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Analysis of the role ofenergy storages in Germany with TIMES PanEU – methodologyand results
ETSAP Workshop MadridJulia Welsch, Markus Blesl
JuliaWelsch
17.11.2016 2
Outline
Introduction
Methodology
1
2
3
4
Scenario analysis
Conclusions and outlook
17.11.2016 3
Outline
Introduction
Methodology
1
2
3
4
Scenario analysis
Conclusions and outlook
Motivation:
• Political induced increase of share of renewables
• Increasingly feed in of electricity from variable renewables (wind and pv)
Occurance of a strongly fluctuating negative residual load
Increased need for flexibility options to balance supply and demand of electricity
Objective:
• Methodological improvements of the energy system model TIMES PanEU
regarding to the temporal resolution and the modelling of energy storages
• Determination of the optimal configuration of energy storages and power-to-x
under minimizing the overall system cost
• Including ESTMAP database for storages
• Analysis of the role of electricity storages within the ESTMAP project
17.11.2016 4
Introduction
Energy system model TIMES PanEU:
• Linear optimization model
• 30 regions (EU-28, NO, CH)
• Horizon: 2010 to 2050
• Whole energy system, from
energy supply to energy service
demand
17.11.2016 5
TIMES PanEU
Model improvement for modelling storages:
• Creation of methodologial extensions for modelling and analysis of energy storages
• Increase of the temporal resolution for Germany
• The high temporal resolution is based on representative, coherent and successive time segments
• Modelling of energy storages and power-to-x for Germany and Europe in TIMES PanEUResearch focus:Integrated consideration of options in the sectors of electricity, heat and mobility over the optimization period taking into account sector coupling through the use of Power-to-Heat, Power-to-Gas and electric mobility
Supply of districtheat and electricity
Power-to-Heat
Power-to-Gas
Electricity Storage
Heat Storage
Gas Storage
Supply ofenergy sources
IndustryAutoproducer
CommercialAutoproducer
HouseholdsBattery
Night StoragePower-to-HeatHeat Storage
TransportElectric mobility
Ene
rgyse
rviced
em
andEn
erg
yso
urc
ep
rice
s,re
sso
urc
eav
aila
bili
ty
Agriculture
Demand
Other energyconversion
17.11.2016 6
Outline
Introduction
Methodology
1
2
3
4
Scenario analysis
Conclusions and outlook
17.11.2016 7
Increase of the temporal resolution for Germany
Methodology: Temporal resolution in TIMES PanEU
RD
R
RP
RN
Milestoneyear
S F W
SD SP SN FD FP FN WD
WP
WN
Season
Weekly
Annual
Daynite
RS1
01
R
…
RS1
56
Milestoneyear
S F W
SS1
01
…
SS1
56
FS1
01
…
FS1
56
WS1
01
…
WS1
56
FP
FPS1
01
…
FPS1
56
Coupling of timeslice trees for modelling trade Integral optimization over all regions and modelling periods
Germany:
• 280 time segments:• One typical week per season with three-
hourly-resolution (224 time segments)• One additional week for representing high
feed of variable renewable energies (56 time segments)
• Representative, coherent times segments
TIMES PanEU
• 12 time segments per year (one typical day per season withthree time steps)
• No coherent temporal resolution
17.11.2016 8
Demand structure exemplary for households
Methodology: Temporal resolution in TIMES PanEU
0
10
20
30
Refrigeration Washing machine
Cloth drying Dishwasher
Cooking Lighting
Other
Gas Cooker
Electric Hot Water
ElektricHeating
Electric Cooker
…
0
5Demand for Hot Water
0
5
10Demand for Space Heat
0
10
20Demand for Cooking
Demand for electricity of households
GW
Electricity demand and electricity
load profile are results of the
optimization and change depending
on the used application technologies
Sector couplingElectricity production
17.11.2016 9
Methodology: Flexibility options in TIMES PanEU
Power-to-Gas
Electric vehicles
H2, Biogas
Electricity storagePump storageDiabatic CAESAdiabatic CAESStationary battery storage
GridHeat marketPower-to-Heat
MobilityMobile battery storage
GasPower-to-Gas
Flexibility options in theelectricty sector
DSM
Curtailment
Changed electricitydemand
Conventionalpower plantsCoalGasOilNuclear
Renewablepower plantsWindPVGeothermal SolarthermalBiomasHydro
CHPrenewable/conventional
GridPower-to-Heat
Electricity tradebetween countries
Changed electricitydemand in Europe
Heat storage
Natural gas storageHydrogen storageGas grid as storage
17.11.2016 10
Modelling of storages as a sequence of three processes
Methodology: Modelling of energy storages in TIMES PanEU
Storage content and storage power are endogenous optimziation results
InputProcess
Capacity: Power (GW)
Storageprocess
Capacity: Energyamount (PJ)
Outputprocess
Capacity: Power (GW)
17.11.2016 11
Interface ESTMAP storage database – TIMES PanEU/TIMES regional models
EXCEL database analysis input deck Creation of Pivot Tables in EXCEL
Integration of data in TIMES
Database and GIS mapping
Technical/economical characterization
Potentials
17.11.2016 12
Interface TIMES regional models – PowerFys
TIMESEnergy system
modelling
PowerFysElectrcity market
modelling
• Capacities of power and CHP plants
• Electricity and heat production of power and CHP plants
• Fuel input in power and CHP plants
• Emissions
• Electricity trade (capacities and amounts)
• Capacities of electrcity storages
• Electrcity demand by sector
17.11.2016 13
Outline
Introduction
Methodology
1
2
3
4
Scenario analysis
Conclusions and outlook
17.11.2016 14
Scenario definition
Scenario analysis from the ESTMAP project
Scenario assumptions
2030 2050
Base MorePVBattery
CostBase MorePV
Battery
Cost
GHG reduction in the EU
(vs. 1990)40 % 90 %
Renewables at electricity
consumption in the EU30 % 80 %
Renewables at gross final
energy consumption in the EU27 % 75 %
PV Capacity in Europe 120 GW 180 GW 120 GW 364 GW 546 GW 364 GW
PV Capacity in Germany 58 GW 87 GW 58 GW 70 GW 105 GW 70 GW
17.11.2016 15
Electricity production by energy carrier in Germany
Scenario analysis from the ESTMAP project
-100
0
100
200
300
400
500
600
700
Sta
tsiti
cs
Base
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
2010 2015 2020 2025 2030 2035 2040 2045 2050
Electricity storage(excl. pump storage)Net Imports
Others / Waste non-ren.Other Renewables
Biomass / Wasteren.Solar
Wind offshore
Wind onshore
Hydro incl. pumpstorageNuclear
Gas CCS
Gas w/o CCS
Oil
Lignite CCS
Lignite w/o CCS
Coal CCS
Coal w/o CCS
Net electricity
TWh
• Electrification of the energy
system until the year 2050
(achieve GHG emission targets)
• Electrification enables
integration of variable renewable
energies
• Other energy carriers can be
substituted
• With nuclear phase-out in the
year 2025 wind turbines are
increasingly used to achieve the
share of renewables
• From the year 2035 additional
lignite CCS power plants enter
the market (reduction of GHG
emissions)
17.11.2016 16
Capacities in Germany
Scenario analysis from the ESTMAP project
0
50
100
150
200
250
300
350
Sta
tsitic
s
Base
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batte
ryC
ost
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
2010 2015 2020 2025 2030 2035 2040 2045 2050
Electricity storage(excl. pumpstorage)Others / Wastenon-ren.
Other Renewables
Biomass / Wasteren.
Solar
Wind
Hydro incl. pumpstorage
Nuclear
Natural gas
Oil
Lignite
Coal
Capacity
GW
• Increase of the
capacities is higher
than the increase of
the overall electricity
production
• Lower full load hours
of pv and wind plants
17.11.2016 17
Electricity storages in Germany
Scenario analysis from the ESTMAP project
0
5
10
15
20
25
Sta
tistics
Base
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
2010 2015 2020 2025 2030 2035 2040 2045 2050
Battery stationary RedoxFlow
Battery stationary LeadAcid
Battery stationaryLithium Ion
CAES adiabatic cavern
CAES adiabatic tank
CAES diabatic cavern
Pump Storage
Storage input capacity
GW
0
5
10
15
20
25
30
Sta
tistics
Base
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
Base
Mo
reP
V
Batt
ery
Co
st
20102015 2020 2025 2030 2035 2040 2045 2050
Battery stationary RedoxFlow
Battery stationary Lead Acid
Battery stationary LithiumIon
CAES adiabatic cavern
CAES adiabatic tank
CAES diabatic cavern
Pump Storage
Storage output capacity
GW
• The increased
fluctuating supply of
electricity from wind
and pv systems leads to
a higher flexibility need
in the whole energy
system
• Therefore new
electricity storages
(especially stationary
lithium ion batteries in
combination with pv)
are built from the year
2045 onwards in
Germany
17.11.2016 18
Electricity storages in Germany
Scenario analysis from the ESTMAP project
0
30
60
90
120
150
180
Sta
tistics
Base
Base
Mo
reP
VB
att
ery
Co
st
Base
Mo
reP
VB
att
ery
Co
st
Base
Mo
reP
VB
att
ery
Co
st
Base
Mo
reP
VB
att
ery
Co
st
Base
Mo
reP
VB
att
ery
Co
st
Base
Mo
reP
VB
att
ery
Co
st
Base
Mo
reP
VB
att
ery
Co
st
20102015 2020 2025 2030 2035 2040 2045 2050
Battery stationary RedoxFlow
Battery stationary LeadAcid
Battery stationary LithiumIon
CAES adiabatic cavern
CAES adiabatic tank
CAES diabatic cavern
Pump Storage
Storage content
GWh
It can be seen, that the ratio of storage content and power is lower for the battery storage than for the pump storage. This is due to the lower content-specific investment costs with higher power-specific investments of pumped storage.
0
20
40
60
80
100
120
140
160
180
200
2010 2015 2020 2025 2030 2035 2040 2045 2050
Stored electricity
Electricity electric cars
Increased electricity demand
Decreased electricity demand
Load shifting in time segment with negativeresidual loadCurtailment in time segments with negativeresidual loadNet export in time segments with negativeresidual loadElectricity Power-to-Gas in time segmentswith negative residual loadElectricity Power-to-Heat in time segmentswith negative residual load
17.11.2016 19
Flexibilisation of electricity in Germany for the MorePV scenario
Scenario analysis from the ESTMAP project
TWh
Flexibilisation
• In order to achieve a high share of renewables in electricity consumption in Germany, less curtailment is used in 2050
• The amount of electricity which is not curtailed is instead stored in electricity storage or used by Power-to-Heat or Power-to-Gas installations (sector coupling)
17.11.2016 20
Outline
Introduction
Methodology: Temporal resolution and modelling of storages in TIMES PanEU
1
2
3
4
Scenario analysis
Conclusions and outlook
17.11.2016 21
Conclusions and outlook
Conclusions:
• Comparing the results for Germany to the ones from the TIMES PanEU model it can be seen, that a big part of new energy storages in Europe are built in Germany.
• This results are not only attributable to the amount of potential storage sites from the ESTMAP database, but also due to the model design with a higher temporal resolution only of the German region.
• With a lower temporal resolution the storage need in the energy system is generally underestimated. The high flexibility need, which results from peaks and valleys of PV and wind production, cannot be mapped adequately in a model with a temporal resolution of only a few typical days.
• New storages after 2040, other flexibility options are important model components
Outlook:
• Outcomes of energy system analysis depend on storage technology parameters, such as cost projections, so that a sensitivity analysis could be useful
• Higher temporal resolution for other countries – model handling
Thank you!
Phone +49 (0) 711 685-
Fax +49 (0) 711 685-
University of Stuttgart
Heßbrühlstraße 49a
70565 Stuttgart
Germany
Julia Welsch
87848
87873
Institute for Energy Economics and the
Rational Use of Energy (IER)
