5. Electricity supply

Electric energy data for the State of California areavailable from the California Energy Commission bothin report form and on the Internet. Generation data

for 1983±1997, compiled from the state's electric utili-ties, alternate energy suppliers, and imports, wereobtained from historical energy statistics [4,6]. They

are shown in Fig. 7 with its regression m.a.g.r. of1.73%/a. Peak power demand for 1990 was 50.2 GWat a historic m.a.g.r. of about 2.0%/a. Forecasts fromCEC [5] show electric energy demand growing from

265 TWh in 2000 to 325 TWh in 2015, at a m.a.g.r. of1.34%/a. The forecast for peak capacity demandgrows from 55.4 GW in 2000 to 68.0 GW in 2015 at

m.a.g.r. of 1.37%/a. The forecast for system capacitygrows from 64.5 GW in 2000 to 78.0 GW in 2015 atm.a.g.r. of 1.27%/a. CEC [6] noted that the estimated

electricity consumption growth rate to 2007 was 1.8%/a. For the model calculations, the values selected werem.a.g.r. of 1.49%/a for electric energy demand, 1.24%/a for peak power demand, and 1.35%/a for system ca-

pacity to utilize the reported history through 1997.Table 4 summarizes the initial value and growth rateof the parameters used for the fuel demand calcu-

lations for the period 1990-2010.

4. Results of the calculations for 2010 initial conditions

The ®rst phase of the study was made with the fourapplication vehicle types as noted in Fig. 1. The outputdata were compiled for each year from 1990 through

2010 in three tables: (1) population and vehicle ¯eet;(2) annual fuel demand (as gasoline); and (3) electricenergy demand. A summary of the data with the calcu-

lated initial values for the year 2010 are given in Table5 together with the values forecast in Caltrans [2].The extrapolation of existing data for California by

the model follows the forecast of Caltrans [2] except

for the ¯eet size, for which the value used by Caltransis smaller than the total ¯eet registered by the Depart-ment of Motor Vehicles. Some uncertainty exists in

whether either value covers all vehicle types on theroad and represents the total ¯eet using Californiaroads. For examining the potential growth scenarios

over the period 2010±2050, the di�erences are prob-ably not signi®cant. Another observation in Table 5 isthe calculated fuel demand based on current vehicletechnology, utilization, and performance. The result

shows a fuel demand in 2010 of 22.7 billion gallons ofgasoline. Conversion of the fuel demand on an equival-ent energy basis indicates that about 250 billion Nm3

of hydrogen would have been required if all the ve-hicles were fueled with hydrogen at the same automo-tive e�ciency. The electric energy consumption needed

to produce this much hydrogen would have beenabout 1020 TWh, about 3-times the extrapolated elec-tricity demand of 309 TWh in California for 2010. For

the higher e�ciency of hydrogen fueled vehicles, theactual hydrogen and electric energy consumptionwould have been proportionally less.

5. Scenarios for hydrogen fuel demand, 2010±2050

Estimates of hydrogen fuel demand based on the in-itial conditions in 2010 require consideration of severalassumptions, including the basis for the following.

1. Initiation of a hydrogen-fuel vehicle industry start-ing before and reaching an initial value in 2010.

2. Estimation of fuel consumption by application type

Table 3

Summary of electrolyser energy consumption data used for the period 1990±2050

Data source Present technology (kWh/Nm3) Projected value by 2010 (kWh/Nm3) Optimistic value by 2050 (kWh/Nm3)

Fluor-Daniel 4.4 n/a n/a

Norsk Hydro 4.9 4.1±4.3 3.6±3.7

Teledyne Brown 4.3 3.8 2.5

Stuart Energy 4.7 n/a n/a

Model Values 4.5 4.0 3.5

Fig. 7. Electric energy generation in California, 1983±1997

(CEC [6]).


of vehicle as they become commercially signi®cant.

3. Estimation of the mean annual growth rate of the

hydrogen-fuel vehicle industry over the 40- year

period.

Some of the parameters in the model can be ®xed.

It is assumed that hydrogen fuel-cell engine vehicles

will be approved as `zero-emission vehicles' by the

Air Resources Board of the California Environmen-

tal Protection Agency and that utilization will be

encouraged at least as much as for electric-battery

powered vehicles. It is assumed that the range of

travel per tankful, cost per re®ll, and reduction in

exhaust-gas emission will be su�cient for public

acceptance of hydrogen fuel and that the mean

annual travel distance per vehicle will be equal to

that for gasoline.

The basis for selecting an initiation date for com-

mercial sale of hydrogen fuel-cell vehicles is di�cult,

but if there is a real potential for industrial develop-

ment, it should be plausible to begin manufacture

before 2010. The actual number of vehicles on the

road in 2010 is not as important as the potential

m.a.g.r. after 2010. As an optimistic basis for in-

itiation, the assumption used in Kruger et al. [12] for

examining the potential for air quality improvement in

the Tokyo air basin was adapted in modi®ed form

from the revised mandate of the Air Resources Board

that requires 10% of all new cars sold in California in

2003 be zero-emission vehicles. The model assumes a

conservative starting value in 2003, in which only 1%

of the àpproved-technology' vehicles sold in California

in 2003 will be hydrogen-fueled vehicles and that the

Table 4

Input parameters for calculation of fuel demand for 1990±2010

Parameter (units) Initial value (1990) Growth rate (%/a)

Population (106) 29.76 1.60

Ownership (VpC)

Automobiles 0.618; max: 0.65 0.021

Total ¯eet 0.857; max: 0.87 0.043

Travel distances (109 vmt)

Automobiles 186.8 graph(t)

Total ¯eet 259.0 graph(t)

Fuel economy (mpg)

Automobiles 21.48 graph(t)

Total ¯eet 17.96 graph(t)

Electrolyser e�ciency (kWh/Nm3) 4.5 graph(t)

Electric energy

Energy demand (TWh) 229 1.49

Peak power demand (GW) 50.2 1.24

System capacity (GW) 55.9 1.35

Table 5

Output values for 2010 initial conditions

Parameter Model value Forecast

valuea

Population (106) 40.88 40.94

Ownership (VpC)

Automobiles 0.62 (0.51)

Total ¯eet 0.86 (0.71)

Fleet size (106)

Automobiles 25.3 21.0

Total ¯eet 35.1 29.1

Travel distance (109 vmt)

Automobiles 276 275

Total ¯eet 400 400

Fuel demand as gasoline (109 gal) 22.7 21.0

Electricity demand (TWh) 309 ±

a Adapted from Caltrans [2].


production growth rate will be a modest 10%/a

through 2010.

The second assumption, estimation of fuel economy,

was based on two considerations: (1) fuel economy is a

function of loaded weight; and (2) literature values of

expected fuel economy are adequate for scenario

analysis. To simplify the model calculations based on

sparse literature data for various application types of

vehicle, two application types were used in the second

phase of the model: automobiles and heavy-duty ve-

hicles. The fuel economy used for automobiles was 80

mpg, based on several studies, e.g. Ogden [15] (74

mpg), Berry [1] (95 mpg equivalent to GM EVI, and

re-estimated as 80 mpg for ®ve passenger loading). The

latter notes the announcement of Ford Motor Com-

pany (5 January 1996) of the Synergy 2010 concept

that the circa-2010 family car will triple the fuel e�-

ciency of a typical family car, which for the Caltrans

[2] assumption that new car ¯eet fuel economy will

remain at 27.5 mpg corresponds to a value of 82 mpg.

The fuel economy for the heavy-duty vehicles were

proportionally weighted for the 2010 calculated auto-

mobile and total ¯eet fuel economies as 40 mpg.

The third assumption is that the mean annual

growth rate for the period 2010±2050 cannot be

assumed for a technology yet commercially unproven.

Instead, the approach used in Kruger et al. [12] of

examining a range of potential growth rates was

adopted. A new industrial enterprise is considered suc-cessful if the m.a.g.r. exceeds a minimum of about10%/a and few enterprises have grown steadily at a

rate exceeding 40%/a. One notable exception was thehistory of the Ford Motor Company (private com-munication, 1996) in mass-producing automobiles at a

m.a.g.r. of 41%/a from startup in 1903 to the begin-ning of WW-I. The scenario analysis covers the rangeof m.a.g.r. from 10%/a to 40%/a, but adjusted to

asymptotic ®t to the estimated ¯eet size instead of con-tinuous exponential growth. The electric energy needed

Fig. 8. Scenario growth of HZEVs to replace forecast ¯eet

growth in California.

Table 6

Summary of growth scenario output data

Year M.a.g.r. (%/a) HFleet (106 veh) HFuel (109 Nm3) HElecEn (TWh) HSysCap (GW)

2010 ± 0.01 0.00 0.10 0.01

CAa 35.1 ± 309 74

2020 10 0.03 0.01 0.25 0.03

20 0.06 0.01 0.61 0.08

30 0.14 0.03 1.35 0.18

40 0.29 0.07 2.83 0.38

CAa 41.2 ± 355 85

2030 10 0.07 0.02 0.64 0.09

20 0.38 0.09 3.62 0.49

30 1.84 0.42 17.5 2.35

40 7.37 1.67 70.1 9.39

CAa 47.3 ± 408 97

2040 10 0.17 0.04 1.60 0.21

20 2.28 0.52 21.0 2.81

30 18.6 4.21 171 22.9

40 47.7 10.8 438 58.7

CAa 54.9 ± 468 111

2050 10 0.45 0.10 3.99 0.53

20 12.1 2.74 107 14.4

30 55.3 12.5 491 65.8

40 61.2 13.9 544 72.8

CAa 63.7 ± 538 128

a CA forecast extrapolation with no hydrogen-fuel vehicle component.


for producing the hydrogen at these growth rates wasadded to the extrapolated electric energy load. For the

scenario analysis, the 2010 initial number of àutos'(light vehicles) at 11,000 mi/yr and `trucks' (heavy ve-hicles) at 12,600 mi/yr were 5000 each (1% of new cars

in 2003). Although this initial number of vehicles for2010 is arbitrary, the output of the model can be line-arly scaled for any other given initial value of either

class of vehicle.

6. Results of the calculations for 2010±2050

The second phase of the study was made for thelight and heavy classes of vehicles with scenario vehicleproduction growth rates of 10±40%/a for the assumed

initial value of 5000 of each class from 2010 to 2050.The output data were compiled at each ®ve years intables of hydrogen vehicle ¯eet fuel consumption and

electric energy (and power) requirement in contrast tothe forecast growth in statewide electric energy (andsystem power capacity) expectations. A summary ofthe key values is given in Table 6. The comparison of

scenario growth of hydrogen fuel vehicles in relationto forecast growth of the California vehicle ¯eet isshown in Fig. 8. Even with one percent of the 10% in-

itiation of alternate fuel zero-emission vehicles in 2003,the relative contribution of hydrogen ZEVs will bequite small at any production growth rate until about

2025±2030 when the number of HZEVs become a sig-ni®cant portion of the total ¯eet. At a m.a.g.r. of20%/a, the number of HZEVs would represent about

23% of the total ¯eet in 2050. For m.a.g.r. above25%/a beyond 2030, the data show the diminishinggrowth rates needed to replace the entire forecast ¯eetsize with HZEVs. Table 6 shows the corresponding

rapid escalation of hydrogen production facilitiesneeded to provide the fuel for these HZEVs Even iflong-distance automobile travel is not yet feasible due

to limited distribution of hydrogen fuel, the growth ofhydrogen fuel production facilities would still beneeded for the centrally-fueled application HZEVs; in

these scenarios amounting to about 50% of the totalfuel requirement.Fig. 9 shows the electric energy requirement in Cali-

fornia for hydrogen fuel production as an additional

demand above the forecast electric energy demandgrowth curve (coincident with the curve for 10%m.a.g.r.). The electric energy demand for producing

the HZEV ¯eet fuel becomes correspondingly signi®-cant after the 2025±2030 time period of growth. Table6 provides the data for estimating the additional sys-

tem power capacity that will be needed to maintain theforecast growth in electric energy demand for all exist-ing and other newly-established applications.

7. Summary

The two-step model provides a convenient means toexamine the potential for initiating hydrogen-fuelengine vehicle production in the 2003±2010 time frame

based on extrapolation of existing conditions of popu-lation growth, a�uence factors of vehicle ownershipand travel, and desire to reduce global emission of car-bon dioxide and local emission of nitrogen oxides.

With technical success in commercial development offuel-cell engines and high-capacity electrolysis stationswith signi®cant growth of the industry, an examination

of the concomitant increased electric power demand isalso needed. The results of the study show that for theconditions forecast by California state agencies, if

hydrogen-fuel vehicle manufacture is commercially in-itiated by 2010, the electric power requirement wouldnot be a signi®cant deterrent during the start-up phasethrough the year 2025. However, after that, if

the industrial growth rate is maintained above about20%/a, the replacement of fossil fuel by hydrogen as atransportation fuel could become increasingly import-

ant. The HZEV replacement of the vehicle ¯eet inCalifornia could essentially be reached by 2050. Duringthis period, the need for additional electric power gen-

erating facilities will become acute. With the existinglong-period of regulatory review of new power plants,planning for additional system power capacity should

begin as soon as it is evident that a hydrogen-fuel ve-hicle industry is feasible.

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Electric power requirement in California for large-scale production of hydrogen fuel