Setting up a Long-Term European Electricity System Model...
Transcript of Setting up a Long-Term European Electricity System Model...
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
Setting up a Long-Term European Electricity System Model Incorporating Climate Change Effects
EERA Energy System Integration Workshop, DTU Lyngby, Denmark
3rd November 2016
Fabian Gotzens, M.Sc. PhD candidate
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 2
Contents
Motivation
Overview of Employed Models
Details of Model Coupling
Scenario Background
Preliminary Results
Outlook
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 3
Motivation
Expansion of RES develops differently according to country-specific goals and RES potentials2
Climate change might influence RES potentials + the related political goals
Policy advice is needed for the required fundamental change in energy systems
1 [EU, 2016] 2 [IRENA, 2016]
The EU sets itself ambitious energy and climate targets1 until 2030
≥ - 40% greenhouse gas emissions compared with 1990
≥ 27% of total energy consumption from renewable energy sources (RES)
≥ 27% increase in energy efficiency
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 4
Overview of Employed Models
existing, running existing, work in progress planned
Climate Effects
Integration
Model
European
electricity
system model
German energy
system model
IKARUS
German regional
electricity
system model
Cross-border electricity exchanges
Convergence Criterion: Match of Capacity Expansion
Capacity Expansion Constraints
Aggregated effects at country-specific level
Aggregated effects at regional level
How, when and where might climate change effects
impact the European electricity system?
Main Research
Question:
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 5
European Electricity System Model
TIMES Model Paradigm LP capacity expansion model
Regions European countries
Years 2010–2050
Resolution 4 seasons, 2 weekdays, 24 hrs = 192 time slices per year
Economical Parameters - Fuel Prices
- CO2 Prices
- Technology investment costs
- Fixed + variable O&M costs
Policy Parameters
- CO2 reduction targets
- RES expansion goals
Technical Parameters - Power plant database
(technologies, fuels, efficiencies decommission pathways, …)
- RES geographical potentials
- RES temporal availability factors
- Cross-border transmission capacities
- CO2 emission factors
- Demands per sector
2010
2015
2020
2025
2030
2035
2040
2045
2050
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 6
German Spatial Electricity System Model
TIMES Model Paradigm LP capacity expansion model
Regions German Regions
Years 2010–2050
Resolution 4 seasons, 2 weekdays, 24 hrs = 192 time slices per year
Economical Parameters - Fuel Prices
- CO2 Prices
- Technology investment costs
- Fixed + variable O&M costs
Policy Parameters
- CO2 reduction targets
- RES expansion goals
Technical Parameters - Power plant database
(technologies, fuels, efficiencies decommission pathways, …)
- RES geographical potentials
- RES temporal availability factors
- Cross-border transmission capacities
- CO2 emission factors
- Demands per sector
2010
2015
2020
2025
2030
2035
2040
2045
2050
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 7
Climate Effects Integration Model
• Spatial resolution 12-km pattern
• Temporal resolution 3h
• Time Horizon 2100 Solar Irradiation
• Spatial resolution 12-km pattern
• Temporal resolution 3h
• Time Horizon 2100
• Height 10 m
Near-surface windspeeds
EURO-CORDEX
Climate Data Model
- Spatial allocation of cell
pattern to countries
- Temporal disaggregation
into hourly values
- Adjustment of wind
heights via
- surface roughness
- turbine curves
- clustering
Final derivation of full load hours for wind and solar power for each region and year Possible integration of data from [Tobin et al., 2015] Planned cooperation with Institute of Geophysics and Meterology, Univ. Cologne
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
050
100150200250300350400450500
0 4 8 121620 0 4 8 121620 0 4 8 121620 0 4 8 121620
R S F W
Sup
ply
[M
W]
Season / Hour of Day
Average Wind Offshore Feed-Ins 2010-2015
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
0 4 8 12 16 20 0 4 8 12 16 20 0 4 8 12 16 20 0 4 8 12 16 20
R S F W
Season / Hour of Day
Average Wind Onshore Feed-Ins 2010-2015
Ø TransnetBW
Ø Amprion
Ø 50Hertz
Ø TenneT
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 8
Pre-analysis of Historical RES Feed-Ins
Average offshore wind feed-ins do not show a clear intra-day temporal dependence
Interesting: Average onshore wind feed-ins show o midday peaks in spring + summer o rather flat patterns in fall + winter
Spring Summer Fall Winter Spring Summer Fall Winter
Are these patterns subject to climate change? If yes, how is the impact on the electricity supply system?
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 9
German energy system model IKARUS*
Primary energy Energy conversion and transport Final consumption
Decentral CHP
Renewable energies
Nuclear fuel
Gas
Electricity
District heat
Coal
Crude oil
Fuel oils
Gasoline
Diesel & kerosene
Central CHP
Production
Housing space
Number of employees
Freight and passenger transport
Demand for raw
materials
Demand
Power plants
Transport/ distribution/
storage
Transport/ distribution/
storage
Coal import
Coal extraction
Gas import
Gas extraction
Electricity import
Nuclear fuel import
Renewable energy sources
Crude oil import
Import of other oils
Refinery
Industry
Non-energy
consump-
tion
Households
Transport
sector
Small
consumer
Transport/ distribution/
storage
Model type: Techno-economic bottom-up optimization model of the German energy system Objective function: minimizing of total system costs Model philosophy: myopic (no perfect forsight) Time horizon: until 2050 (in 5 years intervalls)
* IK
AR
US:
Inst
rum
ents
for
gree
nh
ou
se g
as r
edu
ctio
n s
trat
egie
s
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
IKARUS German Energy System Model
Inputs Outputs
Technologies (Capacities, Costs, Parameters)
Additional inst. electric capacities
Residential sector demands (bn. m² to be heated)
Levelized Cost of Electricity (LCOE)
Transport sector demands (pkm / tkm)
Electricity Demand DE
Industrial gross value added (bn. €)
etc.
Small consumer demands (mio. employees)
Energy carrier prices
Bounds: RE potentials
Bounds: Inst. electric capacities
Bounds: Im- and Exports
Detailled View into Model Coupling
10
TIMES European Electricity System Model
Inputs Outputs
Technologies DE Technologies Others
Additional electric capacities DE Additional electric capacities Oth.
Electricity Demand DE Levelized Cost of Electricity DE Levelized Cost of Electricity Oth.
Electricity Demand Others Electricity: Im- and Exports DE Electricity: Im- and Exports Oth.
Energy carrier prices
Bounds: RE Potentials DE Bounds: RE Potentials Others
etc.
Bounds: Inst. electric capacities
Bounds: Im and Exports (initially free - not bounded)
Convergence criterion:
Δ ≤ ±5%
by 2nd iteration
If violated
Fixed model inputs Data exchange Convergence Criterion
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 11
Scenario Background
• Approach: Comparison with reference scenario
Consistent scenarios for European and German model needed
• Sensitivity case study: Autarky aspects
• Which countries will be able to supply energy self-sufficiently?
• For those how could, what would be the additional costs per country?
• Which countries will –due to limited potentials– still rely on energy imports?
2010
2015
2020
2025
2030
2035
2040
2045
2050
Reference Case Usage and capacity expansion only subject to national constraints
Climate Change Cases Usage and capacity expansion additionally restricted by climate change impacts
Comparison
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 12
Prelimary Exemplary Modeling Results
0
1
2
3
4
5
6
7
8
1 5 9 131721 1 5 9 131721 1 5 9 131721 1 5 9 131721 1 5 9 131721 1 5 9 131721 1 5 9 131721 1 5 9 131721
FE FI RE RI SE SI WE WI
Ele
ctri
city
Ge
ne
rati
on
[TW
h]
Biogas CHP Coal CHP Waste CHP Biogas Run-off-River Hydro Storage
Lignite Combined Cycle Syn. Gases Wind offshore Wind onshore Waste
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 13
Finishing Model Approach and its Application
Outlook and Next Steps
Development of the climate data integration model
Modeling of further European countries
Integration of storage devices
Integration of grid features
Open Questions for Discussion
Adequate modeling of the future role of biogas?
...optimal temporal resolution across scales?
...decrease calculation time of double soft-coupling?
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
03/11/2016 Fabian Gotzens | IEK-STE, FZ Jülich, Germany 14
References Slide Source
3 EU 2030 Energy & Climate Framework http://ec.europa.eu/clima/policies/strategies/2030/index_en.htm Renewable Expansion Data IRENA (2016), Renewable Energy Statistics 2016, The International Renewable Energy Agency, Abu Dhabi
5,6 ETSAP TIMES Loulou et al. (2005), Documentation for the TIMES Model
7 Tobin et al. (2016), Climate change impacts on the power generation potential of a European mid-century wind farms scenario
8 Wind Feed-In Data Germany http://www.50hertz.com/de/Kennzahlen/Windenergie/Archiv-Windenergie http://www.amprion.net/windenergieeinspeisung http://www.tennettso.de/site/Transparenz/veroeffentlichungen/netzkennzahlen/tatsaechliche-und-prognostizierte-windenergieeinspeisung https://www.transnetbw.de/de/kennzahlen/erneuerbare-energien/windenergie Picture TSOs https://upload.wikimedia.org/wikipedia/commons/thumb/1/17/Regelzonen_deutscher_%C3%9Cbertragungsnetzbetreiber_neu.png/200px-Regelzonen_deutscher_%C3%9Cbertragungsnetzbetreiber_neu.png
9 Heinrichs et al. (2015), IKARUS – a German energy system model, IEK-STE, FZ Jülich
Mitg
lie
d d
er
He
lmh
oltz-G
em
ein
sch
aft
Setting up a Long-Term European Electricity System Model Incorporating Climate Change Effects
EERA Energy System Integration Workshop, DTU Lyngby, Denmark
3rd November 2016
Fabian Gotzens, M.Sc. PhD candidate