Climate proofing the renewable electricity deployment in Europe - introducing climate variability in large energy systems models

1. Clim2Power
Climate proofing the renewable electricity
deployment in Europe - introducing climate
variability in large energy systems models
76th semi-annual ETSAP Meeting, 9-13th December 2019
Sofia G. Simões1, Gildas Siggini2, Edi Assoumou2, Filipa Amorim1 et al.
1CENSE–FCT NOVA University Lisbon; 2ARMINES CMA - Sophia Antipolis

2. Clim2power in a nutshell
Hydro, solar,
wind
availability
Power
demand
Changes in
termal and RES
power plant
operation
Concurrent
water uses
Climate
hydro-storage
acq. & storage of fossil fuels
electricity prices
dispatch constraints
operational & maintenance costs
CO2 emissions
EU ETS allowance costs
electricity trade
biodiversity, flood protection,
agriculture, transboundary
water
- next season
- ‘season’ in 2050
Optimisation of
whole energy/
power system
Objectives:
- making energy and power models respond to climate variability

3. Consortium & Coverage
Sweden: Lule älv river basin,
wind and solar power
resources and whole power
system
Germany-Austria: the
Danube river basin, wind and
solar power resources and
the German-Austrian market
zone
France: wind and
solar power
resources and the
whole power
system
Portugal: Douro
river basin, wind
and solar power
resources and
whole power
system
Climate service covers whole
interconnected European electric
system & tested/validated over 4 case-
studies
3

4. Clim2Power Pipeline
Reanalysis
COSMO REA6,
1995-2015, 1hr
(daily), 6km
Seasonal Forecasts
MPI-ESM-HR/GCFS2.0
10+ runs, 6 months
ahead, daily, 6km,
monthly updates
Climate Projections
EUROCORDEX, 11
climate models,
RCP4.5 & 8.5, 1976-
2065, daily, 12.5km
Hydrological models,
Machine Learning
Input Indicators
• Hydro capacity factors
(national)
• Wind & Solar capacity
factors (NUT2)
• % variation in demand
for space heating and
cooling in buildings
(national)
Output Indicators (national, hourly)
• % of electricity generated from RES
• g CO2/kWh
• % variation in electricity costs for final
consumers
• % usage of existing electric grid
interconnection capacity
• electricity stored in batteries and hydro
pumped storage (GWh)
• (…)
Seasonal
Long-term
2030, 2050
RCP4.5
RCP8.5
Policy 1
Policy 2
Policy 3
Policy 1
Policy 2
Policy 3
UNCERTAINTY
TIMES, Dispatch models,
Machine Learning
Electricity, space heating and
cooling demand (machine learning)

5. Clim2Power climate regions (AF!!!)
Total of 686+ regions
273 (+ 5) Portuguese
municipalities
263 NUTS2
regions for
Europa
excluding
Portugal
96 maritime
regions
(intersection of
IHO seas and EEZ
areas)
IHO: international hydrographic association, EEZ: exclusive economic zone, NUTS: Nomenclature des unités territoriales statistiques 5

6. TIMES Model: eTIMES-EU
• Spatial resolution : 29 regions considered aggregated in 8
groups
• Temporal resolution : Milestone years represented by 64 time
slices (3h step for 2 typical days and 4 seasons)
• Modelled period : 2016 -2050
• Demand for electricity from EU Reference scenario 2016
(considers increase of electricity demand due to increased
electrification of end-uses)
• interconnections are represented, calibrated with current
TYNDP2016 projects till 2030
• REF & Carbon neutrality scenarios (modelled as linear
mitigation trajectory from 2016 values till 100% below 2016
emissions in 2050)

7. Annual mean precipitation (mm)
1976-2005
% anomalies 2016-2045
RCP2.5
RCP4.5

8. Availability factor changes from
referencee
Annual AF changes in 2050 for each EU country for all climate projections
Wind offshore hydro
Wind onshore PV

9. Variation in generated electricity in ‘30 &
‘50 in Europe due to climate (diff to REF)
i) No feed-in tariffs
ii) Countries currently without NPP will not have in the future (AT. PT, GR, IT, DK, HR, NO and IS). NPPs lifetime expansion is
authorized till 2040. In DE NPP not operating after 2025;
iii) Coal plants in BE are not operating from 2017 onwards.
iv)No new coal plants to be built in AT, BE, CH,DK, FI, IE, IT, PT, UK, LT, LV, EE, LU and IS.
- Wind (2%)
+ hydro (2%)
+ nuclear
- Solar (7%)
- Biomass (5%)
(k = std/mean)
+ other RES (3%)

10. Variation in generated electricity in ‘30 & ‘50 in
some regions due to climate (diff to REF)
UK & Ireland Germany, France, Netherlands, Belgium, Switzerland
& Austria
Region / Type of RES Hydro Bioenergy Solar Wind Other RES
Alpine Peninsula (ALP) 5% 1% 0% 3% 0%
British Islands (BIS) 11% 2% 41% 0% 15%
Central East Europe (CEE) 5% 7% 1% 1% 0%
Central Western Europe (CWE) 1% 9% 2% 1% 5%
Iberian (IBE) 21% 1% 14% 11% 0%
Nordic & Eastern Nordic (NEE) 42% 3% 19% 1% 0%
Nordic & Western Nordic (NWN) 1% 4% 2% 0% 17%
South Eastern Europe (SEE) 37% 6% 24% 9% 47%
k = std/mean
in 2050
• hydro in BIS, IBE, NEE and SEE
• solar for SEE, wind for SEE, ALP and IBE
• other RES (mainly ocean-based
electricity) in BIS, IBE, SEE and NWN

11. Impact on eletricity trade by 2050

12. Summary and next steps from eTIMES_PT
[work in progress]
• % RES in 2030 varies by 12% for NEE, 10 % ALP, 6% SEE and less than 4%
for the other country groups
• changes in the 2030 carbon intensity from -23% to +12%
• change in invested amounts ranging from less 4 BEuros to more 3 BEuros
in 2030 and from less 10 BEuros to more 0.5 BEuros in 2050
• "climate-proof" some of national Carbon Neutrality Roadmap 2050 for the
power sector + national Energy & Climate plans for 2030 (higher disaggregation
turns effect of climate variability visible leading to differences in power sector portfolio)
Next steps
• Integrate variability for the remaining climate projections
• Study near-neutral scenarios
• Disaggregate VRES to the NUTS2 level (MODEL DOES NOT SOLVE!!!)
• Coupling with Dispa-SET dspatch model
12

13. Never understimate understanding each
other…
Here is the climate
data you asked forCLIMATE DATA
Wow, great! Please
put it all in here!
reanalysis
hindcast
optimisation
remapping
anomaly
EU-ETS
assimilation data
load cost-effective
dispatch
bias correction
capacity factor

14. Thank you
Project CLIM2POWER is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE),
BMWFW (AT), FCT (PT), EPA (IE), ANR (FR) with co-funding by the European Union (Grant 690462).
More on CLIM2POWER:
https://clim2power.com/
sgcs@fct.unl.pt