Case Study 3: Assessing Feasibility of Scenarios, cost of ...
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This project has received funding from the EuropeanUnion’s Horizon 2020 research and innovationprogramme under grant agreement No 773897
Case Study 3: Assessing Feasibility of Scenarios, cost of Renewable integration and value of flexibilities for the European electricity system
by S. Charousset, 20 May ’21;
Joint work of:• Wim van Ackooij, Sandie Balaguer, Sandrine
Charousset, Dominique Daniel, Laurent Dubus, Yohan Moreau, Slimane Noceir, Nadia Oudjane, Felix Trieu (EDF)
• Antonio Frangioni, Rafael Lobato, Ali Ghezelsoflu, Nicollo Iardella (Pisa)
• Utz-Uwe Haus, Alfio Lazzaro (HPE)
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❑ The objective of this case study is to assess the plan4res tool’s ability
to capture
▪ The feasibil ity of a given (external) Scenario for the electricity system
➢With uncertaint ies
➢ Taking into account technical const raints, including dynamic robustness
▪ The Impact of different levels of RES integration on the European system
costs ➢ Electr ic i ty generat ion cost
➢Cost to ensure the dynamic robustness of the system (Reserves, Inert ia )
▪ The Value of different f lexibil ity services: system cost reduction coming
from using the flexibil ity potentials of the different system assets.➢ Examples f rom
o S t o r a ge
o I n t e r c onnec t ions
o T h e r mal g e n e r a t io n
CS3 - Objectives
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❑ Case study 3 focuses on the Pan-European electricity sector in 2050
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CS3 - Methodology
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Multi modal investmentGeneration
mix and demand
(2050) fromCS1
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Transmission Expansion
Transmission capacity(2050)
from CS2
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CapacityExpansion
ModelAdapts
generation mix
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SeasonalStorage
ValuationComputes
strategies for all seasonal storages
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European Unit Commitment
Computesoperational
scheduls and costs
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External ScenarioGeneration mix and demand for a given
year
1/2
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Scenario : openENTRANCE technoFriendly 1.0
❑ Power Sector:▪Decarbonized
▪ Steady increase of Wind and PV
▪ Significant reductionof Fossil (oil & gas)
▪CCS
❑ Demand:▪ Electrification of heat
▪Reduction of gas
▪ Increase of electransport Source: openEntrance D3.1, D7.1
www.openentrance.eu
Electricity Generation (TWh)
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Climatic data: Copernicus C3S Energy
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❑ Scenarised hourly time series over 1 year for:
▪ Electricity demand per region
▪ Load factors per region:
➢PV Power
➢Onshore WindPower
➢Offshore WindPower
▪ Inflows to reservoirs per countries
https://climate.copernicus.eu/operational-service-energy-sector
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The dataset used
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❑ openENTRANCE technoFriendly 1.0, 2030
Installed electricityGeneration mix
Regions :• France• Germany• Italy• Switzerland• Benelux• Iberia= Spain+Portugal• Britain= United Kingdom + Ireland• Eastern Europe= Austria+Czech
Republic+Hungary+Poland+Slovakia• Benelux = Belgium+Luxembourg+Netherlands• Baltics = Estonia+Latvia+Lithuania• Scandinavia= Denmark+Finland+Sweden+Norway• Balkans= Non EU
Balkans+Bulgaria+Croatia+Greece+Romania+Slovenia
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First Step: Generation mix Adaptation
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Non served electricity per country / climatic scenario
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Scenario Assessment
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Marginal Costs of ElectricityFrom Jul 1 to June 30
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France Germany Italy
Switzerland Eastern Europe Benelux
Iberia Britain Balkans
Baltics Scandinavia
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Storage in Hydro (Aggregated) ReservoirsFrom Jul 1 to June 30
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France
Iberia
Balkans
Scandinavia
Italy
Switzerland
Eastern Europe
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Electricity generation (1 scenario)
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Hourly Electricity demand over 1 year (1 scenario)rom Jul 1 to June 30
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Electricity Generation and interconnections (1 scenario)
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Aggregated Exchanges over the year
Co
ntr
ibu
tio
n o
f te
chn
olo
gies
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Hourly Profiles for specific weeks
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Winter Week Summer WeekSpring Week
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Value of Flexibilities
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Interconnections
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❑ Interco Capacities reduced by 10 & 25% or increased by 10%
Impact on generation per technologyImpact on operation cost
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Battery Storage
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❑ Battery Capacities reduced by 10 & 25% or increased by 10% or 25%
Impact on generation per technology
Impact on operation cost
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Nuclear generation
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❑ Nuclear flexibi lity in 1 Country increased/decreased (MinPower, Ramping, Min Durations On/Off)
Impact on generation per technology
Impact on operation cost
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Impact of hosting various sharesof Renewable Energy
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VRE Scenarios : Installed Capacity
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From 57 to 81% Variable RenewableGeneration (Wind and PV power) in the electricity generation mix
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VRE Scenarios: generation
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VRE Curtailement
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Costs
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Conclusion
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❑ The models are able to evaluate the feasibility of a given
long-term energy mix scenario, and to assess the costs of
this scenario from the point of view of the electricity system.
❑ It is possible to run flexibility assessment studies, in order to
evaluate the value of a given kind of flexibility.
❑ Finally we demonstrated that the models were able to
capture the cost and value of hosting more Variable
renewable Generation Systems in the electricity mix.
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Thank you for attendanceQuestions to Case Study 3
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Sandrine [email protected]
Wim van Ackooij
Sandie Balaguer
Dominique Daniel
Slimane Noceir
Nadia Oudjane