WP6 Dodds Production

8/10/2019 WP6 Dodds Production

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UKSHEC Working Paper No. 6

2012

Paul E. Dodds and Will McDowall

UCL Energy Institute, University College London

Central House, 14 Upper Woburn Place

London WC1H 0NN, UK

[email protected]

A review of hydrogen production technologies for energysystem models


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Contents

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

2 Methodology for producing energy systems data .................................................................. 3

2.1 Calculating plant investment and O&M costs ........................................................................ 32.2 Converting costs for use in UK MARKAL ................................................................................. 4

2.3 Heat of combustion ................................................................................................................ 4

3 Hydrogen Production technologies ....................................................................................... 5

3.1 Natural gas .............................................................................................................................. 6

3.2 Coal ......................................................................................................................................... 9

3.2.1 IGCC ................................................................................................................................. 9

3.3 Biomass ................................................................................................................................. 10

3.4 Water .................................................................................................................................... 11

3.4.1 Energy storage using hydrogen-electrolysis systems ................................................... 11

3.4.2 Thermochemical cracking of water ............................................................................... 12

4 Technology data for energy system models ......................................................................... 12

4.1 Summary of technologies in current MARKAL models ......................................................... 13

4.2 Recommendations for the future ......................................................................................... 13

4.3 Uncertainties in technology costing ..................................................................................... 18

4.4 Learning curves ..................................................................................................................... 19

5 Conclusion .......................................................................................................................... 19

6 References ......................................................................................................................... 20

1 Introduction

UK greenhouse gas (GHG) emissions predominantly result from the combustion of fossil fuels to

provide energy services in all sectors of the economy. In the future, it will be necessary to either

capture the emissions or to utilise zero-carbon sources of energy.

Hydrogen has been identified as a potential zero-emission energy carrier for the future, primarily for

the transport sector but also for energy storage and CHP applications. Hydrogen gas does not existnaturally and must be produced from fossil fuels or water. It has been produced for industrial

applications for many decades and several production technologies are now available that use a

range of fuels.

The UKSHEC I project reviewed some of these technologies (Hawkins and Joffe 2005)and

implemented a comprehensive hydrogen energy system in the UK MARKAL model (Joffe et al. 2007;

Kannan et al. 2007). MARKAL is a partial-equilibrium E4 optimisation model (energy-environment-

economics-engineering) that is used to represent the entire UK energy system. The technology

characterisation is several years old and we have identified some shortcomings and inconsistencies

in the data. As part of the UKSHEC II energy systems research programme, hydrogen production is

being revisited to: (i) recommend consistent representations of hydrogen production technologies


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for the UK MARKAL and TIAM-UCL models (TIAM-UCL is a global E4 optimisation model that has

been recently developed); (ii) ensure that the assumptions underlying the hydrogen technologies are

also consistently applied to other competitor technologies; and, (iii) identify technologies for which

the deployment costs are likely to substantially reduce with large-scale deployment. The third

objective reflects the greater emphasis on innovation and technology learning in UKSHEC II.

Hughes (2008)provided an initial paper setting out some of the technological developments that

have occurred since UKSHEC I was completed. This paper builds on that qualitative work using a

comparison of the existing hydrogen production data in the UK and US9R MARKAL models and a

literature review. We recommend revised technology data for the UKSHEC II project and consider

the uncertainties in the data. The impacts of these uncertainties on model simulations will be

considered in a separate paper.

2

Methodology for producing energy systems data

Hydrogen production technologies were identified from current MARKAL models and from the

literature. For each technology, the E4 models require capital investment and operations and

maintenance (O&M) costs, efficiency data, and fuel inputs and outputs. Few sources provided all of

this data for each technology so we based our recommendations on a comparison of all available

data rather than adopting a single source. This approach required a greater understanding of the

factors underlying the costs and efficiencies of each technology which enabled us to consider data

uncertainties. One potential drawback is that the recommended data might no longer represent a

single plant design.

We encountered three difficulties in particular. Firstly, the investment and O&M costs must be

calculated for each technology using a consistent approach with other energy system technologies

so that an unbiased comparison can be performed. Secondly, it is necessary to convert the costs

into consistent monetary units. Thirdly, the energy efficiency must be calculated consistently across

the model for each fuel. The following sections expand on these difficulties.

2.1

Calculating plant investment and O&M costs

Direct plant investment costs refer to the actual cost of the installed equipment. All plant

construction projects also have substantial indirect costs as well. System costs include design, site

preparation, contingency costs and profits for the construction contractor (direct costs implicitly

include profits for equipment manufacturers). The cost of land, licensing and permits vary between

countries. Some plants have additional financial costs to cover financing for up-front fees.

Estimates of technology costs always include direct costs but some indirect costs are often omitted.Since indirect costs are often more than 50% of the direct costs, the inclusion or omission of indirect

costs can be one of the principle drivers of cost differences between studies. It is important that

comparable costs are included for all technologies in the energy system models, both for hydrogen

production and elsewhere, so that unbiased comparisons of technologies can be performed. There

are presently no clear guidelines about which indirect costs are included in the UK MARKAL or TIAM-

UCL models. In this study, we chose to include all indirect costs except for additional financial costs,

which are separately accounted for by the model investment discount rate equations.

O&M costs are also difficult to estimate because they include equipment outage costs, running

costs, licensing costs and labour. Some are fixed each year while other variable O&M costs depend

on the production rate. For hydrogen production technologies, the principle variable cost is the fuel


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and this is separately accounted for by the energy system models so we concentrated on fixed O&M

costs. Our approach calculated the annual O&M costs as a fraction of the capital investment costs.

2.2

Converting costs for use in UK MARKAL

The UK MARKAL model uses British pounds in the year 2000 while the TIAM-UCL model uses USdollars in the year 2005. Investment costs in the literature are specified in both dollars and euros,

for a range of years, so it is necessary to account for both currency conversion and inflation. The

choices are (i) to adjust for inflation in the original currency and then apply the year 2000 currency

conversion rate; or, (ii) to convert to /$ in the technology year then adjust for the UK inflationary

difference to the year 2000. Exchange rates are more volatile than inflation rates so the first option

produces a more consistent conversion factor (Figure 1).

In this paper, in common with Lemus et al. (2010)and Bartels et al. (2010), the first approach is

adopted. There is a 1.72 factor between the UK(2000) and US$(2005). However, there is no

correct methodology as such and it is necessary to consider the conversion rates as a potential

source of uncertainty when producing cost estimates of technologies.

Figure 1: $: conversion factors for two conversion methods

2.3

Heat of combustion

The energy that can be extracted from a fuel is often measured as the energy released as heat whenthe fuel undergoes complete combustion with oxygen. Table 1 shows this heat of combustion for

several common fuels including hydrogen.

The heat of combustion can be specified in terms of the higher or lower heating value (HHV or LHV).

The HHV represents the entire produced heat while the LHV excludes any energy that is used to

vaporise water during combustion. The difference between the two is higher for lower-carbon fuels

(Table 1). The extent to which energy is lost to water vaporisation depends on the technology; the

LHV is most appropriate where large amounts of water vapour are produced at a temperature below

150C or where condensation of the combustion products in impractical. Both HHV and LHV are

used in different sources in the literature so it is necessary to use a consistent approach. Since UK

MARKAL energy efficiencies are theoretically calculated on the basis of the HHV, HHV values are


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used throughout this report. However, the existing data in UK MARKAL has not always been

consistently calculated using HHV data; for example, the vehicle technology data uses the LHV

(which inflates the costs of hydrogen storage tanks, because it effectively reduces the assumed

usable energy in hydrogen). The high hydrogen HHV:LHV ratio (Table 1) accentuates the

discrepancies caused by using different approaches for different hydrogen technologies relative to

other fuels.

Table 1. Heat of combustion of several fuels (MJ/kg)

Higher Heating Value Lower Heating Value HHV:LHV ratio

Hydrogen 142 121 1.17

Methane 56 50 1.12

Gasoline 47 44 1.07

Coal (Anthracite) 27 27 1.00

Wood 15 15 1.00

For solid fuels with higher carbon content (e.g. coal and biomass), the HHV and LHV can vary

substantially depending on the exact fuel composition. For example, the efficiency of coal

gasification will be substantially influenced by the composition of the coal being used. Great care

must be taken to match the fuel type to the process efficiency; if necessary, the process technology

should be defined several times for different fuel compositions with different process efficiencies.

3 Hydrogen Production technologies

Hydrogen is currently produced for industrial applications by cracking carbonaceous fossil fuels.

Methane is the most common fuel but coal has also been used. Since the principle aim of a

hydrogen economy is to reduce carbon emissions, it would be necessary to deploy carbon capture

and storage (CCS) systems on these plants and this would only be economic for large-scale

production.

Recently, a number of methods have been developed to produce hydrogen from biomass. Biomass

gasification is the most advanced but has not been tested at the scale of a large plant. Most other

biomass methods are still at the laboratory stage of development.

Hydrogen is also produced by cracking water, a technology that does not require a carbonaceous

fuel. Electrolysis is the only method that has been demonstrated on an industrial scale. The

principle drawback of this method is the high cost of electricity relative to other fuels; it has been

proposed that high-temperature thermal cracking, using heat from nuclear reactors or photovoltaiccells, could improve the efficiency of the process and reduce the electricity use.

This section briefly reviews each of these technologies with the aim of identifying suitable data for

energy systems models. Schoots et al. (2008)analysed the actual construction costs of numerous

SMR, coal gasification and electrolysis plants and these data were used to estimate the actual built

plant costs. Estimates of current and future costs and energy efficiencies for all of the principle

technologies were extracted from the H2A (Steward et al. 2008)and TECHPOL (Krewitt and Schmid

2004)technology databases. Further data were extracted from studies in the literature (Gray and

Tomlinson 2002;NRC 2004;Kreutz et al. 2005; Iaquaniello et al. 2008;NRC 2008;Cormos 2010; DEA

2010;Khamis and Malshe 2010). Where possible, we compared these data with existing data from

the current UK and US9R MARKAL models.


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We found that only six hydrogen technologies have been sufficiently developed to produce realistic

cost and efficiency data; these are compared in Figures 2 and 3, respectively. Each of these

technologies is discussed in the following sections.

3.1

Natural gas

Natural gas reforming is currently the most efficient, economical and widely used process for

production of hydrogen and has been utilised globally for many decades in the oil refinery and

fertiliser industries. Steam reforming (SMR) is the standard method but membrane reforming has

also been demonstrated in small-scale plants (Iaquaniello et al. 2008;Shirasaki et al. 2009).

Compact, small-scale reformers, suitable for refuelling stations, have been proposed as one option

for a hydrogen economy (Ogden 2001). While this option would remove the requirement for

expensive delivery infrastructure in the early stages of a transition to hydrogen, the systems would

be too small for CCS to be used so substantial GHG emission savings would be not be achieved.

Both large-scale and small-scale SMR technologies are represented within UK MARKAL, each with

two technology vintages (Figure 2). The current UK MARKAL data has one apparent data input

mistake. Investment costs for future large-scale SMR are higher than those for current technologies,

in contrast to the data in the NRC (NRC 2004)report on which the costs are based. Estimates of

large SMR plant investment costs in the literature are substantially lower than for smaller plants

(Damen et al. 2006), although small-scale plant costs are expected to reduce substantially in the

future, perhaps through the adoption of membrane technology. SMR has the lowest capital costs of

the hydrogen production technologies at around 4 GJ-1y-1.

SMR efficiencies are currently in the range 60%80%, with larger plants being more efficient (Figure

3). Efficiencies are expected to rise only slightly in the future but the scale gap should close.

Membrane plants are likely to only slightly increase the operating efficiencies (Shirasaki et al. 2009).

Operating efficiencies will be reduced if plants employ CCS in future. The level of the reduction will

depend on the energy required to capture, compress and transport the CO2to the underground

storage site. UK MARKAL currently assume a total process energy efficiency reduction of 5% to

account for CCS.


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Figure 2. Capital investment costs from the literature for hydrogen production technologies


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Figure 3. Energy efficiencies from the literature for hydrogen production technologies. The SMR and coal data include a

mix of CCS and non-CCS plants.


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3.2 Coal

Prior to the development of electricity networks, coal gasification was used to produce gas for

lighting purposes. The technology is mature but is less-widely used that SMR, despite cheaper fuel

costs, because the capital investment costs are higher and more variable and the energy efficiency is

lower. Only large-scale plants are envisaged in the literature.

UK MARKAL investment costs for current vintages are comparable to constructed plants but future

vintages are cheaper than forecasts in the literature (Figure 2). This is partly caused by the inclusion

of coal membrane gasification technologies using cost data from Parsons Group (Parsons

Technology Group 2002)that is considered speculative and possibly unrealistic (Pers. comm. F. Starr

2011). It is unlikely that the capital investment costs for coal gasification will change substantially in

the future.

The energy efficiency of coal gasification is lower than that of SMR (Figure 2), although the

differential has been reduced historically by relatively lower coal prices. Efficiencies range from

50%80%, which could represent both technological differences and the wide variations in the

quality of different types of coal. Even if membrane technology becomes available, overall

efficiencies are unlikely to change substantially in the future (e.g. see Li et al. 2010).

Any future energy efficiency improvements will be reduced by the incorporation of CCS. UK MARKAL

uses the same approach as for SMR and currently assume a total process energy efficiency reduction

of 5% to account for CCS. Since a greater quantity of CO2is produced by coal gasification for each

unit of produced hydrogen, one might expect a greater efficiency reduction for this technology. On

the other hand, membrane technology is expected to reduce the efficiency loss due to CO2capture

(Amelio et al. 2007).

3.2.1 IGCC

The hydrogen gas stream from coal gasification can be combusted to produce electricity in an

integrated gaseous combined cycle (IGCC) plant (Chiesa et al. 2005; Garca Corts et al. 2009). The

primary advantage of this technology is the flexibility it provides; in return for an additional capital

investment in turbines and steam generators, it allows electricity to be produced at times of peak

demand and hydrogen to be produced at other times.

The additional plant will be similar to a gas CCGT; the main rotating parts, condenser, cooling system

and electricals account for around 75% of the gas CCGT cost (Mott MacDonald 2010:p25). For a new

GTCC in 2030, technology ENGA-CC30B, there is an investment cost in UK MARKAL of 357/kW. We

therefore estimate the cost of upgrading a coal gasification plant to an IGCC as 268/kW. The

energy efficiency is more difficult to specify because it reduces as the proportion of electricity isincreased, hence the large range from the literature in Figure 3. Figure 4 shows that the overall

efficiency varies between 35% and 60% for one proposed plant (Cormos 2010), a conclusion

supported by Li et al. (2010)using a different model.

The UK MARKAL IGCC representation has fixed outputs of hydrogen (10%) and electricity (90%).

Since the principle advantage of this technology is increased flexibility over electricity generation,

with only minor efficiency improvements over conventional power stations, the current UK MARKAL

representation should be altered to reflect this increased flexibility.


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Figure 4. Overall IGCC efficiency as a function of the hydrogen production rate (data from Cormos 2010).

3.3

Biomass

Biomass accounts for 15% of global primary energy consumption and is particularly important in

less-developed countries. Technologies to produce hydrogen from biomass are most strongly

characterised by their diversity, in terms of both the types of technology and the range of different

biomass fuels that are used. All technologies suffer from low yields because of the low hydrogen

content of biomass (approximately 6%) and the 40% oxygen content which lowers the overall

available energy; as a result, there are no completed industrial-scale demonstrations of any biomass

technology for producing hydrogen (Kalinci et al. 2009)and cost and efficiency data must be

considered speculative. Efficiencies are higher for biomass-derived biofuels (e.g. bioethanol) that

are processed prior to the hydrogen production plant; the principle advantage of such fuels would

be to reduce the fuel transport costs from the plantation to the hydrogen plant. Biofuel production

has increased substantially in recent years, with the loss of land for food production causing

controversy.

Sexena et al. (2008)identify three broad methods for producing hydrogen from biomass:

1. Thermochemical conversion: combustion, gasification or pyrolysis of biomass. The latter

two are represented in the UK MARKAL model. Gasification is normally combined with

steam reforming to maximise the hydrogen yield. The most suitable crops UK indigenous

feedstocks would be wood or energy crops but imports would allow a greater range oftechnologies (for example, Haryanto et al. (2005)describe systems for steam reforming of

ethanol which could be produced from sugar cane or maize).

2. Biochemical/biological conversion, which uses either algae to decompose complex biological

molecules (e.g. anaerobic digestion) or photosynthesis with hydrogen as a by-product.

These technologies are limited by high capital costs and low production rates and so are only

ever likely to be niche solutions for problems such as biodegradable waste. Several small

anaerobic digestion plants have been constructed in the UK for electricity generation (ENDS

report 2011).


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3. Mechanical extraction, which produces very low yields and is never likely to be a viable

technology.

Figure 2 shows investment costs for biomass gasification and pyrolysis. Costs must be considered

speculative but are similar to coal gasification costs because the conversion processes and plant

requirements are broadly similar. Pyrolysis uses biomass oil as a feedstock which can be producedfrom wood.

The range of energy efficiencies in Figure 3 reflects the range of potential fuels; the conversion

efficiency of wood is unlikely to exceed 50% because of the low heat of combustion (Table 1) while

the higher values represent steam reforming of biofuels. The latter efficiencies are artificially high

because they do not account for the energy that is required to produce biofuel from the feedstock.

None of these technologies include CCS, which could potentially lead to negative lifecycle emissions

but would cause the process energy efficiency to reduce by perhaps 5%.

The biomass technology data in the UK and US9R MARKAL models are very different. The UK model

data appears to be broadly consistent with literature while the US9R model has a very pessimistic

representation.

3.4

Water

Alkaline electrolysis has been used to produce hydrogen since the eighteenth century and is the

basis of most commercially-available electrolysers. Extremely pure hydrogen is produced but at a

substantially higher cost than from SMR due to the substantially higher cost of electricity relative to

fossil fuel feedstocks. Low-temperature polymer electrolyte membrane (PEM) and high-

temperature solid oxide electrolyser (SOE) electrolysers have been proposed as more efficient

technologies for the future (DEA 2010). PEM electrolysers are suited to small-scale hydrogen

production while SOE electrolysers can reduce electricity requirements by the use of high-

temperature heat instead, a process called thermal cracking.

Figure 2 shows a wide range of capital investment costs for electrolysis systems from the literature.

The most surprising aspect is the large number of estimates that are substantially higher than even

the most expensive plants that have been built (the middle built estimate, at 18 GJ-1

y-1

, represents

the averagecost of building an electrolysis plant at present). Costs for small systems are particularly

high but all systems are expected to become substantially cheaper in the future through

technological breakthroughs and learning.

Twentieth-century electrolysers achieved energy efficiencies in the range 58%72% (Levene et al.

2007)and it is reasonable to assume that new electrolysers will be at the upper end of this range.

The efficiencies of current electrolysers in both MARKAL models, at 60%65%, are thereforerepresentative of older technology vintages and are lower than recent estimates reported in the

literature. Efficiencies in the range 85%95% are expected to be achieved for both small and

medium-sized plants in the future, particularly if PEM and SOE electrolysers can be successfully

developed.

3.4.1 Energy storage using hydrogen-electrolysis systems

Increasing the share of wind in UK electricity generation is likely to introduce a problem of power

generation intermittency. Electricity cannot be stored on a large scale but it has been proposed that

the excess could be stored by producing hydrogen through electrolysis.


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The electrolysers would be operated intermittently, which could cause efficiency reductions and

introduce heat management and safety issues (Sherif et al. 2005). If the electrolyser temperature is

too low, due to a low production rate, then the efficiency of the electrolyser will reduce. A low

production rate could also allow hydrogen and oxygen to permeate through the electrolyte and

come into contact, reducing the efficiency and possible causing a fire. Alkaline electrolysers are

particularly sensitive to these problems but PEM electrolysers are also affected to a lesser extent.

Hydrogen would be produced predominantly using off-peak electricity at times of low demand.

While this would decrease the running costs, it would increase the capital investment costs of the

electrolysers because production would be substantially below capacity. Any analysis of

intermittent production would have to carefully consider the electrolyser utilisation factor.

3.4.2 Thermochemical cracking of water

It was mentioned above that SOE electrolysers operating at higher temperatures achieve greater

hydrogen production efficiencies. Hundreds of other high-temperature chemical cycles have been

identified for producing hydrogen (Rosen 2010). Studies have primarily concentrated on two

technologies to produce the energy for these thermochemical cycles. Firstly, high-temperature

nuclear reactors could supply both electricity and high-temperature waste heat to an adjacent

production plant (Utgikar and Thiesen 2006;Lubis et al. 2010). Secondly, concentrated solar power

(CSP) plants could produce both electricity and the required temperatures in a central tower for

hydrogen production (Felder and Meier 2008; Coelho et al. 2010).

The USA has funded substantial research into fourth-generation high-temperature helium reactors

for hydrogen production under the DOE Nuclear Hydrogen Initiative program (Bartels et al. 2010)

but no plants have been demonstrated on an industrial scale. The high uncertainty in the capital

costs of such a system are reflected by the wide range of estimates in Figure 2. Cost evaluation tools

are now being developed (e.g. Khamis and Malshe 2010)so more authoritative estimates might

become available in future. The different technology energy efficiencies (Figure 3) reflect thedifferent efficiency measurements that are used in the literature. The higher estimate only

considers the hydrogen production plant (Steward et al. 2008)while the lower estimate represents

the entire nuclear reactor and hydrogen production system (Khamis and Malshe 2010). For the

hydrogen production process alone, the energy efficiency should exceed 90% in the future.

The costs of CSP are even more speculative. Most authoritative studies are relatively old (e.g.

Glatzmaier et al. 1998)and both the costs and efficiencies are uncertain at the moment due to the

early stage of development of the technologies (Steinfeld 2005), so no data is presented here. Both

costs and efficiencies would be strongly influenced by the location of the CSP plant due to the

variations in solar radiation across the planet.

4 Technology data for energy system models

We presented energy systems data for a range of hydrogen production technologies in Section 3. In

this section, we summarise the currently-modelled technologies in the UK and US9R MARKAL

models, recommend revised data for the future and consider uncertainties in the data and the

potential for technology learning to reduce investment costs and increase operating efficiencies.


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4.1 Summary of technologies in current MARKAL models

The hydrogen production technologies currently represented in the UK and US9R MARKAL models

are listed in Table 2. The US9R model focuses on technologies that are already mature and does not

incorporate improved technologies in the future. A wider range of technologies is represented in

the UK model with only medium SMR, which is not considered viable in the UK due to the relativelysmaller delivery distances compared to the USA, being excluded relative to the US9R model. The

IGCC technology in the UK model has a fixed hydrogen output (10% of the total). Neither model

includes nuclear or CSP thermochemical technologies.

Table 2. Summary of hydrogen production technologies represented in the UK and US9R MARKAL models. The UK

model versions were used for the Department for Transport hydrogen study (Strachan et al. 2008)and the more recent

Committee on Climate Change study (Usher and Strachan 2010).

Production UK DfT UK CCC US9R

Coal gasification (large) X X X

Membrane coal gasification X X

IGCC XSMR (large) X X X

SMR (medium) X

SMR (refuelling station) X X X

Biomass gasification (medium) X X X

Biomass pyrolysis (medium) X X

Waste gasification (medium) X X

Electrolysis (medium) X X X

Electrolysis (refuelling station) X X X

4.2

Recommendations for the future

We recommend a number of changes to the hydrogen production technologies that are included in

the UK MARKAL and TIAM-UCL models. Figure 5 shows the recommended energy system.

The IGCC is now represented as an additional add-on technology to coal gasification. Using this

approach rather than a single technology, the models will calculate the overall energy efficiency as a

function of the relative production of hydrogen and electricity rather than using fixed outputs as in

the current model.

A small biomass gasification system could be added that would be situated at a refuelling station. To

limit the labour requirements of such a system to acceptable levels, a high-energy imported liquidbiofuel would be used rather than biomass. The UK MARKAL model does not currently represent

biofuel imports for hydrogen production (although biofuels are used in E85 fuels) so this technology

should only be implemented if such imports are likely. Since the principle objective of a hydrogen

economy is to reduce GHG emissions, a new biomass gasification with CSS technology has been

added. It is assumed that the biomass feedstock is solid ligno-cellusic in nature. The UK MARKAL

model currently simulates biomass pyrolysis as a method of using domestic and imported biomass

oil (from pyrolysis of wood). Waste gasification similarly allows the conversion of solid wastes to

hydrogen although the current energy conversion efficiency of 65% seems very high. The latter is

limited by the amount of available waste. These technologies should only be included if the models

will be used to examine technological niches in the future or if substantial imports of biomass oil

might become available.


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We have included data for a fourth-generation high-temperature nuclear technology but this should

be considered extremely speculative and we recommend that this technology only be included if

more reliable data becomes available. Conventional nuclear plants are represented by the

electrolysis technology.

Figure 5. Recommended hydrogen production technologies for future versions of the UK MARKAL and UCL-TIAM

models. Dotted technologies should only be included if the circumstances outlined in the main text are satisfied.

The recommended year of availability, capital investment costs and energy efficiencies for each

technology are listed in Tables 3 and 4 for UK MARKAL and TIAM-UCL, respectively. Since capital

costs tend to reduce and efficiencies tend to increase over time, data is provided for technology

vintages in 2000, 2025 and 2050. All of the data represent averages of the study data plotted in

Figures 2 and 3. In view of the range of data in the literature, we rounded the data to the nearest 1

GJ-1

y-1

for the investment costs and 5% for the energy efficiencies.

UK MARKAL v3.26 separately accounts for the carbon capture part of the hydrogen production

plants (technology CCS-CPR). We instead assume, in the absence of better information, that

retrofitting does not occur and that the capital cost is not affected by CCS because the plant is

redesigned to separate the CO2from other streams. It is, however, necessary to reduce the

technology energy efficiency to account for CCS and we recommend a reduction of 5% in all cases.


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Table 3. Recommended UK MARKAL investment cost and energy efficiency data for hydrogen production technologies

for the period 20002050, for use in energy systems models. Technologies with CCS should reduce the energy

efficiencies by 0.05. Investment costs have units (2000) GJ-1

y-1

, except for those denoted by * that have units

m(2000) GW-1

. See the text for a description of the data source.

Technology Size First year Investment costs Energy efficiency

2000 2025 2050 2000 2025 2050Coal gasification Large 2000 18 16 14 65% 65% 65%

IGCC generation (after

coal gasification)

Large 2020 126* 126* 126* 60% 60% 60%

SMR Large 2000 5 4 3 80% 85% 85%

SMR Medium 2000 12 10 8 75% 80% 80%

SMR Small 2020 45 10 8 65% 80% 80%

Biomass gasification Large 2020 15 15 15 50% 50% 50%

Biomass gasification Medium 2020 30 20 20 50% 50% 50%

Biomass gasification Small 2020 45 25 25 50% 50% 50%

Biomass oil pyrolysis Medium 2020 30 20 20 50% 50% 50%

Waste gasification Medium 2020 30 20 20 50% 50% 50%Nuclear Large 2030 40 40 75% 75%

Electrolysis Medium 2000 18 10 10 75% 85% 90%

Electrolysis Small 2000 65 16 10 75% 85% 90%

Table 4. Recommended TIAM-UCL investment cost and energy efficiency data for hydrogen production technologies for

the period 20002050, for use in energy systems models. Technologies with CCS should reduce the energy efficiencies

by 0.05. Investment costs have units $(2005) GJ-1

y-1

, except for those denoted by * that have units $m(2005) GW-1

. See

the text for a description of the data source.

Technology Size First year Investment costs Energy efficiency

2000 2025 2050 2000 2025 2050

Coal gasification Large 2000 31 27 24 65% 65% 65%


coal gasification)

Large 2020 217* 217* 217* 60% 60% 60%

SMR Large 2000 9 7 5 80% 85% 85%

SMR Medium 2000 21 17 14 75% 80% 80%

SMR Small 2020 77 17 14 65% 80% 80%

Biomass gasification Large 2020 26 26 26 50% 50% 50%

Biomass gasification Medium 2020 52 34 34 50% 50% 50%

Biomass gasification Small 2020 77 43 43 50% 50% 50%

Biomass oil pyrolysis Medium 2020 52 34 34 50% 50% 50%

Waste gasification Medium 2020 52 34 34 50% 50% 50%

Nuclear Large 2030 69 69 75% 75%

Electrolysis Medium 2000 31 17 17 75% 85% 90%

Electrolysis Small 2000 112 27 17 75% 85% 90%

Energy system models also require annual operations and maintenance (O&M) costs for each

technology. The principle O&M cost for hydrogen production is the feedstock but this marginal cost

is calculated separately within the models. In most literature studies, the remaining costs are

predominantly fixed each year. The fixed O&M costs for each technology are plotted as a function

of the investment costs in Figure 6. There are variations for each technology but the fixed O&M

costs are generally around 5% of the investment costs.


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Figure 6. Fixed O&M costs from the literature for hydrogen production technologies.


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The UK MARKAL model currently represents all O&M costs as variable costs. We recommend that

these be changed to fixed O&M costs in future. Tables 5 and 6 list fixed O&M costs for 2000, 2025

and 2050 vintages of each technology for the UK MARKAL and TIAM-UCL models, respectively.

These costs were calculated by combining representative fixed O&M percentages from Figure 5 with

investment cost data from Table 4.

Table 5. Recommended UK MARKAL annual fixed O&M cost data for hydrogen production technologies for the period

20002050, for use in energy systems models. O&M costs have units (2000) GJ-1

y-1

, except for those denoted by * that

have units m(2000) GW-1


Technology Size Fixed O&M (% of

investment costs)

Fixed O&M costs

2000 2025 2050

Coal gasification Large 5% 0.9 0.8 0.7


coal gasification)

Large 5% 6.3* 6.3* 6.3*

SMR Large 4% 0.2 0.2 0.1

SMR Medium 4% 0.5 0.4 0.3

SMR Small 4% 1.8 0.4 0.3Biomass gasification Large 7% 1.1 1.1 1.1

Biomass gasification Medium 7% 2.1 1.4 1.4

Biomass gasification Small 7% 3.2 1.8 1.8

Biomass oil pyrolysis Medium 7% 2.1 1.4 1.4

Waste gasification Medium 7% 2.1 1.4 1.4

Nuclear Large 6% 2.4 2.4

Electrolysis Medium 5% 0.9 0.5 0.5

Electrolysis Small 5% 3.3 0.8 0.5

Table 6. Recommended TIAM-UCL annual fixed O&M cost data for hydrogen production technologies for the period20002050, for use in energy systems models. O&M costs have units $(2005) GJ

-1y

-1, except for those denoted by * that

have units $m(2005) GW-1


Technology Size Fixed O&M (% of

investment costs)

Fixed O&M costs

2000 2025 2050

Coal gasification Large 5% 1.5 1.4 1.2


coal gasification)

Large 5% 10.8 10.8 10.8

SMR Large 4% 0.3 0.3 0.2

SMR Medium 4% 0.8 0.7 0.5

SMR Small 4% 3.1 0.7 0.5Biomass gasification Large 7% 1.8 1.8 1.8

Biomass gasification Medium 7% 3.6 2.4 2.4

Biomass gasification Small 7% 5.4 3.0 3.0

Biomass oil pyrolysis Medium 7% 3.6 2.4 2.4

Waste gasification Medium 7% 3.6 2.4 2.4

Nuclear Large 6% 4.1 4.1

Electrolysis Medium 5% 1.5 0.9 0.9

Electrolysis Small 5% 5.6 1.4 0.9


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Energy system models require a breakdown of the energy inputs and outputs for each technology.

Table 7 shows data extracted from Khamis & Malshe (2010)for high-temperature nuclear and from

the H2A database (Steward et al. 2008)for the other technologies. Adding CCS to the plants would

increase the electricity consumption.

Table 7. Recommended energy source input and output data for hydrogen production technologies for use in energy

systems models. Technologies with CCS should increase the electricity input and reduce the feedstock by 4%. See the

text for a description of the data source.

Technology Energy input Energy output

Feedstock Electricity GH2 Electricity

Coal gasification 100% 0% 100% 0%


coal gasification)

100% 0% 0% 100%

SMR 100% 0% 100% 0%

Biomass and waste 97% 3% 100% 0%

Nuclear 100% 0% 70% 30%

Electrolysis 0% 100% 100% 0%

4.3

Uncertainties in technology costing

The plant investment costs presented in Section 3 apply to plants built in the USA or mainland

Europe. The indirect costs can vary in other countries because they are sensitive to land and labour

costs and to national taxation and environmental legislation.

The impact of technology data uncertainties can be assessed using in an energy systems model using

a formal sensitivity study, but this is a time-consuming process. The impacts will depend on both the

size of the uncertainty, the importance of the technology data in the overall energy system and theproximity of the technology to a tipping pointwhere an alternative technology would be chosen.

The size of the uncertainty can be gauged by comparing data from different studies in Figures 2 and

3: mature gas and coal technologies have lower uncertainties than other immature technologies.

The importance of the technology data depends on the relative size of the investment and feedstock

costs (and hence the feedstock marginal price); Ahluwalia et al. (2011)show that the production

plant investment costs are a relatively small part of the delivered hydrogen cost at current feedstock

prices so it is likely that errors in the energy efficiency will have greater impacts than errors in the

investment costs. The impact of tipping points can only be assessed using a model sensitivity study.

Energy system models tend to be conservative in nature because of a reliance on technologies that

are already mature. Part of the reason is that finding accurate data for unproven, immaturetechnologies is difficult; we encountered this problem in this project when looking for cost and

efficiency data for CSP hydrogen production systems. Where estimates are available in the

literature, it is necessary to critically appraise the rationality of the assumptions underlying the

estimates. For example, Figure 7 shows estimates for a number of technologies converging to a

single low cost in 2030 that is close to a coal + carbon tax cost. It seems highly unlikely that all of

these technology costs will converge to a similar cost when the exergies vary so much between

technologies.


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Figure 7: Hydrogen cost forecasts for a range of renewable systems (Lemus et al. 2010)

4.4 Learning curves

One of the aims of the UKSHEC II project is to examine how innovation and technology learning

might reduce hydrogen technology costs and improve efficiencies in the future. Learning curves

describe technology improvements, normally cost reductions, that are achieved as a result of large-

scale deployment of a technology.

There are limited opportunities for technology learning to influence hydrogen production

technologies. Natural gas and coal technologies are mature and are unlikely to change substantially

over the coming decades. Biomass gasification is an evolution of coal gasification, while nuclear

technologies are also evolutions of current technology. The technology with the most potential for

learning is electrolysis, where currently high investment costs and low energy efficiencies have the

potential to improve substantially as a result of fuel cell research and deployment. Electrolysis

technologies could be included in a technology cluster driven by fuel cell deployment.

5 Conclusion

A range of mature and immature technologies produce hydrogen from a range of fuels. We have

reviewed these technologies and recommended a number of changes to the UK MARKAL and TIAM-

UCL energy system models. The revised technologies represent a range of production methods and

feedstocks. Since the principle objective of a hydrogen economy is to reduce GHG emissions, CCS is

included as an option where appropriate.

Previous UK MARKAL versions included several similar technologies for the same feedstock (e.g. coal

gasification and membrane technologies). In the future, we recommend specifying a single

technology and represented the cost/efficiency improvements as step changes to the technology


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vintages. Such improvements are generally small compared to the variations between different

feedstocks.

We concentrated on mature technologies but included some immature technologies where

appropriate. The two areas where our analyses are most likely to be superseded are biomass, where

a great variety of technologies using different feedstocks are at the laboratory stage, and high-temperature hydrogen production.

6 References

Ahluwalia, R. K., T. Q. Hua, et al. (2011). "On-board and Off-board performance of hydrogen storage

options for light-duty vehicles." International Journal of Hydrogen Energy 37(3): 2891-2910.

Amelio, M., P. Morrone, et al. (2007). "Integrated gasification gas combined cycle plant with

membrane reactors: Technological and economical analysis." Energy Conversion and Management

48(10): 2680-2693.

Bartels, J. R., M. B. Pate, et al. (2010). "An economic survey of hydrogen production from

conventional and alternative energy sources." International Journal of Hydrogen Energy 35(16):

8371-8384.

Chiesa, P., S. Consonni, et al. (2005). "Co-production of hydrogen, electricity and CO2 from coal with

commercially ready technology. Part A: Performance and emissions." International Journal of

Hydrogen Energy 30(7): 747-767.

Coelho, B., A. C. Oliveira, et al. (2010). "Concentrated solar power for renewable electricity and

hydrogen production from water-a review." Energy & Environmental Science 3(10): 1398-1405.

Cormos, C. C. (2010). "Evaluation of energy integration aspects for IGCC-based hydrogen and

electricity co-production with carbon capture and storage." International Journal of Hydrogen

Energy 35(14): 7485-7497.

Damen, K., M. van Troost, et al. (2006). "A comparison of electricity and hydrogen production

systems with CO2 capture and storage. Part A: Review and selection of promising conversion and

capture technologies." Progress in Energy and Combustion Science 32(2): 215-246.

DEA (2010). Technology Data for Energy Plants. Copenhagen, Denmark, Danish Energy Agency.

ENDS report (2011). Government decision against energy crops not evidence-based. The ENDS

report. London, UK, Haymarket Business Media Ltd.

Felder, R. and A. Meier (2008). "Well-To-Wheel Analysis of Solar Hydrogen Production and Utilization

for Passenger Car Transportation." Journal of Solar Energy Engineering 130(1): 011017-011011.

Garca Corts, C., E. Tzimas, et al. (2009). Technologies for Coal based Hydrogen and Electricity Co-

production Power Plants with CO2 Capture. Luxembourg, Institute for Energy, European

Commission.

Glatzmaier, G., D. Blake, et al. (1998). Assessment of methods for hydrogen production using

concentrated solar energy. Golden, CO, USA, NREL.


21/22

21

Gray, D. and G. Tomlinson (2002). Hydrogen from Coal. Falls Church, VA, USA, Mitretek.

Haryanto, A., S. Fernando, et al. (2005). "Current status of hydrogen production techniques by steam

reforming of ethanol: A review." Energy & Fuels 19(5): 2098-2106.

Hawkins, S. and D. Joffe (2005). Technological Characterisation of Hydrogen Production

Technologies. London, UK, Policy Studies Institute.

Hughes, N. (2008). Hydrogen technologies: break-throughs, branching points and pathways. London,

UK, King's College.

Iaquaniello, G., F. Giacobbe, et al. (2008). "Membrane reforming in converting natural gas to

hydrogen: Production costs, Part II." International Journal of Hydrogen Energy 33(22): 6595-6601.

Joffe, D., N. Strachan, et al. (2007). Representation of Hydrogen in the UK, US and Netherlands

MARKAL Energy Systems Models. London, UK, Policy Studies Institute.

Kalinci, Y., A. Hepbasli, et al. (2009). "Biomass-based hydrogen production: A review and analysis."

International Journal of Hydrogen Energy 34(21): 8799-8817.

Kannan, R., N. Strachan, et al. (2007). UK MARKAL Model Documentation.

Khamis, I. and U. D. Malshe (2010). "HEEP: A new tool for the economic evaluation of hydrogen

economy." International Journal of Hydrogen Energy 35(16): 8398-8406.

Kreutz, T., R. Williams, et al. (2005). "Co-production of hydrogen, electricity and CO2 from coal with

commercially ready technology. Part B: Economic analysis." International Journal of HydrogenEnergy 30(7): 769-784.

Krewitt, W. and S. A. Schmid (2004). Fuel Cell Technologies and Hydrogen Production/Distribution

Options. CASCADE MINTS. Stuttgart, Germany, DLR Institute of Vehicle Concepts.

Lemus, R. G. and J. M. M. Duart (2010). "Updated hydrogen production costs and parities for

conventional and renewable technologies." International Journal of Hydrogen Energy 35(9): 3929-

3936.

Levene, J. I., M. K. Mann, et al. (2007). "An analysis of hydrogen production from renewable

electricity sources." Solar Energy 81(6): 773-780.

Li, F., L. Zeng, et al. (2010). "Techno-Economic Analysis of Coal-Based Hydrogen and Electricity

Cogeneration Processes with CO2 Capture." Industrial & Engineering Chemistry Research 49(21):

11018-11028.

Lubis, L. L., I. Dincer, et al. (2010). "Life Cycle Assessment of Hydrogen Production Using Nuclear

Energy: An Application Based on Thermochemical Water Splitting." Journal of Energy Resources

Technology 132(2).

Mott MacDonald (2010). UK Electricity Generation Costs Update. Brighton, UK.


22/22

22

NRC (2004). The Hydrogen Economy: Opportunities, Costs, Barriers, and R&D Needs. Washington, D.

C., USA, National Research Council of the National Academies.

NRC (2008). Transitions to alternative transportation technologies - a focus on hydrogen.

Washington, D. C., USA, National Research Council of the National Academies.

Ogden, J. M. (2001). Review of small stationary reformers for hydrogen production. Princeton, USA,

Princeton University.

Parsons Technology Group (2002). Hydrogen Production Facilities Plant Performance and Cost

Comparisons. Reading, PA, USA, Parsons Technology Group (under contract to US DoE National

Energy Technology Laboratory).

Rosen, M. A. (2010). "Advances in hydrogen production by thermochemical water decomposition: A

review." Energy 35(2): 1068-1076.

Saxena, R. C., D. Seal, et al. (2008). "Thermo-chemical routes for hydrogen rich gas from biomass: Areview." Renewable & Sustainable Energy Reviews 12(7): 1909-1927.

Schoots, K., F. Ferioli, et al. (2008). "Learning curves for hydrogen production technology: An

assessment of observed cost reductions." International Journal of Hydrogen Energy 33(11): 2630-

2645.

Sherif, S. A., F. Barbir, et al. (2005). "Wind energy and the hydrogen economy - review of the

technology." Solar Energy 78(5): 647-660.

Shirasaki, Y., T. Tsuneki, et al. (2009). "Development of membrane reformer system for highly

efficient hydrogen production from natural gas." International Journal of Hydrogen Energy 34(10):4482-4487.

Starr, F. (2011). Telephone call on 26/01/11 to W. McDowall.

Steinfeld, A. (2005). "Solar thermochemical production of hydrogen - a review." Solar Energy 78(5):

603-615.

Steward, D., T. Ramsden, et al. (2008). H2A Production Model, Version 2 User Guide. Golden,

Colorado, National Renewable Energy Laboratory, Department of Energy.

Strachan, N., N. Balta-Ozkan, et al. (2008). State-of-the-art modelling of hydrogen infrastructuredevelopment for the UK. London, UK, Policy Studies Institute.

Usher, W. and N. Strachan (2010). UK MARKAL Modelling - Examining Decarbonisation Pathways in

the 2020s on the Way to Meeting the 2050 Emissions Target. London, UK, UCL Energy Institute.

Utgikar, V. and T. Thiesen (2006). "Life cycle assessment of high temperature electrolysis for

hydrogen production via nuclear energy." International Journal of Hydrogen Energy 31(7): 939-944.

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