Supplementary Material

Net energy and carbon footprint analysis of solar hydrogen production from the

high-temperature electrolysis process

Authors:

Deepak Yadav and Rangan Banerjee*

-Department of Energy Science and Engineering,

Indian Institute of Technology Bombay,

Powai, Mumbai 400 076, India

Corresponding author: Tel.: +91 22 2576 7883, ; Fax: +91 22 25726875.

E-mail address: rangan@iitb.ac.in (R. Banerjee).

This document contains the following information.

Section S1: This section reports the life cycle parameters for electricity obtained from

the concentrated solar power (CSP) and photovoltaic (PV) plants. Figures S1 and S2

show the plot of cumulative energy demand (CED) and carbon emission footprint

(CEF) of power obtained from CSP and PV plants. The graphs are illustrated for CSP

plant size of 1-50 MW.

Section S2: This section reports the life cycle parameters of the alkaline electrolyzer

(AE). The distribution of CED and CEF for the alkaline electrolyzer are illustrated in

Figure S3.

Page 1 of 16

Section S3: This section presents the plot of variation in CED and CEF of hydrogen

obtained from the concentrated solar power (CSP)-based high-temperature steam

electrolysis (HTSE) process. The results are presented for the fixed electrolyzer area

configuration. The plots can be seen in Figures S4 and S5.

Section S4: This section presents the plot of variation in CED (Figure S6) and CEF

(Figure S7) of hydrogen obtained from the CSP-based HTSE process. The plots are

indicated for the fixed steam conversion rate configuration.

Section S5: This section presents the effect of degradation rate on the energy demand

and carbon footprint of the PV-based HTSE process. The results are presented in

Figure S8.

Section S6: This section reports the results from the Monte-Carlo simulation of the

CSP-based HTSE process. The results for the uncertainty in CED and CEF are

presented in Figures S9 and S10, respectively.

Section S7: This section presents the results from the Monte-Carlo simulation of the

PV and CSP based alkaline electrolysis (AE) processes. The results are presented in

Figures S11-S14.

Section S8: This section reports the results from the sensitivity analysis of the CSP-

based HTSE process. The sensitivity study for the CED and CEF of the CSP-based

HTSE process are presented in Figures S15 and S16, respectively.

Section S9: This section presents the results from the parametric analysis of the solar-

based HTSE process. The results are presented in Figures S17-S25.

S1: Life cycle parameters of the solar power plants

Figures S1 and S2 show the comparison of CED and CEF of the PV and CSP plants

respectively. It is observed that the environmental impact of the electricity from the CSP

plant reduces as the plant capacity increases. This is due to the increase in the power block

efficiency with the increase in size. It is observed that the PV plant has a lower environmental

impact than the CSP system. Unlike the CSP plant, the environmental impacts of the power

obtained from the PV system does not change with the size.

Page 2 of 16

0

0.1

0.2

0.3

0.4

0.5

0.6

1 MW 5 MW 10 MW 25 MW 50 MW PV Plant

CE

D (M

J/kW

h)

CSP plants

Solar field

Power block

HTF system Plant

construction

Grid electricity

Natural gas

O&MTransportation

Water

PV Plant

PEU unit

Fig. S1: Cumulative energy demand of the PV and CSP plants

0

5

10

15

20

25

30

35

1 MW 5 MW 10 MW 25 MW 50 MW PV plant

CE

F (g

/kW

h)

CSP plants

Solar field

Power block

HTF system

Grid electricity

O&MTransportation

Water

Plantconstruction

Natural gas

PV Plant

PEU unit

Fig. S2: Carbon emission footprint of the PV and CSP plants

Page 3 of 16

S2: Life cycle parameters of the alkaline electrolyzer

Figure S3 show the life cycle parameters of the alkaline electrolyzer. The material consumed

in the construction of the alkaline electrolyzer is obtained from Burkhardt et al. [1].

63%

2%

9%

3%

9%

11%2% 0% 0% 1%

SteelCast ironCopperAluminiumNickelPolymerResinZeolithElectronicsConcrete

57%

2%7%

4%

10%

14%

1%0% 0% 5%

SteelCast ironCopperAluminiumNickelPolymerResinZeolithElectronicsConcrete

63%

2%

9%

3%

9%

11%2% 0% 0% 1%

SteelCast ironCopperAluminiumNickelPolymerResinZeolithElectronicsConcrete

Fig. S3: Life cycle parameters of the alkaline electrolyzer

S3: Fixed electrolyzer area configuration

Figures S4 and S5 show the plot of variation in CED and CEF, respectively for the CSP-

based HTSE process. The plots are obtained for fixed electrolyzer area configuration. The

observations from the graph are similar to the PV-based system discussed in section 3.2.1 of

the main text.

Page 4 of 16

18

23

28

33

38

43

1000 3000 5000 7000 9000

CE

D (M

J/kg

)

Current density (A/m2)

873 K923 K973 K1023 K1073 K1123 K1173 K1223 K1273 K873 K - EH923 K - EH1273 K - EHAE

Fig. S4: Variation in the energy demand of the CSP-driven HTSE system

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8

1000 3000 5000 7000 9000

CE

F (k

g/kg

)

Current density (A/m2)

873 K923 K973 K1023 K1073 K1123 K1173 K1223 K1273 K873 K - EH923 K - EH1273 K - EHAE

Fig. S5: Variation in the carbon footprint of the CSP-driven HTSE system

Page 5 of 16

S4: Fixed steam conversion configuration

Figures S6 and S7 show the plot of variation in CED and CEF, respectively. The results are

plotted for the CSP-based HTSE process with a fixed steam conversion rate of 90%.

18

23

28

33

38

0 2000 4000 6000 8000 10000 12000 14000

CE

D (M

J/kg

)

Current density (A/m2)

873 K923 K973 K1023 K1073 K1123 K1173 K1223 K1273 K873 K - EH923 K - EH1273 K - EHAE

Fig. S6: Variation in the CED of the CSP-driven system for 90% steam conversion

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8

0 2000 4000 6000 8000 10000 12000 14000

CE

F (k

g/kg

)

Current density (A/m2)

873 K923 K973 K1023 K1073 K1123 K1173 K1223 K1273 K873 K - EH923 K - EH1273 K - EHAE

Fig. S7: Variation in the CEF of the CSP-driven system for 90% steam conversion

Page 6 of 16

S5: Effect of degradation rate

Figure S5 shows the effect of electrolyzer degradation on the energy demand and carbon

footprint of the PV-based HTSE process. The analysis is done for the system that uses an

electric heater. It is observed that there are significant uncertainties and lack of data points for

the electrolyzer degradation rates at various temperature and current density conditions

considered in the study. The analysis can be refined if these uncertainties are addressed.

1

1.5

2

2.5

3

3.5

0

5

10

15

20

25

30

1000 3000 5000 7000 9000 11000C

EF

(kg/

kg)

CE

D (M

J/kg

)

Current density (A/m2)

CED with degradation

CED without degradation

CEF without degradation

CEF with degradation

Fig. S8: Effect of electrolyzer degradation on the CED and CEF at 1073 K

S6: Monte-Carlo simulation of PV and CSP based HTSE process

Figures S9 and S10 show the results of the uncertainties in CED of the PV and CSP based

HTSE process. The trend of results is similar to the CEF discussed in section 4.1 (main text).

Page 7 of 16

Fig. S9: Distribution of CED for the PV driven HTSE process

Fig. S10: Distribution of CED for the CSP driven HTSE process

S7: Monte-Carlo simulation for solar- based alkaline electrolysis process

Figures S11-S14 show the distribution of uncertainty in the life cycle parameters of solar-

based alkaline electrolysis processes. It is seen that the specific energy consumption in the

alkaline electrolyzer is the major source of uncertainty in the analysis. The performance ratio

and efficiency of the PV systems also impact the embodied energy and carbon footprint of

Page 8 of 16

the alkaline electrolysis system. The mean values of energy demand and carbon footprint are

within ±18% of the 10th and 90th percentile. The base-case values are comfortably within the

10th and 90th percentile range.

Fig. S11: Distribution of CED for the PV-based AE process

Fig. S12: Distribution of CEF for the PV-based AE process

Page 9 of 16

Fig. S13: Distribution of CED for the CSP-based AE process

Fig. S14: Distribution of CEF for the CSP-based AE process

S8: Sensitivity analysis for solar-based HTSE process

Figures S15 and S16 show the sensitivity analysis of the CED for the PV and CSP based

HTSE processes respectively. In the analysis, the lower and upper range of the parameters is

Page 10 of 16

varied by ±30% of the base-case values. It can be seen that the life cycle parameters are more

sensitive to the annual solar radiation, the efficiency of the plant and life cycle parameters of

the photovoltaic, parabolic trough collector (PTC) and solid oxide electrolyzer.

14 16 18 20 22 24

PTC CED

SF2 efficiency

SF1 efficiency

SOSE CED

SOSE Life

PV CED

PV Efficiency

GHI

PV Performance ratio

CED (MJ/KG)

UpperLower

Fig. S15: Sensitivity analysis of the CED for the PV driven system

17 19 21 23 25 27 29

SF2 efficiency

SF1 efficiency

Natural gas consumption

SOSE CED

SOSE Life

PTC CED

CSP Efficiency

DNI

UpperLower

Fig. S16: Sensitivity analysis of the CED for the CSP driven system

Page 11 of 16

S9: Parametric study for carbon emission footprint (CEF) of HTSE process

Figures S17-S25 show the effect of various parameters on the CED and CEF of the solar-

HTSE process. The observations are similar to the variation in energy demand discussed in

section 4.3 of the main text.

14

19

24

29

34

39

1700 1900 2100 2300 2500

CE

D (M

J/kg

)

Embodied energy of PV system (MJ/m2)

873 K923 K973 K1073 K1173 K1273 K

Base value

Fig. S17: Effect of embodied energy of the PV system on the energy demand

15

20

25

30

35

40

1500 1700 1900 2100 2300

CE

D (M

J/kg

)

Embodied energy of CSP system (MJ/m2)

873 K923 K973 K1073 K1173 K1273 K

Base value

Fig. S18: Effect of embodied energy of the CSP system on the energy demand

Page 12 of 16

14

19

24

29

34

39

7000 9000 11000 13000 15000

CE

D (M

J/kg

)

Embodied energy of SOSE (MJ/m2)

873 K923 K973 K1073 K1173 K1273 K

Base value

Fig. S19: Effect of the embodied energy of SOSE on the CED of the PV driven process

1

1.2

1.4

1.6

1.8

400 500 600 700 800

CE

F (k

g/kg

)

Carbon footprint of SOSE (kg/m2)

873 K923 K973 K1073 K1173 K1273 K

Base value

Fig. S20: Effect of carbon footprint of the SOSE on the CEF

Page 13 of 16

10152025303540455055

7 10 13 16 19 22

CE

D (M

J/kg

)

PV plant efficiency (%)

873 K923 K973 K1073 K1173 K1273 K

Efficiency considered

Fig. S21: Effect of the PV plant efficiency on the energy demand

15

20

25

30

35

40

45

50

12 17 22 27 32

CE

D (M

J/kg

)

CSP plant design efficiency (%)

873 K923 K973 K1073 K1173 K1273 K

Efficiency considered

Fig. S22: Effect of the CSP plant efficiency on the energy demand

Page 14 of 16

12

17

22

27

32

37

42

1500 1700 1900 2100 2300 2500 2700

CE

D (M

J/kg

)

GHIannual (kWh/m2/year)

873 K923 K973 K1073 K1173 K1273 K

GHIannual at the proposed location

Fig. 23: Effect of the annual global horizontal irradiation for the PV-based process

15

20

25

30

35

40

45

1500 1700 1900 2100 2300 2500 2700

CE

D (M

J/kg

)

DNIannual (kWh/m2/year)

873 K923 K973 K1073 K1173 K1273 K

DNIannual at the proposed location

Fig. S24: Effect of the annual direct normal insolation for the CSP-based process

Page 15 of 16

121722273237424752

0 3 6 9 12 15 18 21 24

CE

D (M

J/kg

)

SOSE life (years)

873 K923 K973 K1073 K1173 K1223 K1273 K

Life considered for the analysis

Critical lifetime

Fig. S25: Effect of the electrolyzer life on the CED of the PV-based process

Page 16 of 16