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

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Contract No. DE-AC36-08GO28308

Wind Electrolysis:

Hydrogen Cost Optimization 

Genevieve Saur and Todd Ramsden

Technical Report

NREL/TP-5600-50408

May 2011 
NREL is a national laboratory of the U.S. Department of Energy, Office of Energy 

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

National Renewable Energy Laboratory

1617 Cole Boulevard

Golden, Colorado 80401

303-275-3000 • www.nrel.gov

Contract No. DE-AC36-08GO28308

Wind Electrolysis: 

Hydrogen Cost Optimization 

Genevieve Saur, Todd Ramsden

Prepared under Task No. H271.3710

Technical Report

NREL/TP-5600-50408

May 2011
NOTICE

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iii

Contents

1 Introduction and Key Findings ....................................................................................... 1

2 Background ....................................................................................................................... 3

3 Model Configurations ....................................................................................................... 4

3.1 Electrolyzers ................................................................................................................... 4

3.2 Wind Farm ...................................................................................................................... 5

3.2.1 Case 1—Low Wind Cost ........................................................................................ 6

3.2.2 Case 2—Current Wind Cost ................................................................................... 7

3.2.3 Wind Turbine Performance..................................................................................... 7

3.2.4 Wind Profiles .......................................................................................................... 7

3.3 Grid Pricing Structure ..................................................................................................... 9

3.4 Scenarios ....................................................................................................................... 10

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

4.1 Case 1—Low Wind Cost .............................................................................................. 12

4.2 Case 2—Current Wind Cost ......................................................................................... 14

4.3 Scenario Details—Current Wind Cost .......................................................................... 15

4.4 Detail Case Site—Current Wind Cost .......................................................................... 19

4.5 Sensitivity Case Site—Current Wind Costs ................................................................. 21

5 Conclusion ....................................................................................................................... 23

6 Recommended Future Work ......................................................................................... 24

7 References ........................................................................................................................ 25

List of Figures

Figure 1. Range of costs for wind electrolysis hydrogen production for different wind classes 

from power-balanced optimization scenario .......................................................................... 2

Figure 2. Wind electricity costs by wind class ............................................................................... 6

Figure 3. Wind electricity costs by wind farm capacity factor ....................................................... 6

Figure 4. Three-megawatt wind turbine power curve ..................................................................... 8

Figure 5. Range of wind sites used in study by wind class and capacity factor ............................. 9

Figure 6. Charge rates for six tiers of grid pricing (structure adapted from Fuel Cell Power 

model [11])............................................................................................................................. 9

Figure 7. Weekly rate structure (structure adapted from Fuel Cell Power model [11]) ............... 10

Figure 8. Cost of hydrogen for case 1 (low-cost wind), cost-balanced scenarios a and c ............ 13

Figure 9. Cost of hydrogen for case 1 (low-cost wind), power-balanced scenarios b and d ........ 13

Figure 10. Cost of hydrogen for case 2 (current wind cost), cost-balanced scenarios a and c ..... 14

Figure 11. Cost of hydrogen for case 2 (current wind cost), power-balanced scenarios b and d . 15

Figure 12. Wind farm size required to produce 50,000 kg/day H2 and cost of electricity at each 

site for each scenario ............................................................................................................ 16

Figure 13. Difference in cost of H2 between similar scenarios that do or do not buy summer 

peak ...................................................................................................................................... 17

Figure 14. Difference in unmet hydrogen among scenarios ......................................................... 18

Figure 15. Unmet hydrogen in scenarios that do not buy summer peak electricity ...................... 19

Figure 16. Example wind profile .................................................................................................. 20

Figure 17. Example scenario b ...................................................................................................... 21
iv

Figure 18. Example scenario d ...................................................................................................... 21

Figure 19. Sensitivity of cost of hydrogen for scenario d (power balanced, no summer peak) ... 22

List of Tables

Table 1. Electrolyzer Economic Parameters Based on the Independent Review Panel Report ..... 4

Table 2. Breakdown of Electrolyzer Depreciable Capital Costs .................................................... 5

Table 3. Wind Class Definitions (at reference height of 10 m) ...................................................... 5

Table 4. Case 1 Wind Cost Parameters from the Malcolm and Hansen Studya ............................. 7

Table 5. Case 2 Wind Cost Parameters from the Wiser et al. Study .............................................. 7

Table 6. Wind Turbine Power Conversion Parameters for a 3-MW Turbine ................................. 8

Table 7. Detailed Example ............................................................................................................ 20

Table 8. Sensitivity Values for High and Low Hydrogen Costs (2005$) ..................................... 23
1 

1 Introduction and Key Findings

Wind-based water electrolysis is a viable approach to producing greener hydrogen, holding 

promise to better utilize domestic renewable energy sources for the energy needs of the 

transportation sector. A wind-based electrolysis system can reduce greenhouse gas emissions 

from the transportation sector while integrating larger percentages of renewable energy into the 

electric grid. To enable a greater penetration of renewable energy resources, hydrogen 

production from wind-based electrolysis must be cost competitive. As a vehicle fuel, this means 

competing with gasoline or other vehicle fuels; as energy storage for the grid, this means being 

cost competitive with other grid electricity technologies. Hydrogen could be produced for $4/kg 

or less at some high wind class sites, class 4 or higher, However a bigger issue is the capacity 

factor, which needs to be 44% or better along with relatively high wind speeds. Along with low 

production costs, however, delivery and storage costs will also factor into the final cost of 

hydrogen, which calls for investigating a wider range of wind class sites, where geographical 

elements such as distance from end use should also be considered. This report compiles 

information on a range of wind class resources to help identify elements that must be balanced.

This report describes a hydrogen production cost analysis of a collection of optimized central 

wind-based water electrolysis production facilities. The basic modeled facility includes a number 

of low temperature electrolyzers and a collocated wind farm of a number of 3-MW wind turbines 

that produce electricity for the electrolyzer units. Shortfalls of wind-based electricity to meet 

electrolyzer electricity requirements can be made up by purchasing electricity from the utility 

grid at market prices; conversely, excess electricity from the wind farm beyond the needs of the 

electrolyzer system can be sold to the utility grid at market prices, lowering the overall cost of 

hydrogen produced. The National Renewable Energy Laboratory (NREL) completed a series of 

scenario optimizations using hour-by-hour modeling (8,760 hours per year), considering both 

wind power output for various wind profiles and estimations of hourly electricity market prices. 

The study was done as part of NREL and Xcel Energy’s Wind2H2 project to characterize the 

technical and economic implications of a large-scale wind electrolysis system. The analysis 

considers the technical requirements of a water electrolysis system and optimized sizing of 

system components required for a particular hydrogen output based on wind availability and 

market costs for electricity. This latest cost study of hydrogen production via wind-based water 

electrolysis builds on the work of earlier cost studies. An earlier NREL study examined the costs 

of wind-based water electrolysis, but it did not consider the purchase of grid electricity during 

times of low wind, leading to a low utilization of the electrolyzer subsystem [1]. A 2009 

independent review panel report on the state of low-temperature electrolysis analyzed hydrogen 

cost via wind electrolysis given recent advances in electrolyzer systems, though for costing 

purposes that analysis assumed that wind-based electricity would always be available to the 

electrolyzer system [2]. 

This study considers the optimal configuration of a water electrolysis production facility capable 

of producing a net 50,000 kg/day of hydrogen with a collocated wind farm as a renewable 

electricity source. Four wind farm sizing scenarios were considered, and hydrogen production 

cost modeling was conducted for two wind turbine capital cost cases: a low wind turbine cost 

case based on turbine costs from a 2006 NREL WindPACT study by Malcolm and Hansen [3], 

and a current cost case from a more recent 2009 wind turbine cost study, by Wiser et al. [4]. The 
2 

independent review panel report on the state of low-temperature electrolysis supplied the 

electrolyzer costs, supplemented with costs from an H2A Production model case study of central 

hydrogen production from water electrolysis [2, 5, 6]. The latter, higher, wind costs better 

represent the costs of hydrogen production expected given the recent rise in wind turbine costs. 

The lower wind cost case, however, is comparable to the wind electricity costs assumed in the 

2009 independent panel study, which concluded that hydrogen could be produced at a cost of 

$3/kg. 

The cost analysis of these sets of optimized systems shows that wind-based water electrolysis 

systems could produce hydrogen for less than $3/kg assuming lower wind turbine costs. Figure 1

shows example results for one of the detailed scenarios that optimizes the size of the wind farm 

by balancing the grid electricity bought with the wind electricity sold. The low wind costs 

represent wind turbine costs from a period of low wind costs in 2002, which are included for 

comparison due to their inclusion in other wind reports; however, current wind costs (blue bars) 

represent more realistic wind turbine costs from 2008 and beyond, which incorporate higher 

material and construction costs. Each data set in Figure 1, current wind cost and low wind cost, is 

the aggregate of the same set of wind sites (128). The range of costs is a function of the spread of 

wind speeds and capacity factors embodied in each wind class. Costs in the low wind cost case 

range from $2.83/kg to $7.83/kg. In the current wind cost case, they range from $3.72/kg to 

$12.16/kg. All costs are presented in 2005 dollars (2005$). This reinforces the independent panel 

findings that wind-electrolyzed hydrogen could be produced for as little as $3/kg at good wind 

sites. Even considering higher wind turbine costs, hydrogen could be produced in some class 4, 

5, and 6 wind areas for as little as $4/kg. 

Figure 1. Range of costs for wind electrolysis hydrogen production for different wind classes from 

power-balanced optimization scenario

Current Wind Cost

Low Wind Cost

0

1

2

3

4

5

6

7

8

9

10

11

12

13

1 2 3 4 5 6

Cost of Hydrogen ($/kg)

Wind Class
3 

2 Background 

NREL researchers developed an 8,760 hourly wind electrolysis optimization model based on the 

H2A Production and Fuel Cell Power models [6, 7]. The model can be configured to conduct 

technoeconomic analyses of different wind electrolysis facility configurations, each including a 

bank of low-temperature electrolysis units to produce hydrogen and a collocated wind farm 

comprising a number of 3-MW wind turbines. The basic functionality could also be 

accomplished by a system that was not entirely collocated as well. An 8,760 hourly grid pricing 

structure is included in the model based on six different daily and weekly charge rates— three 

summer and three winter to represent peak, partial-peak, and off peak time periods. The hour-byhour analysis integrates the hourly wind profile with the hourly grid pricing structure to calculate 

the resulting hydrogen production costs of various wind electrolysis system configurations. 

This initial analysis considers several grid-connected scenarios and an average hydrogen 

production rate of 50,000 kg/day, which is consistent with H2A Production model case studies 

for a central electrolysis plant [5]. The electrolyzers are relatively capital intensive, so this 

analysis assumes that they will be run at near maximum capacity with minimum avoidable 

downtime. Sustainable hydrogen production is met by using wind electricity for electrolysis 

when it is available and selling excess wind electricity to the grid to offset grid electricity that 

must be bought during times of low wind. 
4 

3 Model Configurations

3.1 Electrolyzers

The electrolyzer costs and assumptions used in this analysis come from the report on lowtemperature electrolysis by an independent review panel for a central electrolysis production site 

of 50,000 kg/day capacity [2]. The plant design capacity is 51,020 kg/day with a 98% operating 

capacity factor for a net capacity of 50,000 kg/day. The electricity requirements of the system are 

106 MW. Standard H2A assumptions were used for many of the economic assumptions [5, 8]. 

This includes a 10% internal rate of return and 40 year plant lifetime for a central production 

facility. Parameters adjusted to reflect the new study were total depreciable capital cost, 

electrolyzer efficiency, replacement time and costs, operating capacity factor, working capital, 

labor, production maintenance costs, other material costs, and land costs. Separating the total 

depreciable capital costs into direct and indirect costs reflected the independent review panel’s 

capital cost estimate. Table 1 lists the relevant parameters and their baseline values.

Table 1. Electrolyzer Economic Parameters Based on the Independent Review Panel Reporta 

Parameter Review Panel Baseline Value

Total Depreciable Capital Cost $50.1 milliona

Electrolyzer Efficiency 50 kWh/kg

Replacement Cost 25% of direct installed capital

Replacement Interval 7 years

Operating Capacity Factor 98%

Working Capital 5%

Other Material Costs $0

Land Costs $50,000/acre and 5 acres

Labor 10 full time equivalents

Production Maintenance Costs 2% of direct installed capital a The review panel [2] gave a value of $50 million for total depreciable capital costs. The value listed reflects a close 

approximation that separated the costs into direct and indirect costs. See reference [2] for more information.

For the direct costs, the uninstalled costs for the electrolyzer units were $384/kW ($800/kg/day 

and 50 kWh/kg) with an installation factor of 1.05 to reflect the relative ease of installing skidmounted units. Table 2 shows all depreciable capital costs.

H2A-based analysis of central wind electrolysis using this estimated breakdown of depreciable 

capital costs yields cost results consistent with the findings of the independent panel [2]. Using 

the estimated depreciable cost breakdown in Table 2 together with a constant electricity cost of 

$0.045/kWh, consistent with the independent panel, and the other independent panel cost 

parameters listed in Table 1, we calculated a hydrogen production cost of $3.00/kg [2]. This 

matches the independent panel’s results for the central wind electrolysis case; therefore, the 

capital cost assumptions are considered applicable for this detailed analysis.

We assumed a constant electrolyzer energy usage of 50 kWh/kg for this analysis. Although 

electrolyzers can be run at partial power with an effect on the overall system efficiency, the size 

of the system will generally necessitate 50 or more units run in combination. Therefore, for 

simplicity rather than any given unit running at partial power, the electrolyzer units would be 

sequenced on and off for more or less optimal efficiency. Additionally, the particular scenarios 

analyzed assume near-maximum operating capacity. 
5 

Table 2. Breakdown of Electrolyzer Depreciable Capital Costs

Parameter Value

Uninstalled Direct Capital Cost $40.8 million

Installation Factor 1.05

Direct Installed Capital Cost $42.9 million

Site Preparation 1% of direct installed capital

Engineering and Design 5% of direct installed capital

Project Contingency 10% of direct installed capital

Up-Front Permitting Fees 1% of direct installed capital

Total Depreciable Capital Cost $50.1 million

3.2 Wind Farm

Characterizing and modeling the costs of wind-based electricity production required obtaining 

wind turbine capital and operating costs, wind turbine performance, and wind profiles from 

several sources. 

Two sets of assumptions for wind turbine costs were modeled based on low costs in the Malcolm 

and Hansen study [3] and on current costs from the report by Wiser et al. [4]. For both cases the 

wind farm was modeled as a number of 3-MW turbines using a fixed charge rate of 12.1% for 

the capital costs. The fixed charge rate includes a 10% internal rate of return, 35% federal tax 

rate, and 6% state tax rate. No production tax credits or other incentives are included. The costs 

were separated into turbine installed capital and operations and maintenance (O&M). The costs 

from the Malcolm and Hansen study for wind turbines appear to be consistent with the singlepoint wind-based electricity cost used by the independent panel on electrolysis, and are included 

to better compare results from this hourly optimization analysis to the hydrogen production cost 

results reported by the independent panel. The costs from the more recent Wiser et al. study are 

assumed to reflect the current state-of-the-industry costs for wind turbine installations today. 

The overall resulting wind electricity costs of these wind turbine farms operating in particular 

wind locations can be characterized by wind class (Table 3) and capacity factor. In our analysis, 

the wind electricity cost is same for all modeled scenarios, being based on the same wind profile 

and cost assumptions for each scenario. Figure 2 and Figure 3 shows the electricity cost ranges 

under on different wind classes and capacity factors. 

Table 3. Wind Class Definitions (at reference height of 10 m)

Wind Class

Wind Density 

Minimum 

(W/m2

)

Wind Speed 

Minimum 

(m/s)

Wind Density 

Maximum 

(W/m2

)

Wind Speed 

Maximum 

(m/s)

Average Wind 

Speed

(m/s)

1 0 0.0 100 4.4 2.2

2 100 4.4 150 5.1 4.8

3 150 5.1 200 5.6 5.4

4 200 5.6 250 6.0 5.8

5 250 6.0 300 6.4 6.2

6 300 6.4 400 7.0 6.7

7 400 7.0 1000 9.4 8.2
6 

Figure 2. Wind electricity costs by wind class

Figure 3. Wind electricity costs by wind farm capacity factor

3.2.1 Case 1—Low Wind Cost

Case 1 modeling used the study by Malcolm and Hansen [3]. The data for their study were 

collected between 2000 and 2002, now considered a period of very low turbine prices. These 

costs are included for comparison consistency with other studies and to demonstrate the effect of 

0.00

0.05

0.10

0.15

0.20

0.25

0 1 2 3 4 5 6 7

Cost of Wind Electricity ($/kWh)

Wind Class

Low Wind Cost Current Wind Cost

0.00

0.05

0.10

0.15

0.20

0.25

0.00 0.10 0.20 0.30 0.40 0.50

Cost of Wind Electricity ($/kWh)

Wind Capacity Factor

Low Wind Cost Current Wind Cost
7 

different wind turbine costs. Table 4 shows the model parameters used, which reflect a 3-MW 

turbine.

Table 4. Case 1 Wind Cost Parameters from the Malcolm and Hansen Studya

Parameter Value (2005$)

Installed Turbine Capital Cost $1148/kW

O&M (includes replacement costs) $0.01234/kWh a

Reference [3]

3.2.2 Case 2—Current Wind Cost

The second case used a more current study [4], which reflects the most recent costs of wind 

turbine installations. These costs could be considered more consistent with the state of the 

industry for wind farms installed in 2009. Table 5 shows the parameters used depreciated to 

2005$ using the U.S. Energy Information Administration (EIA) Gross Domestic Product (GDP) 

Implicit Price Deflator Table [9].

Table 5. Case 2 Wind Cost Parameters from the Wiser et al. Studya

Parameter Original Value (2008$) Value (2005$)

Installed Turbine Capital Cost $2,120/kW $1,964/kW

Total O&M $0.008/kWh $0.00741/kWh a Reference [4]

3.2.3 Wind Turbine Performance

The wind turbines were based on a 3-MW turbine designed for a class 4 wind site, average 

annual wind speed 5.8 m/s at 10-m height. The height is adjusted to 100 m using the wind profile 

power law with standard 1/7 exponent. The power curve shown in Figure 4 was generated using 

a Rayleigh distribution curve using parameters in Table 6. The power conversion was used to 

estimate the power at different wind speeds in the 8,760 hourly analysis. 

3.2.4 Wind Profiles

Ten-minute interval wind profiles for 136 random sites in California from 2006 were obtained 

through NREL’s Western Wind Dataset [10]. Average wind speeds at 100 m ranged from 2.4 

m/s to 9.4 m/s, which covers class 1 to class 6 wind sites. The 10-minute interval data were 

averaged each hour to create an 8,760 hourly/year wind profile for each site. Wind profiles do 

vary year to year, but for this analysis using a snapshot of real wind data was appropriate. More 

detailed analysis of an individual site might also include effects of yearly variation, which were 

not performed here.
8 

Table 6. Wind Turbine Power Conversion Parameters for a 3-MW Turbine

Parameter Value

Mean Wind Speed at 10 m (m/s) 5.8

Rated Power (kW) 3,000

Rotor Diameter (m) 99

Wind Reference Height (m) 100

Hub Height (m) 119

Air Density (kg/m3) 1.225

Rotor Cp 0.50

Cut-In Speed at Hub (m/s) 3

Cut-Out Speed at Hub (m/s) 28.9

Power Law Shear Exponent 0.143

Mean Wind Speed at Hub Height 8.3

Rated Wind Speed 11.1

Net Annual Energy Production 88%

Availability 95%

Blade Soiling Losses 2%

Array Losses 5%

Figure 4. Three-megawatt wind turbine power curve

The range of sites for each wind class can be seen in the range of capacity factors shown in 

Figure 5. A variety of sites were analyzed to show a range of hydrogen production costs in 

different wind locations. Of the original 136 sites, 8 were removed because of very low capacity 

factor (<0.11) and would be marginal for wind production even under the best of circumstances. 

Using a large range of sites helps show the trade-offs that might be expected between lower wind 

production sites and better ones. In a fuller analysis, the distance of a site from the hydrogen 

demand would also play a factor in the final economic analysis. Our intention here, however, is 

to isolate only one element, wind electrolysis production of hydrogen. 

Annual Mean Wind 

Speed at reference 

height

Probability annual 

mean wind speed at 

reference height

0

2

4

6

8

10

12

14

0

500

1,000

1,500

2,000

2,500

3,000

3,500

0.0 5.0 10.0 15.0 20.0 25.0 30.0

Probability (%)

Power Output (kW)

Wind Speed at 100 m Reference Height (m/s)

Annual Mean Wind Speed at 

reference height

3-MW Turbine 

Rayleigh Probability Curve

Probability annual mean wind 

speed at reference height
9 

Figure 5. Range of wind sites used in study by wind class and capacity factor

3.3 Grid Pricing Structure

For modeling purposes, we developed an 8,760 hourly electricity pricing estimate for a grid 

pricing structure adopted from the Fuel Cell Power model [7, 11]. This estimate was based on a 

pricing structure that projected electricity prices on a per kilowatt-hour basis using six price tiers: 

summer peak, summer near-peak, summer off-peak, winter peak, winter near-peak, and winter 

off-peak. The base electricity price was set to $0.055/kWh, consistent with EIA price projections 

for average industrial electricity rates in 2005. The variance from this base for the six price tiers 

was based on actual hour-ahead pricing in the Southern California Edison ISO market, based on 

using actual price reports for typical summer and winter days. Figure 6 gives the six tiers.

Similarly, the six tiers for each hour in a typical week were assigned based on actual costs 

reported for the California ISO hour-ahead market, seen in Figure 7. The actual hour by hour 

rates resulted in an average electricity price of $0.053/kWh. These rates reflect an approximated 

electricity demand.

Figure 6. Charge rates for six tiers of grid pricing (structure adapted from Fuel Cell Power model [11])

0

1

2

3

4

5

6

7

0.0 0.1 0.2 0.3 0.4 0.5 0.6

Wind Class

Wind Farm Capacity Factor

Usage Charges Rate Type

Summer rates ($/kWh) Peak 4

Partial peak 5

Off-peak 6

Winter rates ($/kWh) Peak 1

Partial peak 2

Off-peak 3

0.050

0.039

Rate % of Base Rate

180

110

70

110

90

70

Rate ($/kWh)

0.099

0.061

0.039

0.061
10 

Figure 7. Weekly rate structure (structure adapted from Fuel Cell Power model [11])

3.4 Scenarios

We chose four scenarios for our wind-based water electrolysis analysis. The aim of the analysis 

was to determine the optimal wind electrolysis facility configuration for each scenario resulting 

in the lowest cost for production of hydrogen. A consideration in creating the scenarios was to 

not create situations in which wind subsidizes the cost of hydrogen by selling more and more 

wind electricity to the grid, thereby using the profits to drive down the cost of the hydrogen. The 

scenarios show some approaches to balancing the different products of the system. The 

electrolyzer facility was sized consistently to have an average output of 50,000 kg/day of 

hydrogen. Because of the capital intensity of electrolysis, we assumed that electrolyzers would 

be operated at maximum capability with a minimum of downtime for maintenance. The wind 

farm was then sized to meet the scenario requirement. All scenarios assumed that grid electricity 

could be purchased during times of low wind availability and wind electricity could be sold at 

the current grid rate when the output of the wind farm exceeds electrolyzer demand, except 

where specified. Selling wind electricity at the current grid rate has several implications: 1) this 

does not reflect a power purchase agreement for which the wind is purchased at a certain set 

price, 2) the wind selling price also does not include a production tax credit (PTC) or any other 

incentive, and 3) it may mean that wind electricity is sold at a rate below the cost. Each of these 

factors has an effect that this report does not address, but it is mentioned it for clarity. The 

following four scenarios represent different approaches to optimization and sustainable hydrogen 

production: 

• Scenario a: cost balanced—the cost of the grid electricity that is purchased is balanced to 

the wind electricity sold at grid rate. 

• Scenario b: power balanced—the amount of grid electricity purchased (in megawatthours) is balanced with the amount of wind electricity sold. 

• Scenario c: same as scenario a, cost balanced, but no grid electricity is purchased during 

summer peak periods. 

• Scenario d: same as scenario b, power balanced, but no grid electricity is purchased 

during summer peak periods. 

Hour

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

Sunday 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6

Monday 6 6 6 6 6 6 6 6 5 5 5 5 5 4 4 4 4 4 4 5 5 5 5 6

Tuesday 6 6 6 6 6 6 6 6 5 5 5 5 5 4 4 4 4 4 4 5 5 5 5 6

Wednesday 6 6 6 6 6 6 6 6 5 5 5 5 5 4 4 4 4 4 4 5 5 5 5 6

Thursday 6 6 6 6 6 6 6 6 5 5 5 5 5 4 4 4 4 4 4 5 5 5 5 6

Friday 6 6 6 6 6 6 6 6 5 5 5 5 5 4 4 4 4 4 4 5 5 5 5 6

Saturday 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6

Hour

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

Sunday 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 2 2

Monday 3 3 3 3 3 2 2 2 2 2 1 1 1 2 2 2 2 2 1 1 1 2 2 3

Tuesday 3 3 3 3 3 2 2 2 2 2 1 1 1 2 2 2 2 2 1 1 1 2 2 3

Wednesday 3 3 3 3 3 2 2 2 2 2 1 1 1 2 2 2 2 2 1 1 1 2 2 3

Thursday 3 3 3 3 3 2 2 2 2 2 1 1 1 2 2 2 2 2 1 1 1 2 2 3

Friday 3 3 3 3 3 2 2 2 2 2 1 1 1 2 2 2 2 2 1 1 1 2 2 3

Saturday 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 2 2
11 

In the scenarios, the optimization comes from sizing the wind farm to meet the requirements of 

the scenario. The electrolyzer is set up to use wind electricity from the collocated wind farm first, 

then grid electricity as required to meet the electrolyzer system’s needs. Excess wind electricity 

above the electrolyzer’s requirements can be sold to the utility grid at the current grid rate during 

times of high wind production. For power-balanced scenarios the amount of electricity purchased 

from the grid (on a megawatt-hour basis) is balanced with the amount of wind electricity sold to 

the grid. In the cost-balanced scenarios, the hourly power purchased or sold is multiplied by the 

current grid rate and the yearly sum balanced between the amount purchased from the grid and 

the wind sold. Thus, in these optimization scenarios, the size of the wind farm is what changes.

Scenarios c and d were developed to explore the implications of not purchasing grid electricity 

during summer peak hours when the demand on the electric grid is greatest. In certain regions 

this might have significant economic and emissions implications for grid operators where 

peaking plants are both less efficient and more polluting. The system is designed with an average 

output of hydrogen per day, which is met with wind and grid electricity combined. During 

summer peak hours, because grid electricity is not to be used, the system runs at partial load 

using available wind electricity only; therefore the some hydrogen output may be unmet in 

comparison to the design average. 
12 

4 Results 

The two different wind cost cases represented are case 1 using the Malcolm and Hansen study 

[3] and case 2 using the Wiser et al. study [4]. The four scenarios for each case show several 

ways in which the system might be configured and the resulting hydrogen cost from these 

configurations. 

For optimization of the wind farms, an upper limit of less than 1 GW was set. The modeling 

restriction was put in place to eliminate eight sites with very low capacity (<11%) at low wind 

speed (class 1) from consideration because they were very marginal for wind electricity 

production. Therefore, the aggregate results describe 128 sites. 

For the scenarios in which no summer peak electricity is bought, the unmet hydrogen is about 

600,000 kg/yr to 1,000,000 kg/yr. Because the summer period is 122 days long, from June 1 to 

Sept 30, this corresponds to an unmet daily demand in the summer only of approximately 5,000 

kg/day to 8,200 kg/day. 

If a minimum of 50,000 kg/day of hydrogen production is required, systems restricting the use of 

summer peak electricity could be modeled with a higher nominal production capacity, possibly 

in combination with hydrogen storage, such that a minimum of 50,000 kg/day of hydrogen is 

produced even during summer peak electricity demand days with lower production capacity 

utilization. We have not yet conducted such an analysis. 

4.1 Case 1—Low Wind Cost

The hydrogen costs for the four scenarios ranged from $2.83/kg to $7.83/kg. These costs assume 

current electrolyzer technology costs reduced by mass production (see section 3.1) and wind 

costs lower than would be expected today because of a recent trend of rising wind turbine costs. 

The costs of the wind electricity in this case ranged from $0.046/kWh to $0.138/kWh depending 

on wind site. The lower cost of this range is near, however, to the wind electricity cost assumed 

by the independent panel that analyzed the cost of central wind electrolysis [2]. This low-cost 

electricity was reached at a class 5 wind site with the highest capacity factor of any site, though 

not the highest annual average wind speed. It was for scenario d, which balanced the megawatt 

hours of wind bought and sold but did not purchase summer peak grid electricity. 

Figure 8 and Figure 9 show the cost of hydrogen relative to a site’s cost of wind electricity. For 

the cost-balanced scenarios, not purchasing summer peak electricity reduces the cost of 

hydrogen. The effect is more significant for the cost-balanced scenario, but also is seen in the 

power-balanced scenario. This is because the system operator no longer purchases the most 

expensive grid electricity, summer peak; however, the consequence is that some of the hydrogen 

demand may be unmet because the system is not running at full capacity during those summer 

peak hours when wind does not meet the electrolyzer energy needs. The system always uses 

available wind electricity for hydrogen up to the electrolyzer capacity. 
13 

Figure 8. Cost of hydrogen for case 1 (low-cost wind), cost-balanced scenarios a and c

The power-balanced scenarios shown in Figure 9 have a smaller effect on the cost of hydrogen. 

In both scenarios, the amount of electricity bought and electricity sold are still balanced, but the 

size of the wind farm and therefore its production is adjusted. There is still some unmet hydrogen 

demand for the case where summer peak electricity is not purchased.

Figure 9. Cost of hydrogen for case 1 (low-cost wind), power-balanced scenarios b and d

Although we expect the costs of hydrogen production in case 2 to be more accurate given the 

current costs for wind turbines, the results of this lower cost case are a good companion to the 

production costs presented by the independent panel for electrolysis [2]. The panel projected 

0

1

2

3

4

5

6

7

8

9

0.00 0.05 0.10 0.15

Cost of H2 ($/kg)

Cost of Wind Electricity ($/kWh)

a) Buy Summer Peak

c) No Summer Peak

0

1

2

3

4

5

6

7

8

9

0.00 0.05 0.10 0.15

Cost of H2 ($/kg)

Cost of Wind Electricity ($/kWh)

b) Buy Summer Peak

d) No Summer Peak
14 

central wind electrolysis production costs of $3.00/kg, but their projection (which focused on the 

state of technology for electrolyzer systems) used a rough assumption that wind-based electricity 

would always be available at a cost of $0.045/kWh. The cost optimization presented in this case 

shows that when slightly lower wind turbine costs are assumed, a wind electrolysis system using 

wind electricity produced in some class 4, 5, or 6 wind areas can produce hydrogen for a little 

less than $3/kg, as predicted by the independent panel. 

4.2 Case 2—Current Wind Cost

For case 2 using the higher, more current, wind costs from the Wiser et al. study [4], the range of 

hydrogen costs for all scenarios was $3.72/kg to $12.16/kg. This was a direct result of higher 

wind electricity costs, which ranged from $0.064/kWh to $0.222/kWh. It should be noted these 

wind costs do not include any wind PTC or other incentive. 

The lowest cost of hydrogen was found for a class 5 wind site with the highest capacity factor in 

scenario c, which balanced cost and did not buy summer peak electricity. 

Figure 10 and Figure 11 show the cost of hydrogen related to a site’s cost of wind electricity. 

Similar results are found as for case 1 but with slightly higher costs of hydrogen. In fact, the cost 

of hydrogen is fairly linear relative to the cost of the wind electricity, other parameters held 

static.

Figure 10. Cost of hydrogen for case 2 (current wind cost), cost-balanced scenarios a and c

0

2

4

6

8

10

12

14

0.000 0.050 0.100 0.150 0.200 0.250

Cost of H2 ($/kg)

Cost of Wind Electricity ($/kWh)

a) Buy Summer Peak

c) No Summer Peak
15 

Figure 11. Cost of hydrogen for case 2 (current wind cost), power-balanced scenarios b and d

As with case 1 for the cost-balanced scenarios (Figure 10), not purchasing summer peak 

electricity slightly reduces the cost of hydrogen. Unmet hydrogen for the scenarios where 

summer peak electricity is not bought falls in the same range, from 600,000 kg/yr to 1,000,000 

kg/yr. 

The higher wind costs do produce higher costs of hydrogen, but a quick look at the wind sites 

that produced hydrogen at costs less than $4/kg (in 2005$) are informative to get a better idea of 

where low-cost hydrogen can be produced. Nine sites collectively produced low-cost hydrogen 

in at least some of the scenarios. All nine sites produced hydrogen at less than $4/kg in scenario 

c, which was cost balanced without buying summer peak electricity. Eight of the sites did such in 

scenario d, power balanced, and not buying summer peak electricity. Scenarios a and b had five 

sites each. Of the nine sites, seven were wind class 6, one was wind class 5, and one was wind 

class 4. They all had wind farm capacity factors of 44% or better, an average wind speed of 9.1 

m/s at 100 m, and an average wind electricity cost of $0.067/kWh. 

4.3 Scenario Details—Current Wind Cost

Looking more closely at the ramifications of the different scenarios analyzed reveals some 

interesting trends and points to take away in designing green hydrogen wind electrolysis systems. 

Whether or not to purchase summer peak electricity has implications beyond adding to peak load 

during the time of annual highest demand. The scenarios have an effect on the size of the wind 

farm and the cost of hydrogen. Additionally there is a distinct effect on cost of hydrogen and 

quantity of hydrogen unmet based on whether or not the green hydrogen is made by balancing 

cost or amount of electricity. For this, current wind costs from the Wiser et al. study [4] are used; 

however, similar results are found for lower cost wind as well, but in smaller ranges.

0

2

4

6

8

10

12

14

0.000 0.050 0.100 0.150 0.200 0.250

Cost of H2 ($/kg)

Cost of Wind Electricity ($/kWh)

b) Buy Summer Peak

d) No Summer Peak
16 

Figure 12. Wind farm size required to produce 50,000 kg/day H2 and cost of electricity at each site

for each scenario

The size of the optimized wind farms varies depending on the scenario. As stated before, all 

scenarios were set up to meet a 50,000 kg/day hydrogen rate. The electrolyzers were sized to 

meet that with their expected maintenance downtime taken into account. The wind farms were 

then sized based upon the scenario criteria in discrete multiples of 3-MW turbines. Figure 12

shows trends for the different scenarios. The cost of electricity is a function of the average wind 

speed and capacity factor of each site which are roughly conveyed by a wind class. Each 

particular wind site is shown in proxy as a cost of wind electricity which incorporates the 

average wind speed and unique wind profile. The four vertical data points show the different 

wind farm size optimizations for that unique site based upon the scenario constraints. There is a 

strong linear trend based on the cost of the wind electricity produced at a given site. In general, 

higher cost wind electricity means lower wind class sites and lower capacity factors, i.e., worse 

sites for wind production in general. Better wind sites produce lower cost electricity and require 

smaller sizes to meet the hydrogen demand. This is unsurprising. 

Figure 12 shows other trends in which cost of wind electricity is used as a proxy for an 

individual wind site. Each scenario is designed for a peak hydrogen demand of 50,000 kg 

H2/day. The size of the wind farm required meet constraints, however, is linear and differentiated 

by scenario. For instance, scenario c, balancing cost and not buying summer peak grid electricity, 

required the smallest wind farms at all sites and scenario d, balancing power and not buying 

summer peak grid electricity, also required smaller wind farms than both scenarios that buy 

summer peak electricity. The range in wind farm sizes designed to meet the different scenarios at 

a wind site that produced electricity for $0.10/kWh was about 333 MW to 369 MW; a site with 

0

100

200

300

400

500

600

700

800

900

0.050 0.100 0.150 0.200 0.250

Wind Farm Size (MW)

Cost of Wind Electricity ($/kWh)

Scenario a

Scenario b

Scenario c

Scenario d

WindClass 6 WindClass 1
17 

$0.15/kWh needed wind farms between 507 MW and 561 MW. The range of wind farm sizes 

across scenarios narrows as the cost of wind electricity decreases because of being at better 

production wind sites. As noted previously, the sites range from wind class 1 to class 6. Many of 

the lower class sites with high cost of wind electricity would probably not be developed unless 

wind turbine costs dropped significantly more than projected. We include them to show a full 

range of analysis results.

Scenarios c and d, which did not purchase summer peak grid electricity, also had lower hydrogen 

costs than the corresponding scenarios a and b, which did buy summer peak grid electricity. The 

vertical axis in Figure 13 shows the cost difference found by subtracting the scenario a cost of 

hydrogen at a site minus the site’s corresponding cost in scenario c; also shown is the cost of 

hydrogen scenario b minus scenario d. The resulting cost difference is always greater than zero, 

signifying that the cost of hydrogen was lower for scenarios that did not buy summer peak 

electricity compared to the optimization for scenarios that did. There was a hydrogen cost 

penalty for buying summer peak electricity, though it is offset by an unmet hydrogen demand in 

the scenarios that did not purchase summer peak grid electricity. This analysis, however, 

suggests that this unmet demand could be met with small adjustments yielding very small 

production cost effects. Oversizing the electrolyzer results in hydrogen production cost 

differences of only less than $0.06/kg when the wind farms are optimized for that; however, that 

does not account for potential storage costs, which could be about $1.00/kg for bulk storage of 

5,000 kg in compressed tanks [12]. This solution would approximately cover the 50,000 kg/day 

summer demand, but would still result in higher average production in the winter. This kind of 

seasonal variation might not be desired, but further investigation is left as a future exercise.

Figure 13. Difference in cost of H2 between similar scenarios that do or do not buy summer peak

The scenarios that purchase summer peak electricity all had higher hydrogen costs than the 

scenarios that did not purchase summer peak electricity. Understanding this can help researchers

design better, more cost-effective systems and scenarios in the future. Figure 13 shows the 

change in hydrogen cost between scenarios that bought summer peak electricity and those that 

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.000 0.050 0.100 0.150 0.200 0.250

H2 Cost Difference ($/kg)

Cost of Wind Electricity ($/kWh)

Cost Balance (a–c)

Power Balance (b–d)
18 

did not. The trends are separated between the cost- and power-balanced scenarios, but scenarios 

a and b had higher hydrogen costs demonstrated in the figure by all cost differences being 

positive between their corresponding scenarios which did not buy summer peak electricity. The 

results shown are based on the cost of the wind electricity that serves as a proxy for individual 

wind sites; lower wind costs are found at more suitable wind resource locations. 

Figure 13 shows that the cost difference increases greatly for the cost-balanced scenarios as wind 

electricity cost increases, and the power-balanced scenarios remain more level and wind cost 

insensitive. The range of the hydrogen cost difference for the cost-balanced scenarios is $0.08/kg 

to $0.55/kg, and for the power-balanced scenarios the range is much smaller, between $0.05/kg 

and $0.11/kg. For the cost-balanced scenarios, Figure 12 shows that the size of the wind farms is 

significantly smaller for scenario c in which summer peak grid electricity is not bought than 

scenario a in which it is bought. Therefore, consider that both scenarios include the same 

electrolyzer demand, so the smaller sized wind farm is buying more grid electricity, which has an 

average annual cost rate of $0.053/kWh, and selling less wind electricity. As the wind electricity 

cost increases, the system is using less wind and more of the cheaper grid electricity in the cost 

balanced scenarios. Therefore, the cost of hydrogen produced in the no summer peak electricity 

scenario is less; less of the expensive wind electricity is bought, more cheap grid electricity is 

needed because of smaller wind farm size, and less of the wind electricity is sold resulting in 

increasingly lower hydrogen costs as wind electricity cost increases. The power balanced 

scenarios also show that the scenario d in which summer peak grid electricity is not purchased

results in lower costs of hydrogen. In these cases, however, it is less dependent on the cost of the 

wind electricity because only the power not purchased must be normalized. This still results in 

slightly smaller wind farm sizes, seen in Figure 12, because less grid electricity is purchased 

requiring less wind electricity to be sold on a power basis. Not purchasing the more expensive 

summer peak electricity results in a lower cost of hydrogen that is less dependent of the costs of 

electricity at different sites. 

Figure 14. Difference in unmet hydrogen among scenarios

0

5,000

10,000

15,000

20,000

25,000

0.000 0.050 0.100 0.150 0.200 0.250

Difference Unmet H2 (kg/yr)

Cost of Wind Electricity ($/kWh)

Difference of unmet 

hydrogen (scenarios c–d)
19 

Another detail to examine is the effect on unmet hydrogen demand in the scenarios in which 

summer peak electricity is not purchased (scenarios c and d). In Figure 14, in which unmet 

hydrogen per year in scenario d is subtracted from that in scenario c, scenario c results in slightly 

more unmet hydrogen than scenario d in all cases examined. This can be partly explained as a 

result of the sizes of wind farms shown in Figure 12 in which scenario c has slightly smaller 

wind farms than scenario d. This difference results in less hydrogen being produced during 

summer peak time when grid electricity is not used to supplement the wind. 

Figure 15 shows the totals of unmet hydrogen in scenarios c and d. The wide range is not easily 

described by comparing to the wind electricity cost, capacity factor, or wind class. The range is 

probably caused by site specifics that are related to the wind fluctuations and variability of the 

wind profile compared to the average wind speed. In the scenarios described in this analysis, 

however, the unmet hydrogen shortage is all accounted for in the summer months rather than 

spanning the whole year. 

Figure 15. Unmet hydrogen in scenarios that do not buy summer peak electricity

4.4 Detail Case Site—Current Wind Cost

One particular site is selected for a more detailed analysis. The site has a class 5 wind with a 

capacity factor of 0.47. The average wind speed at 100 m is 8.52 m/s. The wind electricity cost is 

$0.064/kWh configured as for case 2, more current wind turbine costs. Figure 16, the wind 

profile of the site, shows a relatively steady wind production through the entire year. 

Table 7 gives some of the results of the optimization. The grid utilization relates the maximum 

megawatt imported from grid to the maximum megawatt wind excess exported to grid; i.e., grid 

utilization = 100 × max grid MW import/max wind MW export. A grid utilization of less than 

100% means that the maximum power of wind electricity exported to the grid was greater than 

the maximum power needed from the grid in any given hour. The maximum grid electricity 

needed will be the maximum power of the electrolyzer, 106 MW, for hours in which there is no 

wind. 

500,000

600,000

700,000

800,000

900,000

1,000,000

1,100,000

0.000 0.100 0.200 0.300

Unmet H2 (kg/yr)

Cost of Wind Electricity ($/kWh)

Cost-balanced 

(scenario c)

Power-balanced 

(scenario d)
20 

Figure 16. Example wind profile

Table 7. Detailed Example

Scenario

Wind 

Farm Size 

(MW)

Number of 

3-MW 

Turbines

Grid 

Utilization 

(%)

Unmet H2

Production 

(kg/yr)

Cost of 

Hydrogen 

($/kg)

(a) Cost-Balanced—Buy 

Summer Peak 210 70 94 0 3.80

(b) Power-Balanced—Buy

Summer Peak 219 73 102 0 3.82

(c) Cost-Balanced— No 

Summer Peak 195 65 100 622,000 3.72

(d) Power-Balanced—No 

Summer Peak 213 71 120 602,000 3.77

To see the difference between purchasing and not purchasing summer peak electricity, compare 

Figure 17 and Figure 18, which show the daily averaged power going to the electrolyzer and the 

grid for scenarios b and d (power balanced). For scenario b, Figure 17 shows a steady line at 106 

MW. Figure 18, however, shows the averaged daily decrease in the summer months where there 

is some unmet hydrogen as compared to the expected average. In both figures, the area of excess 

wind should approximately equal the area in red, which is the power bought from the grid. 

0

2

4

6

8

10

12

14

16

18

20

Average Daily Wind Speed (m/s)
21 

Figure 17. Example scenario b

Figure 18. Example scenario d

4.5 Sensitivity Case Site—Current Wind Costs

Finally, the sensitivity to several variables is shown here. The costs and performance of both the 

wind turbines and the electrolyzers have been predicted, but it is important to show how different 

parts of the wind electrolysis system affect the final cost of hydrogen. How the technologies 

develop both in cost and performance has an effect on the system. 

0

50

100

150

200

250

Daily Averaged (MWh/day)

Wind to Electrolyzer Grid to Electrolyzer Wind Sold to Grid

0

50

100

150

200

250

Daily Averaged (MWh/day)

Wind to Electrolyzer Grid to Electrolyzer Wind Sold to Grid
22 

A sensitivity analysis was performed on five variables—wind turbine cost, wind farm 

availability, electrolyzer cost, electrolyzer energy usage, and electrolyzer capacity factor. The 

wind farm and electrolyzer sizes remained the same as the baseline optimization, then the 

variables were changed to find the new cost of hydrogen. This was done to show how an over, 

under, or incorrect performance prediction would affect the overall economics of the system. 

Figure 19 shows only one scenario; the other scenarios exhibited similar ranges around their 

respective baseline cost of hydrogen. 

Table 8 lists the adjusted variables in the sensitivity analysis. The high and low values of the 

different variables were chosen as being representative, but are not intended to show definitive 

ranges. The wind turbine and electrolyzer capital costs were varied by –/+ 20%, the wind farm 

availability and electrolyzer capacity factor were varied by 2%, and finally the electrolyzer 

energy use (related to its efficiency) was given a high and low value corresponding to the 

independent review panel’s values for a central production facility [2]. The wind turbine costs, 

electrolyzer efficiency, and cost have the largest effect on the overall cost of hydrogen. By 

comparison, the capacity factors of the wind farm and electrolyzers, which gauge the 

maintenance downtime required of the subsystems, have a much smaller overall effect. The wind 

turbine cost uncertainty can have a large effect on the economic viability of a wind electrolysis 

production facility. 

Figure 19. Sensitivity of cost of hydrogen for scenario d (power balanced, no summer peak)

3.00 3.20 3.40 3.60 3.80 4.00 4.20 4.40 4.60

Wind Farm Availability (90%, 88%, 86%)

Electrolyzer Capacity Factor (99.5%, 98%, 96%)

Electrolyzer Capital Cost (-/+ 20%)

Electrolyzer Energy Use (47.5, 50, 60 kWh/kg)

Wind Turbine Capital Cost (-/+ 20%)

Cost of Hydrogen ($/kg)
23 

Table 8. Sensitivity Values for High and Low Hydrogen Costs (2005$)

Variable Name Base Case Value Low Value High Value

Wind Turbine Capital Cost 

($/kW)

1,964 1,571 2,356

Electrolyzer Energy Use 

(kWh/kg)

50 47.5 60

Electrolyzer Capital Cost ($/kW) 384 307 461

Wind Farm Availability (%) 88 90 86

Electrolyzer Capacity Factor (%) 98 99.5 96

5 Conclusion

This analysis builds on the technical accomplishments of the NREL Wind2H2 program by 

examining the systems required for large-scale production of hydrogen via water electrolysis. By 

investigating lower cost and cost-optimized electrolysis production systems that use renewable 

wind energy, this analysis increases our understanding of how to develop green, sustainable 

hydrogen production systems. The model developed can be configured for different economic 

and technical parameters, allowing individual production sites and overall wind electrolysis 

trends to be analyzed. 

This examination highlighted several economic and technical ramifications that should be 

considered. For instance, the scenarios in which peak summer grid electricity was not purchased 

generally resulted in lower costs of hydrogen, while not exacerbating peak demand during the 

summer. Those scenarios, however, also did not meet the average daily hydrogen production 

requirement during those peak summer days. These results must be considered when estimating 

hydrogen production if large demands for fuel cell electric vehicles or other renewable 

integration are to be met.

As expected, the cost of wind electricity is integral to the cost of the hydrogen from a wind 

electrolysis system, and higher wind costs yield higher hydrogen costs. The wind site capacity 

factor and the cost of the hydrogen, however, are highly correlated: higher wind capacity factors 

(that is, higher wind availability) correlate to lower hydrogen cost even at sites with lower 

average wind speeds. Class 4, 5, and 6 wind sites are capable of producing hydrogen for 

approximately $4/kg using current wind turbine costs. 
24 

6 Recommended Future Work

Several areas presented themselves as possibilities for future work, for example, examining 

model enhancements such as inclusion and effect of wind production tax credits or power 

purchase agreements. Also, alternatives to meeting a hydrogen production demand using 

oversized electrolyzers or some storage could warrant further work. Additional scenarios might 

include grid-independent or other coproduction models. GIS-related work might examine the 

effect of different regional electricity costs, or low and high variability of both electricity costs, 

or the balance points of different delivery and production cost based on distance from use. Future 

analysis could include wind site data over several years to show the effect of designing for a 

particular year or averaging over several years. 

Our next steps are to examine the ramifications of some of the results in designing a wind 

electrolysis site, to identify key criteria for locating plants, to consider how costs might be 

reduced, and to develop cost sensitivities that might affect system design. This includes 

continued model validation and refinement. New scenarios could be developed to consider other 

aspects of a system. Continued use of the framework developed and analysis of results will help 

identify areas that need further work. 
25 

7 References 

1. Levene, J.I., Economic Analysis of Hydrogen Production from Wind: Preprint. 

NREL/CP-560-38210. Golden, CO: NREL, 2005. 

2. Genovese, J., et al. Current (2009) State-of-the-Art Hydrogen Production Cost Estimate 

Using Water Electrolysis: Independent Review. NREL/BK-6A1-46676. Golden, CO: 

NREL, 2009. 

3. Malcolm, D.J.; Hansen, A.C. WindPACT Turbine Rotor Design Study, June 2000–June 

2002 (Revised). NREL/SR-500-32495. Golden, CO: NREL, 2006. 

4. Wiser, R.H., et al. 2008 Wind Technologies Report. LBNL-2261E. Berkeley, CA:LBNL, 

2009. 

5. Ramsden, T. Current (2008) Hydrogen Production from Central Grid Electrolysis v. 

2.0.1. U.S. Department of Energy, 2008. 

6. DOE [U.S. Department of Energy] Hydrogen Program. DOE H2A Analysis. July 15, 

2008. http://www.hydrogen.energy.gov/h2a_production.html. Accessed August 2, 2010. 

7. Steward, D.; Penev, M. DOE Fuel Cell Power Analysis. 2009. 

http://www.hydrogen.energy.gov/fc_power_analysis.html. Accessed August 2, 2010. 

8. DOE Hydrogen Program. DOE H2A Analysis. March 11, 2008. 

http://www.hydrogen.energy.gov/h2a_analysis.html. Accessed August 2, 2010. 

9. EIA (Energy Information Administration). Short-Term Energy Outlook. August 2008. 

http://www.eia.doe.gov/emeu/steo/pub/archives/aug08.pdf. Accessed December 15, 

2010. 

10. NREL. Wind Integration Datasets: Western Wind Dataset. 

http://www.nrel.gov/wind/integrationdatasets/western/methodology.html. Accessed July 

15, 2010. 

11. Steward, D.; Penev, M. FCPower Model, Version 1.1. 

http://www.hydrogen.energy.gov/fc_power_analysis.html. Accessed July 10, 2010. 

12. Ringer, M.; Sozinova, O. H2A Delivery Components Model, Version 2.0. 

http://www.hydrogen.energy.gov/h2a_delivery.html. Accessed December 15, 2010 
F1147-E(10/2008) 

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Wind Electrolysis: Hydrogen Cost Optimization

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This report describes a hydrogen production cost analysis of a collection of optimized central wind based electrolysis 

production facilities. the basic modeled wind electrolysis facility includes a number of low temperature electrolyzers 

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wind electrolysis; hydrogen cost optimization; wind based water electrolysis; wind based electricity

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