Australian-German Climate and Energy College and the ...climatecollege.unimelb.edu.au/files/site1/seminar_documents/Wolf-P… · Optimal hydrogen supply chains: co -benefits for integrating

Australian-German Climate and Energy College and the Energy Transition Hub Seminar

Optimal hydrogen supply chains: co-benefits for integrating renewable energy sourcesFabian Stöckl. Wolf-Peter Schill, Alexander ZerrahnSeptember 17, 2019

Work in progress – working paper and source codeshould be available by October 2019

Background

Optimal hydrogen supply chains

German energy and climate policy targets• Strongly increasing use of variable renewable

energy sources• Decarbonization of all energy sectors

Sector coupling as a strategy to• (i) decarbonize other sectors• (ii) provide flexibility to the power sector

often under-represented in IA models• E.g., produce hydrogen with renewable electricity

and use it for mobility, heating, industry, …

Focus here• Domestic H2 production and distribution• Use of H2 for fuel-cell electric vehicles• Research carried out in Kopernikus project P2X, supported by BMBF

Stöckl, Schill, Zerrahn. September 17, 2019, Melbourne

1

BMWI, AGEE Stat: Zeitreihen zur Entwicklung der erneuerbaren Energien in Deutschland

https://www.erneuerbare-energien.de/EE/Navigation/DE/Service/Erneuerbare_Energien_in_Zahlen/Zeitreihen/zeitreihen.html



Research questions and contribution


We aim to determine least-cost hydrogen supply chains…• … considering differences in energy efficiency, investment costs, and storage capabilities• … and considering electricity system interactions

This calls for a numerical model• We develop an open-source model and apply it to a future (German) power system with high

shares of renewables

Outcomes of interest• Hydrogen: optimal technology mix, supply costs, and their drivers• Electricity system: effects on capacity and dispatch, costs

What is new?• Previous studies often did not account for power sector interactions of flexible hydrogen supply• Fully open-source / open data analysis


1

Background

The model

1

Model: DIETER


Visit DIETER• Open-source GAMS code under MIT license• www.diw.de/dieter• https://github.com/diw-berlin/dieter

Cost minimization• Dispatch and investment• Hourly resolution over one year• Thermal and renewable technologies• Different types of electricity storage• Demand-side management, reserves• Residential heating, electric vehicles

Linear program• Deterministic, perfect foresight

• No transmission constraints


2

http://www.diw.de/dieter

https://github.com/diw-berlin/dieter

Model: extension of DIETER


New hydrogen module• Two electrolysis technologies• Four channels for distributing H2 to fuel stations, including

• Gaseous H2

• Liquified H2

• LOHC

• Different storage options• Follow-up work: reconversion to electricity

Full co-optimization• Model decides on optimal capacities and hourly use• Given conventional electricity demand and H2 demand for mobility


2

https://commons.wikimedia.org/wiki/File:Dibenzyltoluene_V1.svg

https://commons.wikimedia.org/wiki/File:Dibenzyltoluene_V1.svg

2 Overview of hydrogen supply chains in the model

Stöckl, Schill, Zerrahn. September 17, 2019, MelbourneOptimal hydrogen supply chains

We investigate not all channels in onemodel run, but combinations of eachcentralized with the decentralized channel

Data and scenarios


Electricity sector• Brownfield scenario for 2030• Capacities bounded by current grid

development plan (NEP)• Maximum investment into thermal

plants, minimum investments intorenewables and storage

• Time series provided by Open Power System Data & ENTSO-E

• Exogenous minimum renewablesshare of 65%, 70%, 75%, 80%


2

Hydrogen infrastructure• Fully „greenfield“• H2 demand for mobility: 0, 5%, 10%, 25% of passenger road traffic in Germany (0, 9, 18, 45 TWhH2)• General assumptions: each fuel station can only offer H2 from one channel

Lignite; 9.3 GWHard coal; 9.8 GW

CCGT; 17.6 GW

OCGT; 17.6 GW

Oil; 3.2 GW

Other; 4.1 GW

Run-of-river; …

Biomass; 6.89 GW

Wind onshore; 81.5 GWWind offshore; 17.0 GW

PV; 91.3 GW

Pumped-hydro storage; 9.5 GW

Lithium-ion batteries; 2.0 GW

https://www.netzentwicklungsplan.de/de/netzentwicklungsplaene/netzentwicklungsplan-2030-2019

https://doi.org/10.1016/j.apenergy.2018.11.097

Background

Some intuition: potential drivers of results

1

Drivers I: Tradeoff between overall efficiency and flexibility


LOHC dominated by GH2 and LH2 (worse in both dimensions in direct comparison)


3

DEC

GH2 LH2

LOHC

0

10

20

30

40

50

60

40 45 50 55 60 65 70

Elec

tric

ity d

eman

d at

the

fillin

g st

atio

n af

ter m

ass s

tora

ge (

kWh e

l/kg H

2)

Overall elecricity demand of hydrogen supply chain (kWhel/kgH2)

mor

efl

exib

le

more energy efficienct

Drivers II: Fixed investment and transportation capacity costs


Only 3% spread between cheapest and most expensive supply chain Transportation costs highest for GH2 , low effective load capacity of GH2 trailer


3

0

5,000

10,000

15,000

20,000

25,000

30,000

DEC GH₂ LH₂ LOHC

unw

eigh

ted

fixed

cos

ts (€

/kW

)w

ith(o

ut) t

rans

port

atio

n

0

200

400

600

800

1,000

1,200

1,400

GH₂ LH₂ LOHC

tran

spor

tatio

n ca

paci

ty c

osts

(€/k

g H2)

Drivers III: Storage costs (and losses)


• Substantially lower storage costs for LH2 and LOHC• Expensive high pressure storage at the filling station only buffer storage• LH2 also suffers from boil-off (about 20%/week)

Intuition not so clear Analysis with numerical optimization model required


3

0

2

4

6

8

10

12

14

16

18

20

DEC(only HP)

GH₂ LH₂ LOHC HighPressure

stor

age

cost

s (€

/kg)

fillin

g st

atio

n

Background

Results: hydrogen supply

1

Results: hydrogen supply chains and H2 supply costs

Optimal hydrogen supply chainsStöckl, Schill, Zerrahn. September 17, 2019, Melbourne

4

Low RES share, low H2 demand:• Limited renewable surpluses• Not much need for additional flexibility• Decentralised H2 supply dominant because

high energy efficiency matters most



4

High RES share, low H2 demand:• Higher renewable surplus generation• Temporal flexibility more beneficial• LH2 and LOHC allow longer-term storage



4

High H2 demand:• LH2 or LOHC beneficial• High RES: boil-off prevents seasonal storage with LH2• Hardly any GH2: high storage and transportation costs

Background

Results: electricity system

1

4 Effects on generation capacity (vs. respective baseline)


-10

0

10

20

30

40

50

Res65-Dem5(DEC)

Res65-Dem25(DEC+LH2)

Res80-Dem5(DEC+LOHC)


Gig

awat

t

Pumped hydro

Li-ion

Other renewable

PV

Offshore wind

Onshore wind

Other conventional

Natural gas

Hard coal

Lignite

More PV and (a bit) less storage Less capacity needed in high-RES scenario (better utilization)

4 Effects on yearly electricity generation (vs. respective baseline)


-30

-10

10

30

50

70

90

Res65-Dem5(DEC)




TWh

Pumped hydro

Li-ion

Other renewable

PV

Offshore wind

Onshore wind

Other conventional

Natural gas

Hard coal

Lignite

Storage capability of LOHC and LH2 allows additional integration of wind power

4 Effects on renewable curtailment (vs. respective baseline)


-50

-40

-30

-20

-10

0

10

Res65-Dem5(DEC)




TWh

LOHC makes use of renewable electricity that would otherwise be curtailed

4 Effects on system LCOE (without fixed H2 costs)


Clear renewable integration co-benefit of hydrogen in 80% renewables case

-10%

-8%

-6%

-4%

-2%

0%

2%Res65-Dem25 (DEC+LH2) Res80-Dem25 (DEC) Res80-Dem25 (DEC+LOHC)

4Sneak preview: what about battery-electric vehicles?Effects on system LCOE (without fixed H2 or BEV-related costs)


If BEV are used instead of fuel cell H2 vehicles, also substantial co-benefits …and lower electricity demand, lower deployment of RES, lower overall cost

-10%

-9%

-8%

-7%

-6%

-5%

-4%

-3%

-2%

-1%

0%Res80-Dem25 (DEC+LOHC) Res 80_Dem25 EV (no V2G) Res 80_Dem25 EV (with V2G)

To be explored in more detail in future work

Summary and conclusion


Tradeoff between energy efficiency and temporal flexibility• Energy-efficient decentral electrolysis optimal for lower shares of variable renewables• Less energy-efficient centralized electrolysis gains relevance with higher shares of variable

renewables because of storage benefits

Optimal choice of H2 supply chains also needs to consider other factors• Space requirements• Technology acceptance• Perceived / real danger of operations


5

Summary and conclusion


Flexible sector coupling• …can generate substantial co-benefits for integrating wind and solar energy

should be considered in energy models• …but also requires additional deployment of variable renewables

Limitations• Results are driven by renewable surplus generation• Surpluses may be over-estimated, as we do not consider competing options for flexibility and

sector couplingMore research on energy system implications of massive sector coupling necessary

Future research• Additional or competing flexibility options in the electricty sector• Long-term power storage via H2-to-electricity• Maybe: how does this compare with Australia?


5

Thank you for listening

DIW Berlin — Deutsches Institutfür Wirtschaftsforschung e.V.Mohrenstraße 58, 10117 Berlinwww.diw.de

ContactDr. Wolf-Peter [email protected] | @WPSchill

Utilization patterns LOHC (RES75 DEM5)


4

0

2

4

6

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2hydr

ogen

atio

n ac

tivity

(MW

)

electricity price (€/kWh)

Hydrogenation

0

1

2

3

0 0.05 0.1 0.15 0.2 0.25dehy

drog

enat

ion

activ

ity (M

W)


Dehydrogenation

00.20.40.60.8

11.2

151

710

3315

4920

6525

8130

9736

1341

2946

45 5161

5677

6193

6709

7225

7741

8257Fi

lling

leve

l (TW

h)

Hour of the year

LOHC (production site storage)

020406080

151

710

3315

4920

6525

8130

9736

1341

2946

45 5161

5677

6193

6709

7225

7741

8257Fi

lling

leve

l (M

Wh)

Hour of the year

LOHC storage at filling stations (per station)

02468

1012

1 11 21 31 41 51 61 71 81 91 101 111 121

131

141

151

Filli

ng le

vel (

MW

h)

Hour of the year

HP storage at filling stations

„Flexible“ H2 storage loading

0

0.2

0.4

0.6

0.8

1

1 11 21 31 41 51 61 71 81 91 101 111 121

131

141

151

Filli

ng le

vel (

MW

h)

Hour of the year

HP storage at filling stations

02468

10

158

5116

917

5323

3729

2135

0540

8946

7352

5758

4164

2570

0975

9381

77Filli

ng le

vel (

MW

h)

Hour of the year

LH2 storage at filling stations (per station)

00.10.20.30.40.5

151

710

3315

4920

6525

8130

9736

1341

2946

45 5161

5677

6193

6709

7225

7741

8257Fi

lling

leve

l (TW

h)

Hour of the year

LH2 (production site storage)

0

1

2

3

4

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2

lique

fact

ion

activ

ity

(MW

)


Liquefaction

Utilization patterns LH2 (RES75 DEM5)


4

0

1

2

3

0 0.05 0.1 0.15 0.2 0.25

evap

orat

ion

activ

ity

(MW

)


Evaporation

Flexibility of storage loadingconstrained by boil-off

Documents

Australian-German Climate and Energy College and the ...climatecollege.unimelb.edu.au/files/site1/seminar_documents/Wolf-P… · Optimal hydrogen supply chains: co -benefits for integrating