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)

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

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 3Non-policy

factors 1

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

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”

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

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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

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

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Charger density

Input parameters for current policy scenario

Best practice case Best practice case

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%)

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Results: incentive factor

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2015 2020 2025 2030 2035 2040 2045 2050

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Vs

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Policy projection

Projection

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Analysis highlights shows lots of room for all EU MS to improve their policy packages to reach „best practice policy“ uptake

Best practice case

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

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of re

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Timeline2017

Current policy curve

Factor driving

pace of growth

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CTI Model upgrade10

RES support policies and target determine the “pace of growth”

MetricBest 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 proceduresExistence of maximum number of services around

premit granting

Siting/ZoningExisting administrative identification of geographical

sites

4

Results

CTI Model upgrade11

The future readiness of the energy system determines the ceiling

Metric Best practice policy indicator value

Grid transmission and distribution

and interconnection100 % share of GWh/d

Markets supporting integration of

variable renewablesFlexible 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

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

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2020 2030

Good practice

36% 66%

Current policy

31% 21%