National Renewable Energy Laboratory

Innovation for Our Energy Future 

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

Office of Energy Efficiency & Renewable Energy

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

Economic Analysis of Hydrogen 

Production from Wind 

Preprint 

J. I. Levene 

To be presented at WindPower 2005 Conference 

Denver, Colorado 

May 15–18, 2005 

Conference Paper 

NREL/CP-560-38210

May 2005 
NOTICE

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Executive Summary

Wind energy can be harnessed to provide electricity at some of the lowest costs available

for new generation. Coupling wind turbines with hydrogen-generating electrolyzers has 

the potential to provide low-cost, environmentally friendly electricity and hydrogen. In

this way, hydrogen generation can be a pathway for using wind energy to contribute 

directly to reducing the Nation's reliance on imported fuels. 

But what is the cost of hydrogen from such a pathway, and what are the potential 

technical and economic barriers of this technology? The price of hydrogen production 

from wind was calculated using the Department of Energy’s (DOE) Hydrogen Analysis

model (H2A) – a discounted cash flow analysis tool that uses standard DOE analysis 

methodologies and parameters to provide consistent analysis results across technologies. 

The analysis was conducted to determine the cost of hydrogen produced from wind 

energy via electrolysis, and to identify which technical areas are key cost drivers in the 

near, mid, and long term. The study focused on large-scale wind farms of 300-500 MW

connected to a co-located electrolysis plant that produces 50,000 kg of hydrogen per day.

Different scenarios were studied, from standalone wind hydrogen systems that produce 

only hydrogen to grid connected systems which can co-produce electricity. Results from

this study will help researchers and analysts determine where efforts should be focused if

wind is to play a major role in the future hydrogen economy.

The results from this analysis show that the price of hydrogen from a 50,000 kg/day

wind-hydrogen system can range from $5.69 per kilogram of hydrogen in the near term 

to $2.12 per kilogram of hydrogen in the long term. Slightly higher prices are seen 

without the co-production of electricity. Sensitivity analyses indicate that research 

should focus on reducing the capital costs of the wind/hydrogen system, while analysis 

should focus on electricity pricing scenarios, and validate depreciation assumptions. 

1.0 Introduction

The purpose of this analysis is to determine the cost of using wind energy to produce 

hydrogen for use as a transportation fuel. This analysis assumes that a market exists for 

50,000 kg of hydrogen per day produced from wind at the wind site; only production 

costs to the front gate are included, no delivery or dispensing costs are included. Three 

different scenarios are examined: near term, which represents 2005 currently available 

technology; mid term, which represents technological improvements and price reductions 

in the next 5-10 years; and long term, which is representative of the best technology gains 

and price reductions surmised by industry at this point, and represents the next 10-25 

years. 

1 
For purposes of clarity a few conceptual explanations are needed. First, hydrogen can be

produced from wind power by a process called electrolysis, which splits the water

molecule into hydrogen gas and oxygen gas. This is accomplished when electricity is

passed through two electrodes in water. The water molecule bonds are broken and 

oxygen gas is produced at the anode and hydrogen gas is produced at the cathode via the 

following reaction: H2O → 1⁄2 O2 + H2. In an ideal system, with no losses, the 

thermodynamic amount of energy needed to produce 1 kg of hydrogen from liquid water 

is approximately 39 kWh. Note that the amount of energy needed in actual electrolysis 

systems is larger than this due to system losses and peripheral equipment demands, such 

as pumps and dryers. 

In the previous explanation, the amount of energy needed to produce one kilogram of 

hydrogen was presented for a reason. Typically, when discussing hydrogen for 

transportation fueling needs, a kilogram of hydrogen is the unit used. This is because a 

kilogram of hydrogen is roughly equivalent in energy to a gallon of gasoline. A gallon of 

gasoline has roughly 108,000 – 123,500 British Thermal Units (BTU) per gallon, while 

hydrogen falls between those two values at 116,000 BTU per kilogram. Often, a 

kilogram of hydrogen is referred to as a gallon of gasoline equivalent or (GGE) when 

comparing hydrogen to gasoline. Therefore, if a gasoline engine and a hydrogen engine 

had the same miles per GGE efficiency, a kilogram of hydrogen and a gallon of gasoline

would result in the same number of miles traveled when used in said engine. The caveat

to this rule is that if you compare a traditional internal combustion gasoline engine to a

hydrogen fuel cell engine, and fuel cells are twice as efficient, than only half the amount 

of hydrogen would be needed to travel the same distance. In other words, if the fuel cell 

were twice as efficient, twice the mileage with a GGE of hydrogen would result 

compared to a gallon of gasoline in a traditional internal combustion engine. 

2.0 H2A Model 

The DOE Hydrogen Fuel Cell and Infrastructure Technologies (HFC&IT) program 

developed the H2A model used for this analysis. The H2A model was developed to 

provide the levelized selling price of hydrogen required to attain a specified internal rate

of return using a discounted cash flow rate of return analysis; or in other words, to 

determine a minimum hydrogen selling price. The reason for the H2A model’s 

development was to provide a framework where hydrogen analysis could be performed 

on a consistent and transparent basis. When comparing hydrogen technologies, analysts 

found that too often differences in analyses were the result of differing assumptions, such 

as internal rate of return (IRR) or feedstock costs, and not actual system differences. 

Models that examined the same hydrogen production system, such as wind electrolysis, 

might yield completely different results due to the assumptions used. The goal of the 

H2A model is to provide a common framework to improve the understanding of the 

differences among analyses. 

2 
To date two H2A modeling frameworks have been developed: a hydrogen production 

cash flow model and hydrogen delivery model. For this analysis, the hydrogen central 

production model was used, which is intended for hydrogen production facilities that 

produce at least 50,000kg/day of hydrogen. When using this model, hydrogen purity

must be suitable for Proton Exchange Membrane (PEM) fuel cells, and minimal storage 

is provided for operational support purposes only. 

The H2A effort was unique as many different national labs, universities, and agencies

contributed to its development. In addition, industrial collaborators were used to validate 

the model’s structure and assumptions. These key industrial collaborators (KIC) were

also used to validate results produced once analyses were completed. 

H2A Analysis Process 

A chevron showing the basic flow of the H2A model is presented in Figure 1. If a model 

were being built using H2A, the analysis would start at the left side of the diagram and 

move towards the right. Beginning on the far left side, the model provides standard 

feedstock and utility prices along with physical property data. The analyst then must 

provide some basic information about the hydrogen production system in the description 

and the title. Then, the analyst is responsible for providing data about the cost and 

technical analysis. The model is not a process simulation tool, so the analyst must gather

this information before entering it into the model. The cost analysis includes financial 

inputs, cost inputs, and replacement costs of the system. Financial inputs include 

parameters such as tax rate, depreciation type and period, internal rate of return, and 

construction data. Cost inputs include capital, operating, utility, and byproduct costs. 

The technical analysis includes the performance assumptions, process flowsheet, and 

stream summary of the system. The performance assumptions include the efficiencies of 

the different aspects of the system, along with purity data. The stream summary includes 

a mass and energy balance of the system, provided to the same level of detail as shown in 

the process flowsheet. Once the cost and technical analysis sections are completed, the 

model can produce information such as minimum selling price, and the data shown in the 

results chevron: cash flow, cost contribution, and sensitivity analyses. Examples of the 

types of results that can be obtained from H2A can be seen in the results section of this 

paper. 

3 
Financial

Inputs

Cost

Inputs

Replacement

Costs

Performance

Assumptions

Process

Flowsheet

Stream 

Summary

Title

Description

Feedstock

and Utility

Prices

Physical

Property

Data

Standard Price and

Property Data

Information

Cost Analysis

Technical Analysis

Cash

Flow

Cost

Contribution

Sensitivity

Analyses

Results

Figure 1: H2A Chevron 

3.0 Systems Analyzed

The purpose of the H2A wind electrolysis study was to analyze the technical and 

economic aspects of hydrogen production from wind. Two scenarios were run. The first, 

seen in Figure 2 is a standalone wind hydrogen system not connected to the grid, so no 

byproduct electricity was sold. This scenario may make sense in a good wind location 

where there are grid constraints, or where there is no grid available. 

Electricity

Hydrogen

From Norsk Hydro Electrolysers 

(www.electrolysers.com)

Figure 2: Standalone Wind/Hydrogen Plant 

The second system, seen in Figure 3, is grid connected, but only excess electricity is sold 

as a byproduct of the system; the system does not purchase power from the grid. In both 

cases, hydrogen is only produced with renewable power. 

 

4 
Electricity to the Grid

From Norsk Hydro Electrolysers 

(www.electrolysers.com)

Electricity

Hydrogen

Figure 3: Grid Connected Wind/Hydrogen Plant 

4.0 System Assumptions 

As stated before, one of the main goals of the H2A development was to provide a 

modeling framework where consistent assumptions would be used. A sampling of the 

financial assumptions used in this model is seen in Table 1. 

Table 1: Financial Assumptions

After-Tax Real IRR (%) 10%

Depreciation Type (MACRS, Straight Line) MACRS

Depreciation Schedule Length (No. of Years) 15

Analysis Period (years) 40

Plant Life (years) 40

Effective Tax Rate (%) 38.9%

% Equity Financing 100%

Length of Construction Period (years) 2

Capital costs and capacity factors are critical assumptions for this analysis. Wind farm

capital costs and capacity factors were modeled as following: near term, $873/kW capital 

cost and 0.4 capacity factor; mid term $754/kW capital cost and 0.5 capacity factor; long

term, $706/kW capital cost and 0.54 capacity factor. Near term electrolyzer costs came 

from a quote provided by electrolyzer manufacturer Norsk Hydro, and mid and long term 

costs were estimated using input from the H2A and H2A KIC teams. The values of 

$800/kW (near term), $480/kW (mid term), and $360/kW (long term) were used for 

electrolyzer installed capital costs. The replacement costs of both the electrolyzer and the 

wind turbines were included. The electrolyzer cell stack was refurbished every 10 years 

5 
at a cost of 30% of the initial electrolyzer investment. The turbine rotors were replaced at

20 years at a cost of 20% of the initial turbine investment. 

In addition, several system assumptions were made. The system was assumed to be sited 

at a class-6 wind location. The wind farm is co-located with an electrolysis plant that 

produces 50,000 kg of hydrogen per day. The maximum size for wind farms was 

assumed to be approximately 300 MW in 2005 and 2015, and 500 MW in 2030. From 

the specifications provided by Norsk Hydro on their electrolyzer, it was assumed that the 

hydrogen was produced from the hydrogen generation unit without external compression 

at a pressure of 440 psig and 99.8% pure hydrogen. In the grid-connected systems, any

electricity produced as a by-product would be sold at a price of $0.03/kWh. Finally, for 

the base case, the Production Tax Credit (PTC) was not used except for in the case where 

electricity was sold to the grid in the near term, as it is known that the scenario does 

currently exist. However, the effect of the PTC for all electricity produced was run for all

cases, and can be seen in the sensitivity analysis section. 

Next, assumptions specific to each scenario (stand-alone and grid connected), and each 

timeframe (near, mid and long term) were made. The system assumptions specific to the

standalone scenario without electricity co-production for all three timeframes can be seen 

in Table 2. 

Table 2: H2A Assumptions - Without Electricity Co Production 

Scenario Without Electricity Co Production

Time Period Near 

Term

Mid Term Long 

Term

Number of Electrolyzers 119 97 89 

$/kW for electrolyzer (installed) 800 480 360 

Electrolyzer Energy Requirement (kWh/kg) 53.4 47.9 44.7 

Electrolyzer Efficiency (HHV) 64% 71% 76% 

Electrolyzer Capacity Factor 41% 50% 54%

Number of Turbines (1.5 MW Current, 3 MW Near and 

Long Term) 

185 68 58

Total kW capacity 277,500 204,000 174,000 

Wind Farm Capacity Factor 41% 50% 54% 

Total annual GWh Produced 997 886 829 

Electrolyzer kW 113,340 100,187 94,188 

Co Product kW 580 981 561 

$/kW for turbine (installed) 873 754 706 

The system assumptions specific to the grid-connected scenario with electricity coproduction for all three timeframes can be seen in Table 3. 

6 
Table 3: H2A Assumptions - With Electricity Co Production

Scenario With Electricity Co Production

Time Period Near 

Term

Mid Term Long 

Term

Number of Electrolyzers 110 82 63 

$/kW for electrolyzer (installed) 800 480 360 

Electrolyzer Energy Requirement (kWh/kg) 53.4 47.9 44.7 

Electrolyzer Efficiency (HHV) 64% 71% 76% 

Electrolyzer Capacity Factor 44% 58% 77%

Number of Turbines (1.5 MW Current, 3 MW Near and 

Long Term) 

202 92 141

Total kW capacity 303,000 276,000 423,000 

Wind Farm Capacity Factor 40% 50% 54% 

Total annual GWh Produced 1,089 1,199 2,017 

Electrolyzer kW 111,400 99,876 94,139 

Co Product kW 12,988 36,998 136,197 

$/kW for turbine (installed) 873 754 706 

5.0 System Optimization

In the previous tables, note that for all timeframes the turbine and electrolyzer capital 

costs decrease over time. Note also, that the wind and electrolyzer capacity factors 

increase over time. However, in the standalone systems, the wind farm capacity factor

and electrolyzer capacity factor are the same, while in the grid connected system the 

electrolyzer capacity factor is higher than the wind farm capacity factor. This is due to a 

system optimization that was run for both scenarios and all timeframes. 

For all systems, the ratio of electricity produced from the turbine and electricity sent to

the electrolyzer was varied, and the resultant hydrogen price of the system was 

calculated. The minimum ratio for all systems was one, meaning that all electricity

produced by the turbine was sent to the electrolyzer for hydrogen production; the wind 

farm size exactly matched the hydrogen plant size, so a 100 MW wind farm would have 

100 MW of available electrolyzer plant. As the ratio increased from one, the wind farm 

size increased, and the electrolyzer plant decreased so that approximately 50,000 

kilograms per day of hydrogen was produced. When the new plant size was determined, 

the resulting hydrogen price was calculated. This process was repeated, and the results 

were graphed. An example of the graph resulting from the mid term co-production case 

can be seen in Figure 4. In the standalone plant, the increase in wind farm size and 

decrease in hydrogen plant size meant that during peak periods, electricity was thrown 

7 
away, and in the co-production scenario, these excess electrons were sold to the grid at a 

price of $0.03/kWh. 

The optimization found that for the standalone wind/hydrogen plants the hydrogen plant 

and the wind farm are most economical for hydrogen production when the hydrogen 

plant is sized the same as the wind farm, so both operate at the same capacity factor. 

However, the scenario was different for grid-connected plants. In this scenario, a 

minimum was found where the wind farm was oversized to a certain amount, and thus the 

hydrogen plant could be downsized, and as a result, operate at a higher capacity factor. 

An example of this optimization for the mid term co-production plant can be seen in 

Figure 4. 

Figure 4: Mid Term Plant with Co-Product Optimization 

Figure 4 shows that there is a point where the mid term plant with electricity co-product 

is optimized for the lowest price for hydrogen production. Once the system is 

constrained not to allow fractional wind turbines and fractional electrolyzers, the system

is optimized when 324 GWh/year sold as electricity and 875 GWh/year used for 

hydrogen production, for a total electricity production of 1199 GWh/year, which yields a 

ratio of 1199/875 or 1.4. All three of the timeframes for the co-production scenario 

yielded curves with minimum selling prices of hydrogen when the wind farm was 

oversized, and the results of those optimizations yielded the number of electrolyzers and 

turbines for the co-production scenarios. 

The optimized systems found are a result of the assumptions and constraints of the 

system. For example, if the hydrogen system were allowed to fall below 

50,000kg/hydrogen per day, a lower hydrogen cost could be achieved. As a result, the 

system sizes presented are optimized according to the constraints of this study and will 

not be indicative of other systems where other assumptions are used. 

8 
6.0 Results 

The results from this analysis show that the price of hydrogen from a 50,000 kg/day

wind-hydrogen system can range from $5.69 per kilogram of hydrogen in the near term 

to $2.12 per kilogram of hydrogen in the long term. Slightly higher prices are seen 

without the co-production of electricity. Figure 5 displays the price of hydrogen 

produced from all three time frames in both scenarios. 

Figure 5 - Graph of Hydrogen Wind Generation Cost Over Time

The overall cost reductions from time period to time period result from the decrease in 

capital costs and increased efficiency of the electrolyzer and wind turbines. The ability to 

use electricity as a co-product decreases the cost of hydrogen from $5.69 to $5.55 in the 

near term, from $3.19 to $3.07 in the mid term, and from $2.37 to $2.21 in the long term. 

The DOE HFC&IT program goal for wind produced hydrogen in 2015 is $2.75/kg. This 

timeframe falls towards the end of the mid term timeframe and towards the beginning of

the long term timeframe. In order to better understand why the cost target is not met in 

the mid term and is met in the long term, the cost contributions for each timeframe need

to be analyzed, and sensitivity analyses are required. 

Cost Contribution 

The H2A analysis model provides a breakdown of cost contributors to the price of 

hydrogen. The price is broken down into capital cost, decommissioning, fixed operation 

and maintenance (O&M), feedstock, other raw materials, byproduct, and other variable 

9 
costs. The cost contributors for this process can be seen in Figure 6. The most

significant contributors for all scenarios and timeframes are the capital costs of the wind 

farm and the electrolysis unit, followed by the fixed O&M costs of the system, which 

include costs such as labor, property taxes, and materials for maintenance and repairs. 

All cost contributors other than capital cost, fixed O&M, and by-product credit for this 

system are small enough to be insignificant. 

When comparing the co-product scenario timeframes, note that the capital costs for the 

co-product scenario fluctuate as the wind farm size in the mid term is actually smaller 

than the short term. However in the long term, the wind farm is significantly larger, and 

thus the capital cost increases significantly. The higher capital costs in the long term are

offset because of the positive cost contribution from the electricity co-product, which can

be seen below the $0/kg x-axis. This co-product credit needs to be subtracted from the 

positive cost contributors of the system to yield the final hydrogen selling price. 

When comparing the standalone systems to the co-product scenarios, note that in all three 

timeframes the co-product cases have a higher cost (above the $0/kg x-axis) than their 

corresponding standalone systems in the same timeframe, but those additional costs are 

offset by the by-product credit. Even though the co-product systems have a larger overall 

cost, their ability to sell byproduct electricity makes the final hydrogen selling price

lower. 

10 
Figure 6 - Graph of Hydrogen Cost Contribution Over Time

Sensitivity Analyses 

Once the base case hydrogen price is determined for each scenario in each time frame, a 

sensitivity analysis is run on each case to determine to which parameters the price of

hydrogen is most sensitive. For this analysis, six parameters were analyzed for the

standalone case, and seven were analyzed for the co-production cases. The parameters 

were varied one at a time, while all other parameters were held constant, so the effect of

each parameter could be determined independently. A list of the parameters varied is in

Table 4. 

Table 4 – Sensitivity Parameters 

Scenario 1 = Standalone system

Scenario 2 = System with electricity co-product 

Parameter varied 1 2 Sensitivity Range

MACRS depreciation period X X Renewable energy systems, such as wind farms 

are allowed a 5-year MACRS depreciation 

period. However, this may not be applicable to 

the hydrogen system. Standard MACRS 

depreciation period is 20 years, so the 

parameter was varied from 5-20 years. 

11 
Wind farm capital cost X X Capital costs were varied from +20% of the 

base case to –20% of the base case. 

Electrolyzer capital cost X X Electrolyzer capital costs were varied from

600-730/kW in the near term, 300-600/kW in 

the mid term, and 250-500/kW in the long

term. 

Electrolyzer energy

requirement 

X X Electrolyzer energy requirements varied from

56.7-52.3 kWh/kg in the near term, 53.1-45.9 

kWh/kg in the mid term, and 53.1-43 kWh/kg

in the long term. 

By-product electricity value X The value of the byproduct electricity was only

used in cases where electricity could be sold to

the grid, and was varied from $0.02/kWh - 

$0.06/kWh 

Production Tax Credit X X In all cases except the near term co-product 

case, the PTC was not applied to any energy

produced. For the near term co-product case 

the PTC was only applied to the electricity sold

to the grid in the base case, as it was unknown 

if electricity used to make hydrogen was 

eligible for the PTC. A sensitivity analysis 

was run for all cases from no electricity

produced being allowed the PTC to all 

electricity produced, even that used to make 

hydrogen, being allowed the PTC. 

Oxygen by-product X X This parameter was varied from 0% of the 

oxygen produced to 100% of the oxygen 

produced being sold at $0.02/kg. 

Once each of the above parameters were varied for each case, and the resultant hydrogen 

price found, the results were ordered from the parameter that had the highest effect on the 

hydrogen price when varied, to the parameter that had the lowest effect. These 

parameters were then graphed on a tornado plot, and an example of the two mid term 

plots can be seen in Figures 7 and 8 below. 

12 
Figure 7 - Mid Term Central Wind Tornado Plot 

Figure 7 shows that even with no electricity co-product, the ability to take the PTC for 

electricity produced to make hydrogen would allow the mid term process to make 

hydrogen for below the DOE cost target of $2.75. This is not a parameter research can 

effect, but it is worth noting as it is the only parameter when varied alone can make the 

standalone technology in this timeframe meet the $2.75 cost targets. The next two most 

significant parameters, electrolyzer cost and wind farm capital costs are areas where 

research can help reduce costs. For example, work is being done at NREL currently to 

optimize a wind/hydrogen system to help combine components common to both the wind 

turbine and the electrolyzer, thus reducing the cost. The fourth most important 

parameter, Modified Accelerated Cost Recovery System (MACRS) depreciation is a 

financial parameter that again, cannot be helped with research. However, like the PTC, it 

is worth noting so future analyses can be sure to verify the correct depreciation period to 

use for hydrogen systems. The fifth most important parameter, electrolyzer efficiency

could be improved with additional research. Note that the oxygen by-product credit is

minimal given that the additional capital costs of oxygen purification, compression, and 

storage were not included when the credit was taken. 

13 
Figure 8 - Mid Term Central Wind with Electricity Co-Product Tornado Plot 

Figure 8 shows that even with electricity co-product, the top three most sensitive

parameters are the same as the system without co-product electricity. However, the PTC 

has a much larger effect on this system, as it produces more electricity than the 

standalone system. With the PTC, the mid term process easily achieves the DOE cost

target of $2.75. In this case, the fourth most important parameter is the byproduct 

electricity value, because this system produces 324 GWh/year of byproduct electricity. 

Future analyses need to better establish the worth of co-product electricity. The final

three parameters are of the same importance in this system as in the standalone system. 

This scenario differs from the standalone scenario in that four parameters, when varied 

independently, can reach the DOE cost target: PTC, wind farm capital cost, byproduct 

electricity value, and MACRS depreciation. The ability to produce co-product electricity

makes the electricity price parameters more important; makes the wind farm larger, 

which increases the wind farm capital cost; and makes the overall capital cost larger, 

which increases the importance of the depreciation period. 

The top three most sensitive parameters for each scenario and timeframe are shown in 

Table 5 below, so the variations over time and between scenarios can be understood. 

14 
Table 5 – Hydrogen Cost Sensitivity Ranking 

Hydrogen Cost Sensitivity Ranking

Technology 1 2 3 

Near Term no 

co-production 

Production Tax Credit 

(0-100% of kWh 

produced) 

MACRS depreciation 

length (20-5 years) 

Wind farm capital costs 

(+/- 20%) 

Near Term with

co-production 

Production Tax Credit 

(0-100% of kWh 

produced) 

Wind farm capital costs 

(+/- 20%) 

MACRS depreciation 

length (20-5 years) 

Mid Term no coproduction Production Tax Credit 

(0-100% of kWh 

produced) 

Electrolyzer capital Costs 

(300-600 $/kW) 

Wind farm capital costs 

(+/- 20%) 

Mid Term with 

co-production 

Production Tax Credit 

(0-100% of kWh 

produced) 

Wind farm capital costs 

(+/- 20%) 

Electrolyzer capital Costs 

(300-600 $/kW) 

Long Term no 

co-production 

Production Tax Credit 

(0-100% of kWh 

produced) 

Electrolyzer capital Costs 

(250-500 $/kW) 

Wind farm capital costs 

(+/- 20%) 

Long Term with 

co-production 

Byproduct Electricity

Value (2-6 cents/kWh)

Production Tax Credit 

(0-100% of kWh 

produced) 

Wind farm capital costs 

(+/- 20%) 

In all cases, the production tax credit and wind farm capital costs are in the top three most 

sensitive parameters. Electrolyzer capital costs are in the top three in half of the cases, 

and the MACRS depreciation length is in the top three for the near term cases. The 

depreciation effect is understandable as the individual component capital costs for these 

systems are higher in the near term. Electrolyzer efficiencies are not to be ignored, as the 

effect this parameter has on hydrogen price ranged from $0.44 - $0.49/kg, which by itself 

is not enough to make the hydrogen cost target, but when combined with other 

parameters may be significant. 

Based on the sensitivity analyses, wind/hydrogen research should focus on the following: 

1.) reduce wind farm capital cost; 2.) reduce electrolyzer capital cost; 3.) improve

electrolyzer efficiency. Other critical parameters were the production tax credit, the 

byproduct electricity value, and the MACRS depreciation period, which are policy and 

electricity related parameters, and are outside the scope of wind/hydrogen research and 

development, but which should be better understood via analysis. 

Future studies should determine the effect on hydrogen price if several of the above 

parameters were decreased simultaneously. It may be that the cost target could be 

reached with smaller changes to some or all of these parameters, if implemented 

simultaneously. 

15 
7.0 Conclusions

The results of this analysis demonstrate that wind has the potential to generate hydrogen 

via electrolysis for prices ranging from $5.69 per kilogram of hydrogen in the near term, 

and as low as $2.12 per kilogram in the next 10-25 years, if capital costs and process 

efficiency improvements are fully recognized as assumed. Furthermore, the mid term

scenario shows that this process can produce hydrogen for $3.19/kg in a standalone wind 

hydrogen plan and $3.07/kg in a plant that can co-produce electricity. These values are 

$0.44/kg and $0.32/kg respectively above the DOE cost target of $2.75/kg for hydrogen 

production from wind electrolysis by 2015. However, the sensitivity analyses show that 

including the production tax credit, lowering wind turbine costs, receiving an increased 

byproduct electricity value, or using an accelerated depreciation period can all help to

make the cost target achievable by 2015 independently. Similarly, if process 

improvements occur quicker than the timeline assumes, the long term scenarios may be

valid by 2015, in which case both the standalone and co-product cases can meet the DOE 

2015 cost target. 

Research efforts need to focus on reducing wind farm capital costs, reducing electrolyzer 

capital cost, and improving electrolyzer efficiency. Individual components need to be 

considered, along with optimizing the system as a whole by eliminating redundancies in 

the system. Analysis should be used to better understand the effects of the production tax

credit, the byproduct electricity value and valid depreciation periods for hydrogen 

systems. 

8.0 Bibliography

Eliassen, Bjorn E. Norsk Hydro Electrolyzers Electrolyzer Hydrogen Plant 485 Nm3

/h 

Hydrogen. Norsk Hydro Electrolyzers, AS, 8 Aug. 2002. 

H2A Model website, 

<http://www.eere.energy.gov/hydrogenandfuelcells/analysis/model.html>, 

1/31/2005. 

Ivy, J. S. (2004). “Summary of Electrolytic Hydrogen Production”. Golden, CO: 

National Renewable Energy Laboratory; 27 pp.; NREL Report No. MP-560-

36734 

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Economic Analysis of Hydrogen Production from Wind: Preprint 

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The purpose of this analysis is to determine the cost of using wind energy to produce hydrogen for use as a 

transportation fuel. This analysis assumes that a market exists for 50,000 kg of hydrogen per day produced from 

wind at the wind site; only production costs to the front gate are included, no delivery or dispensing costs are 

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which is representative of the best technology gains and price reductions surmised by industry at this point, and 

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Wind energy; hydrogen production; cost analysis 

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