This document discusses using an S-curve model to project technology uptake like electric vehicles and renewable energy sources under different policy scenarios. It can model a "best practice policy" scenario based on successful country examples and a "no policy" scenario without incentives. The model links specific policies to factors that influence adoption rates. Analysis identifies policy areas where countries can improve incentives to increase technology uptake towards best practice levels. Results are intended to help policymakers understand how policies impact projections and what more actions may be possible.

1. CTI Model upgrade
How to strengthen the EU NDC?
Understanding the impact of sector-based policies.
EU Pavilion Side Event at COP23
10 November 2017
Markus Hagemann (NewClimate Institute)

2. CTI Model upgrade
Projections attempt at grasping a complex
future with many influencing factors
 Unforseen trends (e.g. EV, solar PV),
barriers (e.g. CCS), policy
developments can change
trajectories
Enabling policy makers to understand the
link between policies and trajectories
enables them to take better informed
decisions
 How do barriers and policies that are
part of a policy package link to the
trajectory?
Source Figure 1: Cronin, C. et al. (2015) Faster and Cleaner - Decarbonisation in the power and transport sectors is surpassing predictions and offering hope for
limiting warming to 2°C. San Francisco, USA. Available at: https://newclimateinstitute.files.wordpress.com/2015/12/faster-cleaner-decarbonization-in-the-power-
transport-sectors.pdf.
16-11-17 COP 232
Transparency in policy analysis enables policy makers to understand
projections better

3. CTI Model upgrade3 16/11/2017
Linking policy packages to levers in the CTI model
CTI Model
Sector X
Activity
Intensity
Policy 1
Policy 2
Policy lever X
Other lever Y
…
Policy 4
Policy package
modelled in tool
Non-policy
factors 1
Non-policy
factors 2
Illustration of the model logic
Policy 3
Non-policy
factors 1

4. CTI Model upgrade CONFIDENTIAL4 16/11/2017
S-curve - a proven market diffusion model to estimate future technology uptake
Historical uptake of different technologies followed s-curved market dynamics in a
large number of sectors
 the S-curve is a proven concept of technology uptake

5. CTI Model upgrade
Our knowledge about two
extreme cases allows us to
determine a policy pathway:
1. „Best practice policy case“
are policy examples in
countries that have
successfully implemented
policy package to
incentivise diffusion.
2. „No policy case“ represent
trajectories where diffusion
is achieved (or not) without
the influence of policies
5
The S-Curve approach
Current policy
trajectory
“No policy case”
“Best practice policy
case”

6. CTI Model upgrade
“
Best practice policy” S-curve: based on Norway’s historical EV uptake
“No policy” S-curve: based on IEA EV Outlook 4DS scenario (global)
COP 236 16/11/2017
S-curve bounded by Norways best practice examples describes EV
uptake
Current
policy
curve
“No policy” curve
“Best practice policy” curve
Incentive factor
One factor identified for each MS
0%
100%
Incentive factor
• Density of chargers
• Financial incentives (level of
purchase subsidy and existence of
tax rebates)
• Behavioural characteristics
(wealth, propensity to buy second
car)
• Behavioural incentives (i.e., access
to bus lanes, free parking)
1

7. CTI Model upgrade COP 237 16/11/2017
Analysis highlights individual policy-relevant areas with potential for
more action in individual MS1
Analysis is based on important policy relevant indicators that can be easily
understood by policy makers
 benchmarking againts „Best practice“ case (or other MS) allows policy
makers to understand which levers they can take to increase action
NON-EXHAUSTIVE
€ 0
€ 1,000
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€/vehicle
Purchase subsidies
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
Norway
France
Austria
Netherlands
Luxembourg
Malta
UnitedKingdom
Rep.Ireland
Slovenia
Belgium
Germany
Sweden
Portugal
Spain
Finland
Greece
Hungary
Denmark
Romania
Latvia
CzechRepublic
Cyprus
Lithuania
Italy
Estonia
Croatia
Poland
Slovakia
Bulgaria
chargers/1000capita
Charger density
Input parameters for current policy scenario
Best practice case Best practice case

8. CTI Model upgrade COP 238 16/11/2017
Resulting incentive factor at the MS level and total EU EV uptake show
potential for improvements
Incentive factor across all EU MS
(and Norway for consistency check)
Average outcome for EU EV uptake with
current policies (𝑭𝒊𝒏𝒄 = 31%)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Norway
France
Austria
Netherlands
Luxembourg
Malta
UnitedKingdom
Rep.Ireland
Slovenia
Belgium
Germany
Sweden
Portugal
Spain
Finland
Greece
Hungary
Denmark
Romania
Latvia
CzechRepublic
Cyprus
Lithuania
Italy
Estonia
Croatia
Poland
Slovakia
Bulgaria
Finc
Results:incentive factor
0%
10%
20%
30%
40%
50%
60%
2015 2020 2025 2030 2035 2040 2045 2050
ShareofEVsinnewvehiclessold(%)
Policy projection
Projection
1
 Analysis highlights shows lots of room for all EU MS to improve their policy
packages to reach „best practice policy“ uptake
Best practice case

9. CTI Model upgrade9
RES uptake can be modelled with an S-Curve bounded by the level of
support and the ability of the grid/market to capture high RES
penetration
Factor
defining the
ceiling
“No policy” curve based on IEA
ETP 4DS growth rates (global)
“Best practice policy” curve based
on Denmark’s historical uptake
Shareofrenewablesin
electricitygeneration
Timeline2017
Current policy curve
Factor driving
pace of growth
4

10. CTI Model upgrade10
RES support policies and target determine the “pace of growth”
Metric
Best practice policy (BPP) indicator value
Level of support from RES scheme(s) S-curve fitted to growth in elec. generation in Denmark
b/w 2009 (19.2%) and 2015 (39.2%)Long-term implications
Barriers reducing the factor
Permit granting procedures
Existence of maximum number of services around
premit granting
Siting/Zoning
Existing administrative identification of geographical
sites
4
Results

11. CTI Model upgrade11
The future readiness of the energy system determines the ceiling
Metric Best practice policy indicator value
Grid transmission and distribution
and interconnection
100 % share of GWh/d
Markets supporting integration of
variable renewables
Flexible markets and capacity mechanism in place
Demand side management (DSM)
Both demand response and independent
aggregation enabled
Storage capacities 18% of installed electricity generation capacity
4
Results

12. CTI Model upgrade12
Policy modelling results help gauge the increase of action possible
Some interesting results
@ MS level
Germany performing best
overall
UK catching up due to support
schemes in place
EU level resultsGood practice
Current policy
Preliminary results
4
2020 2030
Good
practice
36% 66%
Current
policy
31% 21%