How to strengthen the EU NDC? Understanding the impact of sector-based policies - COP 23
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Transcript of How to strengthen the EU NDC? Understanding the impact of sector-based policies - COP 23
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
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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
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
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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rway
Fran
ceA
ust
ria
Net
her
lan
ds
Luxe
mb
ourg
Mal
taU
nit
ed K
ingd
om
Rep
. Ire
lan
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oven
iaB
elgi
um
Ger
man
ySw
eden
Port
uga
lSp
ain
Finl
and
Gre
ece
Hu
ngar
yD
enm
ark
Ro
man
iaLa
tvia
Cze
ch R
epu
blic
Cyp
rus
Lith
uan
iaIt
aly
Esto
nia
Cro
atia
Pola
nd
Slov
akia
Bu
lgar
ia
char
gers
/ 1
00
0 c
apit
a
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%)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
No
rwa
y
Fra
nce
Au
stri
a
Ne
the
rla
nd
s
Lux
em
bo
urg
Ma
lta
Un
ite
d K
ing
do
m
Rep
. Ir
ela
nd
Slo
ven
ia
Be
lgiu
m
Ge
rma
ny
Sw
ed
en
Po
rtu
gal
Sp
ain
Fin
lan
d
Gre
ece
Hu
ng
ary
De
nm
ark
Ro
ma
nia
Latv
ia
Cze
ch R
ep
ub
lic
Cy
pru
s
Lith
ua
nia
Ita
ly
Est
on
ia
Cro
ati
a
Po
lan
d
Slo
vaki
a
Bu
lga
ria
Fin
c
Results: incentive factor
0%
10%
20%
30%
40%
50%
60%
2015 2020 2025 2030 2035 2040 2045 2050
Sha
re o
f E
Vs
in n
ew
ve
hic
les
sold
(%
)
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
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
Sh
are
of re
ne
wa
ble
s in
ele
ctr
icity g
en
era
tio
n
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
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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
4
2020 2030
Good practice
36% 66%
Current policy
31% 21%