Impact of technology uncertainty on future low-carbon pathways in the UK

Impact of technology uncertainty on future low-carbon pathways in the UK

Birgit Fais, Ilkka Keppo, Hannah Daly, Marianne Zeyringer

UCL Energy Institute, University College London

68th Semi-annual ETSAP MeetingSophia Antipolis, 22nd – 23rd June 2015

Technology uncertainty

Birgit Fais 2

Motivation

Research questions• Which technologies are most crucial to realize the UK’s long-term emission reduction

commitment? • Are there interdependencies between the use of different technologies? • How are carbon prices and energy system costs influenced by the

non-availability of important low-carbon options?

Low-carbon energy transition requires major technological changes

BUT: Availability, cost and performance of these technologies is highly uncertain

From the UK Government’s Carbon Plan:“But there are some major uncertainties. How far can we reduce demand? Will sustainable biomass be scarce or abundant? To what extent will electrification occur across transport and heating? Will wind, CCS or nuclear be the cheapest method of generating large-scale low carbon electricity? How far can aviation, shipping, industry and agriculture be decarbonised?”

Use energy systems modelling to explore the impact of technology

uncertainty on the long-term development of the UK energy system

3Technology uncertainty

Birgit Fais

Methodological approach• Model: UKTM-UCL Successor of UK MARKAL with updated data and new features Strong policy engagement (DECC) Open-source release planned for next year

• Uncertainty analysis Focuses on the availability, cost and diffusion of key low-carbon options (both

technologies and resources) for the UK energy system 5 dimensions identified: nuclear, biomass, CCS, renewables, demand-side change –

with either optimistic or pessimistic assumptions Try out all possible combinations -> 25 = 32 scenarios All low-carbon scenarios: -80% reduction target implemented as cumulative budget

• Results analysisCompare scenarios from different perspectives to identify general trends: Sector-specific perspective Fuel-specific perspective Indicators (emissions, energy savings, renewable targets) Costs

4

Dimensions on technology uncertainty

Reference Restricted

Nuclear (N)New nuclear capacity limited to 33 GW until 2050

No additions after 2010

CCS (C)

• Electricity: limited to 45 GW in 2050 • Industry & hydrogen: growth

constraints (10% p.a.)• Available in 2020 (2030 for BECCS)

CCS does not become available in the UK

Bioenergy (B)Based on CCC Bioenergy Review: 1300 PJ in 2050 (imports + domestic)

380 PJ in 2050

Renewables (R)• High technical potential (> 400 GW)• learning effects for all technologies

• Restricted potential (49 GW), • higher cost assumptions for offshore

wind & solar PV• marine & geothermal not available

Demand-side (D)

• Medium elasticities (-0.03 to -0.8)• growth constraints of 10 / 15% p.a.

on all innovative and energy-efficient technologies

• Low elasticities (-0.01 to -0.6)• growth constraints of 5% / 7.5% on

innovative and energy-efficient technologies


Birgit Fais

The unrestricted case

20502010

Electricity generation

45%

18%28%

7%

66%

20%

8%355 TWh 358 TWh

2010 2050

Final energy consumption

43%

33%18%

34%

27%

22%

11%

6350 PJ 5200 PJ28%

0%

45%

0%1%

3% 0%

3% 1% 18%

0% 1%

Coal Coal CCS Natural Gas Natural Gas CCS Oil BiomassBiomass CCS Wind Other RE Nuclear Hydrogen Net Imports

4%

33%

43%

2%18%

0% 0%

Electricity

-200

0

200

400

600

800

2010 2050

[Mt

CO

2e

q]

Other

AGR & LULUCF

Transport

Industry

Services

Residential

Electricity

-164%

-38%

• Electricity generation dominated by nuclear and BECCS

• Limited change on the demand side• Strong reliance on decarbonisation

of electricity sector (BECCS!) to reach -80% reduction target

Emission reduction

0

100

200

300

REF

N C B NC

BD

NC

R

NB

R

NC

BD

NB

RD

CB

RD

[GW

]

0

200

400

600

800

REF

N C B NC

BD

NC

R

NB

R

NC

BD

NB

RD

CB

RD

[TW

h]


Birgit Fais

Sector-specific (1) - Electricity

0

100

200

300

REF

B NC

R

NB

RD

[GW

]

Hydrogen

Nuclear

Other RE

Wind

Biomass CCS

Biomass

Oil

Natural Gas CCS

Natural Gas

Coal CCS

Coal

Generation Capacity

• Stronger electrification in scenarios where biomass and/or CCS not available and demand-side technology diffusion restricted

• Central role of wind in restricted scenarios -> expansion of renewables can lead to almost quadrupling of today’s installed capacity

• Significant role of gas only if nuclear energy not available & RE and/or biomass additionally restricted -> substantial role of gas CCS

• Hydrogen partially replaces gas as back-up capacity in some scenarios, significant contribution to generation only in NBRD


Birgit Fais

Sector-specific (2) – Buildings sector

0

300

600

900

1200

1500

REF C B D

NR

BD

NC

R

NB

R

CB

R

NC

BR

NB

RD

[PJ]

0

200

400

600

800

1000

REF C B D

NR

BD

NC

R

NB

R

CB

R

NC

BR

NB

RD

[PJ]

0

200

400

600

800

1000

REF D

NC

R

NC

BR

[PJ]

Other RE

Oil Products

Hydrogen

Natural Gas

Electricity

Coal

Biomass

• Electrification & demand reduction in the residential sector key strategy in most restricted scenarios

• In the services sector, most energy savings potentials are already exploited in the unrestricted case & less clear trend in terms of electrification

• While biomass does not play a substantial role in the residential sector, its use is increased significantly in the services sector (if CCS is not available & biomass not restricted, mostly in district heating plants)

Residential Services


Birgit Fais

Sector-specific (3) – Industry & Transport

0

200

400

600

800

1000

REF C B

NC

CB

NC

B

NB

R

NR

D

NC

BR

NB

RD

CB

RD

[PJ]

0

200

400

600

800

1000

REF NC

NB

R

NB

RD

[PJ]

Manufac. fuels

Other RE

Oil Products

Hydrogen

Natural Gas

Electricity

Coal

Biomass

0

400

800

1200

1600

2000

2400

REF C B D

NC

CB

NC

R

CB

D

NC

BD

NC

RD

NB

RD

[PJ]

• Further demand reductions in the industry sector only induced in extreme scenarios with no CCS and strong restrictions on the electricity sector

• Increased biomass use in industry in scenarios without CCS (even if biomass restricted)• Highest use of CCS in industry in scenarios with restricted biomass

• Significantly higher demand reduction in transport in scenarios with strongly restricted electricity sector

• Dimension D clearly limits transition to alternative vehicles• Stronger electrification when CCS is restricted

Industry Transport


Birgit Fais

Fuel-specific perspective

0

1000

2000

3000

4000

5000

6000

Natural gas Oil products Electricity Hydrogen Renewables Biomass

[PJ]

REF 2010

Use in 2050, across all 31 scenarios

• Strong variability in gas use• Oil products still relevant in transport sector• Stronger electrification in almost all restricted scenarios• Role of hydrogen strongly dependent on CCS availability• Strong role of renewables in electricity generation when

other options are restricted• Biomass use is always maxed out according to constraint


Birgit Fais

GHG emission reductionTotal emissions reduction: cumulative approach highlights cost efficiency of early action → none of the scenarios reaches -80% in 2050 (range from -67% to -76%) → the more restricted the technology availability the higher the tendency for early action

-200%-150%-100%-50%0%50%

Electricity

Residential

Services

Industry

Transport REF

• Electricity: contribution maxed out in unrestricted case, but always zero-carbon sector from 2035 onwards

• Residential: contribution increases significantly in most of the restricted cases• Services: Strong variation, even with possibility of emission increase• Industry: contribution depends strongly on availability of biomass & electricity• Transport: higher contribution from transport needed when CCS and low-carbon

electricity options not available

GHG emissions reduction (2050 to 2010)


Birgit Fais

Energy savings & use of renewable energy

• Crucial role of the residential sector in restricted scenarios

• Strong variation in transport fuel demand

• Strong overall reductions in scenarios without CCS & high levels of electrification or when supply side is very restricted

-60% -40% -20% 0% 20% 40%

Residential

Services

Industry

Transport

Total REF

Reduction in final energy consumption (2050 to 2010)

Renewable share in gross final energy consumption (2050)0% 20% 40% 60% 80% 100%

RE in electricity

RE in transport

RE in heating

Overall share REF

• Strong variation, especially in electricity

• Restriction of low-carbon options tends to increase the use of renewables

• Biofuels no relevant option for the transport sector

• Renewable use for heating dominated by heat pumps


Birgit Fais

Cost parameters

0%

5%

10%

15%

20%

25%

30%R

EF N C B R D

NC

NB

NR

ND CB

CR

CD BR

BD

RD

NC

B

NC

R

NC

D

NB

R

NB

D

NR

D

CB

R

CB

D

CR

D

BR

D

NC

BR

NC

BD

NC

RD

NB

RD

CB

RD

Change in cum. system costs to REF

67%

0

500

1000

1500

2000

2500

3000

0%

5%

10%

15%

20%

25%

30%R

EF N C B R D

NC

NB

NR

ND CB

CR

CD BR

BD

RD

NC

B

NC

R

NC

D

NB

R

NB

D

NR

D

CB

R

CB

D

CR

D

BR

D

NC

BR

NC

BD

NC

RD

NB

RD

CB

RD

[£2

01

0/t

CO

2e

q]

Change in cum. system costs to REF Carbon price

67%

• Non-availability of CCS and restricted biomass have the strongest impact in case of scenarios with one restriction

• Combined effect of several restrictions is usually greater than individual effects, exemption: CB

• Dimension R has strong impact in cases where other low-carbon electricity options are restricted

• In cases where all other dimensions fail, availability of nuclear and CCS (followed by renewables) most important to limit transition costs

• Carbon price at 244 – 7000 £ t/CO2eq in 2050 (with some extreme outliers); ranking usually quite similar to system cost, exemptions: CR/CBR & BD/NBD -> depends on shape of abatement cost curve

13

Conclusions

Comparative scenario analysis allows to identify critical insights on:

• Complementarity of technologies (e.g. strong dependence of hydrogen development on CCS availability)

• Substitutability of technologies (e.g. replacement of nuclear by renewables with limited cost increases)

• Critical technologies / low-carbon options (electrification!!) vs. “failed” technologies (marine?)

• Issues of timing and path dependencies (e.g. importance of early action)

In terms of government strategy: is it better to support a wide range of technologies or is it time to “pick winners” at some point?

Modelling the resource nexus

Birgit Fais

Thank you for your attention!

Dr Birgit Fais UCL Energy Institute

University College London

[email protected]

This research was supported under the Whole Systems Energy Modelling

Consortium (WholeSEM) – Ref: EP/K039326/1

www.wholesem.ac.uk/

mailto:[email protected]

http://www.wholesem.ac.uk/

Data & Analytics

Impact of technology uncertainty on future low-carbon pathways in the UK