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Reproducing the evolution of import and export electricity price curves in Belgium, in the framework of a European power market
Introduction
• Scope of the problem
• Endogenous representation of power trade
• Exogenous approach (price-quantity curves)
o Conceptual design
o Dispatch model
o Import/export curves
o Implementation in TIMES
• Comparison
o Advantages and disadvantages of the exogenous approach
Scope of the problem
• Reproduce electricity price fluctuations
• Account for other countries’ exceeding produced power
• Better tracking of electricity import/export emissions
Why is it important to model electricity import/export in a
consistent way in a national model?
Scope of the problem
• In particular, for Belgium this is a very influent aspect
o Belgium’s interconnection (38%) is much higher than EU requirements by 2030
(15%) [a]
o More interconnection capacity is foreseen (almost doubled in 2040) [b]
Why is it important to model electricity import/export in a
consistent way in a national model?
[a] ELIA, Electricity scenarios for Belgium towards 2050, 2017
[b] ENTSO-E, TYNDP 2020 Scenario Report, 2020
Endogenous representation
A multi-regional approach
• Neighboring countries included in the model, but only for their power
sector
• Neighboring countries’ power sector:
o Power demand built exogenously
o Power plants capacity (and availability) in input, also renewables
o Possibility to invest in extra gas-based capacity (and in High
Renewable Ambition scenario, also PV + batteries)
o Same carbon price as in Belgium
• Data source: TYNDP
ELIA, Electricity scenarios for Belgium towards 2050, 2017
Installed capacity evolution
Endogenous representation
Behavior of the model
Endogenous representation
• Phase-out of coal would be much faster in the
neighboring countries then expected/constrained
• Consistent investment in new gas power plants in
neighboring countries
The exogenous approach: electricity import price curves
Conceptual design
Price/demand
projections
Capacity
forecasts
European-level
dispatch model
Belgium not
included
Import price-
quantity curves
Export price-
quantity curves
TIMES-BE
PSE, Impact report 2019
Model
simplifications/
assumptions
The exogenous approach: electricity import price curves
Dispatch model: assumptions and inputs
Model assumptions Capacity information Techno-economic
parameters
Cost curves method
• 56 zones
• Hourly resolution
• No transport cost
• No losses
• Price of import =
marginal
production price
• NTC between
zones → TYNDP
• Generation
capacities →
TYNDP 2020
o 2025 → National
trends scenario
o 2030-2040 →
Distributed
energy scenario
o 2050 →
Distributed
energy scenario
decarbonized
• Demand TS → TYNDP
• Renewable TS → PECD
• Climate year 2012
• Efficiency and emission
factors → TYNDP
• Storage technologies →
hydro (ROR, RES and
PHS) and batteries
• Fuels and carbon price
projections → WEO
2019 SD
• Initial run with BE to
determine storage
evolution (then fixed)
• Removal of BE, and
setting of increasing
import/export levels
in different runs →
Price-quantity curves
Input data - Imports
Neighboring countries export price curves (hourly)
Power price [€/MWh]
0 400
Input data - Exports
Neighboring countries import price curves (hourly)
Power price [€/MWh]
0 400
The new approach: electricity import price curves
• One process per each import
power production technology
(from the dispatch model)
• Price changing in each period
The implementation in the model
0
50
100
150
200
250
300
350
400
450
Marginal
prices
[€/MWh]
Marginal prices for import power production
2025 2030 2035 2040 2045 2050
The new approach: electricity import price curves
• Emission factors correlated to each
technology (no need to do further
assumptions)
The implementation in the model
0
50
100
150
200
250
300
Emission
factors
[kg
CO2
/GJ
el
]
Emission factors import power per production technology
The new approach: electricity import price curves
• Using the availability factors of the different import/export
technologies, we then reproduced the price-quantity curves
• Price curves have been time-sliced, obtaining →
The implementation in the model
The new approach: electricity import price curves
Power price [€/MWh]
0 400
Neighboring countries export price curves (time-sliced)
The new approach: electricity export price curves
Neighboring countries import price curves (time-sliced)
Power price [€/MWh]
0 400
Results of the model
• Advantages coming with the new approach:
o No risk of overinvestments in neighboring countries to avoid power-related
emissions in BE
o Reduced computing time
o More realistic representation, with the inclusion of more countries/zones
Comparison with the endogenous representation (1)
Results of the model
• Disadvantages of the new approach
o Endogenous effects of capacity investments in the power sector of neighboring
countries are not represented (even if the operation is regulated with the same
assumptions in the two approaches)
o Accountability of power exports-related emissions (as power production and
power exports reporting are decoupled)
Comparison with the endogenous representation (2)
Next steps
• Solve the problem of accountability power exports-related emissions
• Increase the representativeness of the TS by including the time series of
import/export prices in the TS tool
What can still be improved?
Thank you for the attention
andrea.moglianesi@vito.be

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Reproducing the evolution of import and export electricity price curves in Belgium, in the framework of a European power market

  • 2. Introduction • Scope of the problem • Endogenous representation of power trade • Exogenous approach (price-quantity curves) o Conceptual design o Dispatch model o Import/export curves o Implementation in TIMES • Comparison o Advantages and disadvantages of the exogenous approach
  • 3. Scope of the problem • Reproduce electricity price fluctuations • Account for other countries’ exceeding produced power • Better tracking of electricity import/export emissions Why is it important to model electricity import/export in a consistent way in a national model?
  • 4. Scope of the problem • In particular, for Belgium this is a very influent aspect o Belgium’s interconnection (38%) is much higher than EU requirements by 2030 (15%) [a] o More interconnection capacity is foreseen (almost doubled in 2040) [b] Why is it important to model electricity import/export in a consistent way in a national model? [a] ELIA, Electricity scenarios for Belgium towards 2050, 2017 [b] ENTSO-E, TYNDP 2020 Scenario Report, 2020
  • 5. Endogenous representation A multi-regional approach • Neighboring countries included in the model, but only for their power sector • Neighboring countries’ power sector: o Power demand built exogenously o Power plants capacity (and availability) in input, also renewables o Possibility to invest in extra gas-based capacity (and in High Renewable Ambition scenario, also PV + batteries) o Same carbon price as in Belgium • Data source: TYNDP ELIA, Electricity scenarios for Belgium towards 2050, 2017
  • 7. Behavior of the model Endogenous representation • Phase-out of coal would be much faster in the neighboring countries then expected/constrained • Consistent investment in new gas power plants in neighboring countries
  • 8. The exogenous approach: electricity import price curves Conceptual design Price/demand projections Capacity forecasts European-level dispatch model Belgium not included Import price- quantity curves Export price- quantity curves TIMES-BE PSE, Impact report 2019 Model simplifications/ assumptions
  • 9. The exogenous approach: electricity import price curves Dispatch model: assumptions and inputs Model assumptions Capacity information Techno-economic parameters Cost curves method • 56 zones • Hourly resolution • No transport cost • No losses • Price of import = marginal production price • NTC between zones → TYNDP • Generation capacities → TYNDP 2020 o 2025 → National trends scenario o 2030-2040 → Distributed energy scenario o 2050 → Distributed energy scenario decarbonized • Demand TS → TYNDP • Renewable TS → PECD • Climate year 2012 • Efficiency and emission factors → TYNDP • Storage technologies → hydro (ROR, RES and PHS) and batteries • Fuels and carbon price projections → WEO 2019 SD • Initial run with BE to determine storage evolution (then fixed) • Removal of BE, and setting of increasing import/export levels in different runs → Price-quantity curves
  • 10. Input data - Imports Neighboring countries export price curves (hourly) Power price [€/MWh] 0 400
  • 11. Input data - Exports Neighboring countries import price curves (hourly) Power price [€/MWh] 0 400
  • 12. The new approach: electricity import price curves • One process per each import power production technology (from the dispatch model) • Price changing in each period The implementation in the model 0 50 100 150 200 250 300 350 400 450 Marginal prices [€/MWh] Marginal prices for import power production 2025 2030 2035 2040 2045 2050
  • 13. The new approach: electricity import price curves • Emission factors correlated to each technology (no need to do further assumptions) The implementation in the model 0 50 100 150 200 250 300 Emission factors [kg CO2 /GJ el ] Emission factors import power per production technology
  • 14. The new approach: electricity import price curves • Using the availability factors of the different import/export technologies, we then reproduced the price-quantity curves • Price curves have been time-sliced, obtaining → The implementation in the model
  • 15. The new approach: electricity import price curves Power price [€/MWh] 0 400 Neighboring countries export price curves (time-sliced)
  • 16. The new approach: electricity export price curves Neighboring countries import price curves (time-sliced) Power price [€/MWh] 0 400
  • 17. Results of the model • Advantages coming with the new approach: o No risk of overinvestments in neighboring countries to avoid power-related emissions in BE o Reduced computing time o More realistic representation, with the inclusion of more countries/zones Comparison with the endogenous representation (1)
  • 18. Results of the model • Disadvantages of the new approach o Endogenous effects of capacity investments in the power sector of neighboring countries are not represented (even if the operation is regulated with the same assumptions in the two approaches) o Accountability of power exports-related emissions (as power production and power exports reporting are decoupled) Comparison with the endogenous representation (2)
  • 19. Next steps • Solve the problem of accountability power exports-related emissions • Increase the representativeness of the TS by including the time series of import/export prices in the TS tool What can still be improved?
  • 20. Thank you for the attention andrea.moglianesi@vito.be