D.2.1 Geographical scope
The Balmorel simulations are carried out over a model area which comprises the Baltic countries, the Nordic countries, Poland, Germany, the Benelux, Great Britain, Ireland, France, Switzerland, Austria, Czech Republic and Italy.
D.2.2 Power demand
Development of electricity demand is based on the ENTSO-E scenarios in the TYNDP 2018. For 2020 and 2025, the Best Estimates (BE) are used. For 2030, demand is based on the Sustainable Transition (ST) 2030 scenario. For 2050, the demand is further extrapolated from the ST 2040 scenario. As for the RE developments, the ST scenario is more in line with the BE scenarios compared to the EUCO (European Commission) scenario.
The electricity demands for future years also includes:
›
Individual heating,›
Electric vehicles,›
Electricity for district heating,›
Electricity for process heat (industry)Electricity used in district heating, for industrial heat and production and for hydrogen is determined endogenously in the model simulations.
Figure 11-2 Power demand by type in the modelled area. Part of the demand projection is subject to model optimisation and therefore a result rather than an exogenous assumption
0 500 1.000 1.500 2.000 2.500 3.000 3.500 4.000
2017 2020 2030 2050
TWh
Classic EV District heating Individual heating Industrial electrification
D.2.3 Demand flexibility
Demand flexibility (demand response) can be an important measure for integration of renewable energy in the power system. However, current experiences with demand flexibility are limited and projections are highly uncertain.
As a cautious assumption, it is assumed here, that 10% of the average nominal demand throughout the year is flexible and can be shifted in time by up to 4 hours.
This leads to a demand response capacity of 27 GW by 2050 and the option to
“store” 108 GWh. Additional demand flexibility related to electric vehicles is also included.
D.2.4 Heat demand
District heating areas with related heat demand is modelled for selected countries:
the Baltic countries, the Nordic countries, Poland and Germany.
Figure 11-3 District heating demand in the modelled area
D.2.5 Exogenous capacity
Development of the existing generation capacity is subject to uncertainty. The reason is that similar to new investment, the lifetime of existing capacities is subject to economic optimisation and thus dependent on the development of electricity prices. However, other factors also play a role, and these can be harder to reflect in the model optimisation. They include: Environmental legislation on emissions effectively ruling out older power plants; various national subsidies to support certain power plants or type of power plants due to either concerns about the security of supply or national priorities (e.g. importance of power plants for regional economy and labour), optimisation of fixed cost as a result of changing operational patterns.
The overall approach to the development of existing capacities is that known and certain phase-outs are implemented exogenously, while the remaining capacity is
0 50 100 150 200 250 300 350 400
2017 2020 2030 2050
TWh
Nordics Baltics Germany Poland
held constant, and the lifetime is subject to economic optimisation (power plants have to recover fixed cost). Wind and solar capacity have relatively low fixed operational cost and are therefore assumed to be decommissioned after the end of the technical lifetime.
D.2.6 Endogenous investments and decommissioning
The capacity in the power system develops according to the least cost optimisation of the Balmorel model. The model invests in generation capacity if it is profitable, and decommissions capacity if it is not, from a power system perspective. The model both invests and decommissions myopically, i.e. only based on the information of the given year, not taking into account estimates for the future. This applies to parameters such as fuel and CO2 prices.
›
Investments: The model invests in a technology when its projected annual revenue can cover all costs including capital costs, fixed O&M. The model investments have been allowed after 2017, the base year of the model runs.›
Decommissioning: The model decommissions a technology when the revenue can no longer recover fixed O&M. Exogenous capacity is kept constant (except if better data for expected decommissioning year is available) unless it is decommissioned by the model. The model has been allowed to decommission capacity after 2020.D.2.7 Technology costs for new investments
Table 11-1 shows the cost and efficiency assumptions for new technologies.
Technology assumptions are mainly based on the Technology Catalogue, published by Danish Transmission System operator Energinet and the Danish Energy Agency63.
63 https://ens.dk/en/our-services/projections-and-models/technology-data
Table 11-1 Costs and efficiency for model-optimised investments.
First
year
Last year
Efficiency Investment Fixed O&M
Variable O&M
% €/kW €/kW €/MWh
Coal steam turbine
2020 2029 49% 2.300 41,75 2,49
2030 2049 52% 2.255 41,75 2,49
2050 - 54% 2.142 41,75 2,49
Natural gas CCGT
2020 2029 60% 836 16,70 2,41
2030 2049 62% 826 16,70 2,41
2050 - 62% 806 16,70 2,41
Wood pellet steam turbine
2020 2029 49% 2.300 50,10 2,49
2030 2049 52% 2.255 50,10 2,49
2050 - 54% 2.142 50,10 2,49
Wood steam turbine
2020 2029 47% 2.334 66,80 2,49
2030 2049 49% 2.244 66,80 2,49
2050 - 49% 2.244 66,80 2,49
Wind Onshore
2020 2024 - 1.016 24,65 2,58
2030 2049 - 935 23,00 2,37
2050 - - 860 21,86 2,17
Wind Offshore
2020 2024 - 2.740 54,06 4,05
2030 2049 - 2.172 41,37 2,99
2050 - - 1.793 33,68 2,31
Solar PV
2020 2024 - 745 8,79 -
2030 2039 - 547 6,99 -
2050 - - 433 5,77 -
LCOE for selected technologies
For selected technologies, Figure 11-4 shows the development of the levelised costs of electricity. In the comparison, 4000 FLHs are assumed for thermal capacity. The full load hours for onshore wind is from Mid-Sweden, the offshore FLHs are from the Baltic Sea and Polish solar FLHs are used.
Figure 11-4 LCOE for selected technologies, assumed FLHs for thermal capacity: 4000. Mid- Sweden used for onshore wind FLHs, Baltic FLHs for offshore and Polish solar full-load hours used.
D.2.8 Minimum RE roll-out
A minimum level of RE roll-out towards 2030 in all modelled European countries is required in all scenarios to reflect the expected impact of national climate and energy policies and expected contributions to EU targets. The model will be able to exceed these minimums where it is profitable to do so.
The levels for 2030 ENTSO-E’s 2030 Sustainable Transition scenario (ST 2030), as a starting point for determining the minimum roll-outs per country. The table below shows the RE capacities by 2030 per country according the Sustainable Transition scenario. Offshore wind capacities will be adjusted to reflect the assumptions of the different scenarios.
0 20 40 60 80 100 120 140 160 180 200
2020 2030 2050 2020 2030 2050 2020 2030 2050 2020 2030 2050 2020 2030 2050 2020 2030 2050
Coal ST Natural gas CCGT
Biomass ST Wind Onshore
Wind Offshore
Solar PV
€/MWh
Investment Fixed O&M Variable O&M Fuel CO2
Table 11-2 Renewable energy capacities (MW) by 2030 in ENTSO-E’s Sustainable Transition scenario.
Biofuels Hydro-
pump Hydro Other RES
Solar- PV
Wind- onshore
Wind- offshore Germany 0 8.378 12.794 6.631 66.300 58.500 15.000
Denmark 1.185 0 7 700 2.939 5.596 2.905
Estonia 0 0 10 127 100 1.500 0
Finland 685 0 3.200 2.200 1.200 2.300 700
Lithuania 0 950 1.263 199 80 750 0
Latvia 0 0 1.619 295 10 300 150
Norway 0 1.115 35.817 76 400 3.330 0
Poland 0 1.488 2.446 1.756 2.430 9.200 2.250
Sweden 330 0 16.184 4.203 1.740 10.780 190
Total 2.200 11.930 73.340 16.187 75.199 92.256 21.195 Beyond 2030 no further minimum roll-out is assumed within the modelling framework and RE-investments will instead be driven by market conditions, including an increasing CO2 price.
D.2.9 RE subsidies
Until 2020, RE technologies receive subsidies for power generation. The different subsidy levels per technology type are shown in Table 11-3.
Table 11-3 Subsidy level until 2020 for RE technologies. These levels are 50% lower in Poland and Czech Republic.
Technology Subsidy level
(€/MWh)
Onshore wind 5
Offshore wind 8
Solar power 5
Solid biomass 15
Biogas 25
D.2.10 Fossil fuel and carbon prices
The value of offshore wind power in the power system is highly dependent on expected future fuel prices and the cost of emitting CO2.
The current (autumn 2018) price of EU emission allowances is around 20 €. The price of CO2 allowances does, however, not necessarily represent the actual socio- economic cost of abating CO2 emissions within the EU ETS because other measures, including policies to support renewable energy technologies and energy efficiency measures, have considerable associated cost attached to them.