Use of Scenarios in the Special Report on Renewable Energy of

the IPCC Fifth Assessment Report Leon Clarke

May 25, 2011

Global Technology Strategy Program Technical Workshop

Joint Global Change Research Institute

There was a long discussion about using scenarios across chapters in the SRREN.

Energy-economic or integrated assessment models

Bottom-up assessments of technology cost and potential

The interaction should go both ways.

0

1

2

3

4

5

6

0 200 400 600 800Energy Production (EJ/yr)

Res

ourc

e G

rade

RESOURCE SUPPLY CURVE

Scenarios of scale, timing, location.

ENERGY SUPPLY SCENARIO

Supply curves and related aggregate representations

Vetting scenarios from aggregate models

For Chapter 10, we took on a thorough review of existing scenarios. ! Driving Questions:

! What sorts of future levels of renewable energy deployment are consistent with different CO2 concentration goals; or, put another way, what is the linkage between CO2 concentration goals and the deployment of renewable energy?

! Which classes of renewable energy will be the most prominent energy producers and how quickly might they expand production?

! Where would an expansion in renewable energy occur? ! What is the linkage between the costs of mitigation and an expansion

of renewable energy? ! The value of the dataset

! Latest scenarios, including delayed participation scenarios and limited technology scenarios.

! Collected data on renewable energy at a more detailed level than in previous assessments.

There is a broad spread of mitigation levels in the dataset.

Imagine how much stronger the story is going to be when we have thousands of scenarios.

Although there is some correlation between renewable deployment and mitigation level, there is enormous uncertainty.

Primary energy is not all that linked to stabilization level.

Fossil energy is tightly correlated to fossil and industrial CO2 emissions.

Low-carbon energy is far less correlated, because of energy demand.

Looking only at renewable energy adds the uncertainty of competition between nuclear and CCS.

Maybe the deployment of renewable energy is just a function of whether nuclear and CCS are available.

But that is clearly not the whole story.

The increase in costs from limiting renewables is comparable to the increase from limiting other technologies.

The increase in costs from limiting renewables is comparable to the increase from limiting other technologies.

There is no correlation between carbon prices and renewable energy deployment levels

The growth rates for some technologies are quite large.

One of the main lessons is that much of the growth in renewable energy takes place in the developing world.

One of the main lessons is that much of the growth in renewable energy takes place in the developing world.

In the SRREN, a small set of scenarios were used to for a more detailed exploration.

In the SRREN, a small set of scenarios were used to for a more detailed exploration.

In the SRREN, a small set of scenarios were used to for a more detailed exploration.

Chapter 10 used these specific scenarios to construct cost curves.

Chapter 10 also produced mitigation by technology for these scenarios.

Chapter 10 also produced mitigation by technology for these scenarios.

There was a long discussion about using scenarios across chapters in the SRREN.

Energy-economic or integrated assessment models

Bottom-up assessments of technology cost and potential

The interaction should go both ways.

0

1

2

3

4

5

6

0 200 400 600 800Energy Production (EJ/yr)

Res

ourc

e G

rade

RESOURCE SUPPLY CURVE

Scenarios of scale, timing, location.

ENERGY SUPPLY SCENARIO

Supply curves and related aggregate representations

Vetting scenarios from aggregate models

These sorts of ranges were passed to the chapter with the goal that they would try to explain what might need to happen to get to the higher deployment levels.

2020 2030 2050

050

100

150

200

250

300

350

Global Biomass Primary Energy SupplyG

loba

l Bio

mas

s Pr

imar

y En

ergy

Sup

ply

[EJ/

yr] N=137

BaselinesCat. III + IV (440-600 ppm)Cat. I + II (<440 ppm)

CO2 Concentration Targets

2020 2030 2050

020

4060

8010

012

0

Global Wind Primary Energy Supply

Glo

bal W

ind

Prim

ary

Ener

gy S

uppl

y [E

J/yr

]

N=152

2020 2030 2050

050

100

150

Global Solar Primary Energy Supply

Glo

bal S

olar

Prim

ary

Ener

gy S

uppl

y [E

J/yr

]

N=156

2020 2030 2050

010

2030

40

Global Hydro Primary Energy Supply

Glo

bal H

ydro

Prim

ary

Ener

gy S

uppl

y [E

J/yr

]N=164

2020 2030 2050

010

2030

4050

60

Global Geothermal Primary Energy Supply

Glo

bal G

eoth

erm

al P

rimar

y En

ergy

Sup

ply

[EJ/

yr] N=122

2020 2030 2050

010

2030

4050

6070

Global Wind and Solar PV Electricity Share

Glo

bal W

ind

and

Sola

r PV

Elec

trici

ty S

hare

[%] N=149

Where are we headed with AR5?

! Lots and lots and lots and lots of scenarios ! AMPERE, EMF 24, RoSE, LINKS, AME

! Imagine how much more illuminating this graph will be with ten times more scenarios!!

Where are we headed with AR5?

! But there are some particularly important new dimensions of coordination of scenarios: ! Technology, particularly with limits on the deployment of particular

technologies, for example, nuclear energy and CCS. ! Policy, particlularly idealized policy scenarios, for example the

EMF 22 and EMF 24 scenarios. ! Linkage to RCPs. ! Some scenarios with coordinated socioeconomics.

! Remaining to be worked out ! How will scenarios be used within WGIII? ! How will the RCPs be used to link across working groups?

Questions