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How fusion power can contribute to a fully decarbonized European power mix after 2050
Fusion Engineering and Design 146 (2019) 2189–2193
Contents lists available at ScienceDirect
Fusion Engineering and Design journal homepage: www.elsevier.com/locate/fusengdes
How fusion power can contribute to a fully decarbonized European power mix after 2050 C. Bustreoa,b, U. Giuliania,b, D. Maggioa,b, G. Zollinoa,b, a b
T
⁎
Consorzio RFX (CNR, ENEA, INFN, Università di Padova, Acciaierie Venete SpA), Corso Stati Uniti 4, 35127 Padova, Italy University of Padova, Department of Industrial Engineering, via Gradenigo 6a, 35131, Padova, Italy
ARTICLE INFO
ABSTRACT
Keywords: European energy scenarios Cost of electricity Fusion electricity
In the second half of this century, the European energy mix will be very likely completely decarbonized. Two main options are available to generate carbon free electricity: either to rely on renewable energy sources only, or to integrate renewables with a new generation of nuclear power plant, e.g. fusion power plant. In the former case a large storage capacity and/or dispatchable generation are required to compensate for the variable electricity generation. The size of the necessary storage systems and dispatchable power plants can be reduced if a baseload carbon free power technology is available, such as fusion. These options are analysed in this paper with the CO.ME.S.E. (COsto MEdio del Sistema Elettrico – Electric System Average Cost) code that assesses the hourly balance between load and generation, through a simplified dispatch model and the system costs, through a stochastic economic analysis. Two sets of power generation scenarios are considered in typical North and SouthEurope cases. The study gives key indications to make fusion a cost-effective ingredient of a future European decarbonized power mix.
1. Introduction According to the current international pledges on climate change, de-carbonization of the energy systems is a must, almost worldwide. The European Union has adopted an Energy Roadmap to 2050, setting an 80% reduction in energy related greenhouse gas emission below 1990 levels by 2050, which cannot be achieved but with a 95%–100% decarbonized power sector [1]. Hence, the European electricity generation mix of the second part of this century will be composed by carbon free technologies only: fossil fuel power plants plus CCS (Carbon Capture and Storage), nuclear power plants, renewable technologies. As for nuclear power, besides nuclear fission generation III + and IV reactors, also fusion power plants could contribute [2]. This paper provides a range of scenarios (see Table 1) in order to estimate to what extent fusion power will be able to enter the scene in Europe together with renewable energy sources (RES) by the last two decades of this century. Due to the high share of variable renewable energy the actual feasibility of each scenario must be assessed. To this aim, the generation profile is studied with a one-hour time resolution over a one-year timeframe and the energy storage and dispatchable generation capacity necessary to compensate the variable generation from renewable energy sources are estimated. In addition to the power generation mix technical feasibility, the scenarios here presented are used to assess the ⁎
costs of each choice and try to answer the question whether a carbon free power mix with fusion would be less expensive and more affordable - e.g. in terms of soil consumption - than a power mix without fusion. 2. The COMESE code The CO.ME.S.E. (COsto MEdio del Sistema Elettrico - Electric System Average Cost) code [3] is able to find the needs for power generation, storage and back-up capacity of power system scenarios, which are necessary to assure power dispatch on an hourly base, and perform economic analyses. A zero-dimensional network model is adopted, i.e. all generators, storage systems and loads are connected to the same node (the so called “copper plate” assumption). Power generation scenarios are at first arranged so as to cover annual demand and fulfill specific policy objectives, such as de-carbonization, specific technology targets or ban, etc. Then the actual feasibility of each mix is checked through the analysis of the hourly balance of power generation and demand whose profiles reflects historical database. Dispatchable technologies, such as dam hydropower and biomass and biogas power generation, and storage systems, such as pumped hydro plants and batteries, are included in each power mix, in order to manage surplus (over-generation) and deficit (under-generation) events, due to variable
Corresponding author at: Consorzio RFX (CNR, ENEA, INFN, Università di Padova, Acciaierie Venete SpA), Corso Stati Uniti 4, 35127 Padova, Italy. E-mail address: [email protected] (G. Zollino).
https://doi.org/10.1016/j.fusengdes.2019.03.150 Received 9 October 2018; Received in revised form 20 March 2019; Accepted 22 March 2019 Available online 04 April 2019 0920-3796/ © 2019 Elsevier B.V. All rights reserved.
Fusion Engineering and Design 146 (2019) 2189–2193
C. Bustreo, et al.
Table 1 Key parameters of the power generation scenarios, all with 600 TW h demand. South Europe
North Europe
100%-RES
Photovoltaic
Residential roof Commercial roof Utility scale on shore near shore off shore Run of River Hydro Geothermal Municipal Waste
Wind Baseload Generation Fusion Dispatchable Generation Total generation Curtailed Energy Storage Roundtrip losses
Fusion Baseload
Fusion 2 Seasons
100% RES
Fusion Baseload
[GW]
[TWh]
[GW]
[TWh]
[GW]
[TWh]
[GW]
[TWh]
[GW]
[TWh]
230 60 160 23 2
280 70 240 45 5
63 16 44 23 2
76 19 67 45 5
78 20 55 23 2
94 24 82 45 5
13
11
13
11
12
30
12
30
8 1 1
35 8 7
8 1 1 37 13 22
35 8 7 260 31* 62* 614 7 0.1 0.4 7
8 1 1 37 13 15
35 8 7 260 31* 31* 622 11 0.1 0.5 11
170 1.9
640 6
75 1.9
290 6
1
8
1 37
8 260
40
41* 736 124 0.05 1 12
39
40* 645 41 0.05 0.4 4
Dam Hydro Bioenergy
13 28
Pumped Hydro Batteries
9 150
*
29 50* 769 130 0.1 1.2 39
9 50
9 62
3 125
3 50
* According to the hourly simulation results.
and un-programmable energy sources, and guarantee load balance. In particular, during peak under-generation event, the missing power is provided by dispatchable generators plus storage devices, preloaded by the same dispatchable generators. The size of dispatchable power plants and storage systems, including the possibility of curtailment, are determined through an iterative approach which minimize their contribution to cost of electricity, as defined below. Once the contribution of all technologies to the hourly power generation is assessed, the capacity factor of dispatchable generators is determined and the average Levelised Cost of Timely Electricity (LCOTE) is calculated. Provided that Np different kinds of power plants are generating electricity and storage systems are involved, the LCOTE is calculated as follows: Np i=1
LCOTE =
power plants in Europe by 2080 is assumed in favor of a wide fusion power deployment. Two cases are proposed: “South-Europe”, with a predominant solar generation and “North-Europe”, largely based on wind power, reflecting the actual potentials of these renewable energy sources in Europe, in line with scenarios proposed at EU level [1]. Indeed, among renewable energy, solar and wind are the most promising in terms of electricity generation potential and technology maturity, as shown by the impressive tariff reductions recently registered in national auctions. For all the scenarios, geothermal, run of river hydro and municipal waste power generation are assumed to provide base-load generation and are set to their maximum estimated potentials. As for solar and wind generation, the actual hourly profiles recorded by the national TSO in 2015 (year 2015 is arbitrary chosen), are taken into account. In order to simplify the analysis, although electricity demand is assumed to growth to 600 TW h/year, due to the electrification of new energy sectors (e.g. transport and space heating), the same hourly profiles recorded by TSOs in 2015 are considered, without any demand response effect.
(LCOEi × Ei ) + Cstor Eload
where LCOEi is the well known levelized lifetime average cost of electricity generated by the i–th technology, Ei and Eload are the electricity generated by the i–th technology and the annual electricity demand, respectively. Cstor is the annual cost of energy storage systems, which is computed as follows:
Cstor =
s
Is
r )ns
r (1 + (1 + r )ns
1
3.1. South-Europe scenarios Italy is chosen as reference Country for the analysis of a future South-Europe power generation mix and three scenarios are simulated: a) 100%-RES, without any fusion contribution; b) fusion-baseload, where fusion power plants generate 260 TW h at 30 GW constant power; i.e. 37 GW installed capacity with 80% availability [5]; c) fusion-two-seasons, where fusion still generate 260 TW h, but at 25 GW power in the six months when solar radiation is higher (i.e. from April to September) and at 35 GW power during the rest of the year. In all the scenarios, base load generation supplies 50 TW and wind farms (mostly on-shore, with a small contribution of near-shore plants) generate 50 TWh [6]. In the 100%-RES scenario, 450 GW PV capacity must be installed, generating 590 TW h, in addition to the 100 TW h coming from base-load and wind plants. However, due to wind and PV variability, 690 TW h is not enough to satisfy the 600 TW h demand. In fact, over-generation occurs for more than 3000 h and under-generation for 5700 h (Fig. 1). Thus, in order to guarantee that power demand be covered hour by hour, dispatchable energy must be added, together with pumped-hydro and battery storage systems. In Table 1, the optimal arrangement (i.e. that giving the lowest cost of electricity) of dispatchable generators (41 GW/79 TW h), pumped-
+ O &Ms
where Is is the investment costs (Eur) of a storage technology (pumpedhydro or batteries), O&Ms its annual average O&M costs (Eur/years), ns its expected lifetime (years) and r the lifetime average discount rate. As indicated in Table 2, for each technology, investment and O&M costs, fuel cost and lifetime are varied within a range chosen according to the most recent learning factor estimations to technology maturity [4]; once probability distribution are assigned, Montecarlo analyses can be performed. It is worth noting that, due to the copper plate assumption, the LCOTE doesn’t account for investment and O&M costs necessary to cope with electric grid enhancements requested to manage overgeneration events. 3. Energy scenarios Possible decarbonized power generation mixes in Europe are studied, referring to the second half of this century (indicatively 2080 and beyond). CCS technologies are deliberately not included in the scenarios. With regards to nuclear power, a complete phase-out of fission 2190
Fusion Engineering and Design 146 (2019) 2189–2193
C. Bustreo, et al.
Table 2 Technical and economic parameters of power generation and storage technologies. Overnight cost [€/kW]
O&M costs
Lifetime [years]
FIXED [€/kW y] Photovoltaic Wind
Residential roof Commercial roof Utility-tracking on shore near shore off shore Run of River
Hydro Geothermal Municipal Waste* (η = 30%) Fusion Dispatchable Energy Dam Hydro Bioenergy** (η = 33%) Storage Pumped Hydro (η = 80%) Batteries (η = 85%)
1000 ± 15% 800 ± 15% 800 ± 15% 1100 ± 20% 2100 ± 20% 1800 ± 20% 3000 ± 40% 3500 ± 15% 4500 ± 20% 6000 ± 30% 2500 ± 40% 3000 ± 20% 1500 ± 40% 750 ± 20% (8 h storage)
VAR. [€/MWh]
20 ± 15% 20 ± 12% 20 ± 15% 20 ± 30% 30 ± 30% 50 ± 30% 80 ± 30% 80 ± 25% 130 ± 25% 110 50 ± 30% 100 ± 25% 20 ± 25% 8 ± 20%
5 30 5 8
25 ± 15% 25 ± 15% 25 ± 15% 25 ± 15% 25 ± 15% 25 ± 15% 60 ± 10% 30 ± 15% 25 ± 15% 60 60 ± 10% 15 + 35% 60 ± 10% 10 ± 25%
Load hours
LCOE [c€/kWh]
North
South
North
South
800 800 1100 2500
1200 1200 1500 1900 2200
11.5 9.7 7.1 4
7.7 6.5 5.2 5.3 8.3
3800 3200 7800 7800 7000
4500 7800 7800 7000 2500 1000 – 3000***
4.7 8 4.3 0 6.3 50-24
6 4.3 0 6.3 8
* Fuel cost is assumed as negative at -80Eur/ton; **Fuel cost at 100 Eur/ton; *** According to the hourly simulation results.
Fig. 1. Duration curves of load and PV + Wind generation (left), under-generation and over-generation (center), dispatchable energy and storage output (right) for the 100%-RES scenarios in South-Europe and North-Europe.
95% and 82% respectively. Finally, in the fusion-two-seasons scenario, the installed PV capacity is slightly higher than in the fusion-baseload scenario (153 GW, generating 200 TW h), but the optimal arrangement for dispatchable energy and storage is even more favorable: -21% dispatchable energy and capacity than in 100%-RES; 9 GW/0.1 TW h pumped-hydro and 62 GW/0.5 TW h battery storage, with 11 TW h curtailed energy and 11 TW h losses due to the battery efficiency. 3.2. North-Europe scenarios United Kingdom is chosen as reference Country for the analysis of a future North-Europe power generation mix and only two scenarios are considered because of no evident seasonal change in wind generation: a) 100%-RES; b) fusion-baseload, with the same fusion contribution as for South-Europe scenarios. In both scenarios, base load generation, provided by run of river hydro and municipal waste power plants, supplies 14 TW h and 13 GW PV plants are installed on residential roofs only, generating 11 TW h [7]. As for wind generation, in both scenarios 12 GW on-shore wind capacity is installed, supplying 30 TW h. In the 100%-RES scenario, most of the electricity is generated by off-shore wind farms: in fact, 170 GW must be installed (within the estimated potential [8]), generating 640 TW h, in addition to the 52 TW h coming from base-load, PV and on-shore wind plants. However, due to the predominant contribution of variable energy source, such as wind energy, 692 TW h are not enough to satisfy the 600 TW h demand. In fact, over-generation occurs for 5000 h and under-generation for 4000 h (Fig. 1). Thus, also in this case, dispatchable energy must be added (40 GW/41 TW h), together with energy storage systems (3 GW/ 0.05 TW h pumped-hydro which is the maximum UK potential and 125 GW/1 TW h battery storage). In the fusion-baseload scenario, the
Fig. 2. Breakdown of the LCOTE when all cost parameters are set at their middle value.
hydro (9 GW/0.1 TW h which is the maximum Italian potential) and battery storage (150 GW/1.2 TW h) are given. In the fusion-baseload scenario, the installed PV capacity is less than one third than in the 100%-RES scenario (123 GW, generating 162 TW h). As compared to the 100%-RES scenario, +17% dispatchable energy is needed but less capacity is required (−15%); as for the storage systems, the maximum Italian potential of pumped-hydro is exploited like in 100%-RES scenario but battery storage system size is reduced by 67%. Curtailed energy and energy losses due to the battery efficiency are reduced by 2191
Fusion Engineering and Design 146 (2019) 2189–2193
C. Bustreo, et al.
Fig. 3. Probability density distribution of the LCOTE.
Fig. 4. Modes of the LCOTE as a function of future fusion power plants overnight costs.
installed off-shore wind capacity is less than one half than in the 100%RES scenario, i.e. 75 GW, generating 290 TW h; the optimal arrangement for dispatchable energy is the same as in 100%-RES, but the battery storage size is reduced by 60% while the pumped-hydro potential is again exploited. Curtailed energy is reduced by 69% and losses due to the battery efficiency by 67%.
North-Europe and for the South-Europe case, the presence of fusion power plants reduces the LCOTE A sensitivity analysis has been also performed. Fig. 4 shows that fusion would be effective in reducing the LCOTE as long as its overnight costs were kept below 8500 Eur/kW in the North-Europe case and below 12,500 Eur/kW in the South-Europe case.
4. Main results
5. Conclusions
Cost analyses have been performed, as described in Section 2, to assess whether and to what extent fully decarbonized power mixes could take benefits from nuclear fusion power. Table 2 summarizes the technical and economic parameters, taken from the literature [4]; as for fusion, a steady state fusion power plant is considered, with 6000 Eur/ kW investment cost, 110 Eur/kWy O&M costs, 60 y life-time and 80% availability, which are in line with the ranges proposed by EUROfusion for “basic” commercial power plants [9] and the results of analyses carried out with the FRESCO code [10,11]. Fig. 2 shows the LCOTE recovered using the central value of all economic parameters and its breakdown among different kinds of power plants and storage. In the 100%-RES scenarios, almost one half of the LCOTE is due to dispachable energy and storage, which must face variability of renewable energy sources. Fig. 3 reports the probability density distribution of the LCOTE, as cost parameters vary as indicated in Table 2. Both for the
In a carbon-free power generation mix, likely by the end of this century, fusion would reduce the cost of electricity, in comparison with 100%-RES scenarios. This is true as long as the overnight cost of a fusion power plant will be lower than 8500 Eur/kW in the North-Europe case and lower than 12,500 Eur/kW in the South-Europe case. Actually, due to the copper plate assumption, the costs of an electric grid able to manage over-generation and storage are not taken into account; thus, the convenience of a power mix with fusion would result even higher if a detailed electric grid model were considered. In addition to cost, warnings on soil consumption, linked with hundreds GW size deployment of PV and Wind power plants, is a further issue in favour of power generation scenarios with fusion.
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References
(2007) 1524–1532. [6] Ministero dello Sviluppo Economico, Strategia Energetica Nazionale, (2017). [7] https://www.gov.uk/government/statistics/energy-trends-section-6-renewables. [8] R.J. Swart, et al., Europe’s Onshore and Offshore Wind Energy Potential: an Assessment of Environmental and Economic Constraints, European Environment Agency, 2009. [9] H. Cabal, et al., Fusion power in a future low carbon global electricity system, Energy Strategy Rev. 15 (2017) 1–8. [10] C. Bustreo, et al., The Monte Carlo approach to the economics of a DEMO-like power plant, Fusion Eng. Des. 98–99 (2015) 2108–2111. [11] C. Bustreo, et al., FRESCO, a simplified code for cost analysis of fusion power plants, Fusion Eng. Des. 88 (2013) 3141–3151.
[1] EU Coucil-General Secretariat, Working Paper 1976/2016 REV 1: Revised Technical Report on Member States Results of the EUCO Policy Scenarios, January (2017). [2] T. Donnè, et al., European Research Roadmap to the Realisation of Fusion Energy, (2018). [3] C. Bustreo, et al., COMESE, A Code to Assess the Feasibility of Power System Scenarios and Their Cost, in Presence of Variable Generation, in preparation (2019). [4] European Commission, ETRI 2014 – Energy Technology Reference Indicator Projections for 2010–2050, EC Joint Research Centre Institute for Energy and Transport, Petten, Netherland, 2014. [5] D. Maisonnier, et al., Power plant conceptual studies in Europe, Nucl. Fusion 47
2193
Contents lists available at ScienceDirect
Fusion Engineering and Design journal homepage: www.elsevier.com/locate/fusengdes
How fusion power can contribute to a fully decarbonized European power mix after 2050 C. Bustreoa,b, U. Giuliania,b, D. Maggioa,b, G. Zollinoa,b, a b
T
⁎
Consorzio RFX (CNR, ENEA, INFN, Università di Padova, Acciaierie Venete SpA), Corso Stati Uniti 4, 35127 Padova, Italy University of Padova, Department of Industrial Engineering, via Gradenigo 6a, 35131, Padova, Italy
ARTICLE INFO
ABSTRACT
Keywords: European energy scenarios Cost of electricity Fusion electricity
In the second half of this century, the European energy mix will be very likely completely decarbonized. Two main options are available to generate carbon free electricity: either to rely on renewable energy sources only, or to integrate renewables with a new generation of nuclear power plant, e.g. fusion power plant. In the former case a large storage capacity and/or dispatchable generation are required to compensate for the variable electricity generation. The size of the necessary storage systems and dispatchable power plants can be reduced if a baseload carbon free power technology is available, such as fusion. These options are analysed in this paper with the CO.ME.S.E. (COsto MEdio del Sistema Elettrico – Electric System Average Cost) code that assesses the hourly balance between load and generation, through a simplified dispatch model and the system costs, through a stochastic economic analysis. Two sets of power generation scenarios are considered in typical North and SouthEurope cases. The study gives key indications to make fusion a cost-effective ingredient of a future European decarbonized power mix.
1. Introduction According to the current international pledges on climate change, de-carbonization of the energy systems is a must, almost worldwide. The European Union has adopted an Energy Roadmap to 2050, setting an 80% reduction in energy related greenhouse gas emission below 1990 levels by 2050, which cannot be achieved but with a 95%–100% decarbonized power sector [1]. Hence, the European electricity generation mix of the second part of this century will be composed by carbon free technologies only: fossil fuel power plants plus CCS (Carbon Capture and Storage), nuclear power plants, renewable technologies. As for nuclear power, besides nuclear fission generation III + and IV reactors, also fusion power plants could contribute [2]. This paper provides a range of scenarios (see Table 1) in order to estimate to what extent fusion power will be able to enter the scene in Europe together with renewable energy sources (RES) by the last two decades of this century. Due to the high share of variable renewable energy the actual feasibility of each scenario must be assessed. To this aim, the generation profile is studied with a one-hour time resolution over a one-year timeframe and the energy storage and dispatchable generation capacity necessary to compensate the variable generation from renewable energy sources are estimated. In addition to the power generation mix technical feasibility, the scenarios here presented are used to assess the ⁎
costs of each choice and try to answer the question whether a carbon free power mix with fusion would be less expensive and more affordable - e.g. in terms of soil consumption - than a power mix without fusion. 2. The COMESE code The CO.ME.S.E. (COsto MEdio del Sistema Elettrico - Electric System Average Cost) code [3] is able to find the needs for power generation, storage and back-up capacity of power system scenarios, which are necessary to assure power dispatch on an hourly base, and perform economic analyses. A zero-dimensional network model is adopted, i.e. all generators, storage systems and loads are connected to the same node (the so called “copper plate” assumption). Power generation scenarios are at first arranged so as to cover annual demand and fulfill specific policy objectives, such as de-carbonization, specific technology targets or ban, etc. Then the actual feasibility of each mix is checked through the analysis of the hourly balance of power generation and demand whose profiles reflects historical database. Dispatchable technologies, such as dam hydropower and biomass and biogas power generation, and storage systems, such as pumped hydro plants and batteries, are included in each power mix, in order to manage surplus (over-generation) and deficit (under-generation) events, due to variable
Corresponding author at: Consorzio RFX (CNR, ENEA, INFN, Università di Padova, Acciaierie Venete SpA), Corso Stati Uniti 4, 35127 Padova, Italy. E-mail address: [email protected] (G. Zollino).
https://doi.org/10.1016/j.fusengdes.2019.03.150 Received 9 October 2018; Received in revised form 20 March 2019; Accepted 22 March 2019 Available online 04 April 2019 0920-3796/ © 2019 Elsevier B.V. All rights reserved.
Fusion Engineering and Design 146 (2019) 2189–2193
C. Bustreo, et al.
Table 1 Key parameters of the power generation scenarios, all with 600 TW h demand. South Europe
North Europe
100%-RES
Photovoltaic
Residential roof Commercial roof Utility scale on shore near shore off shore Run of River Hydro Geothermal Municipal Waste
Wind Baseload Generation Fusion Dispatchable Generation Total generation Curtailed Energy Storage Roundtrip losses
Fusion Baseload
Fusion 2 Seasons
100% RES
Fusion Baseload
[GW]
[TWh]
[GW]
[TWh]
[GW]
[TWh]
[GW]
[TWh]
[GW]
[TWh]
230 60 160 23 2
280 70 240 45 5
63 16 44 23 2
76 19 67 45 5
78 20 55 23 2
94 24 82 45 5
13
11
13
11
12
30
12
30
8 1 1
35 8 7
8 1 1 37 13 22
35 8 7 260 31* 62* 614 7 0.1 0.4 7
8 1 1 37 13 15
35 8 7 260 31* 31* 622 11 0.1 0.5 11
170 1.9
640 6
75 1.9
290 6
1
8
1 37
8 260
40
41* 736 124 0.05 1 12
39
40* 645 41 0.05 0.4 4
Dam Hydro Bioenergy
13 28
Pumped Hydro Batteries
9 150
*
29 50* 769 130 0.1 1.2 39
9 50
9 62
3 125
3 50
* According to the hourly simulation results.
and un-programmable energy sources, and guarantee load balance. In particular, during peak under-generation event, the missing power is provided by dispatchable generators plus storage devices, preloaded by the same dispatchable generators. The size of dispatchable power plants and storage systems, including the possibility of curtailment, are determined through an iterative approach which minimize their contribution to cost of electricity, as defined below. Once the contribution of all technologies to the hourly power generation is assessed, the capacity factor of dispatchable generators is determined and the average Levelised Cost of Timely Electricity (LCOTE) is calculated. Provided that Np different kinds of power plants are generating electricity and storage systems are involved, the LCOTE is calculated as follows: Np i=1
LCOTE =
power plants in Europe by 2080 is assumed in favor of a wide fusion power deployment. Two cases are proposed: “South-Europe”, with a predominant solar generation and “North-Europe”, largely based on wind power, reflecting the actual potentials of these renewable energy sources in Europe, in line with scenarios proposed at EU level [1]. Indeed, among renewable energy, solar and wind are the most promising in terms of electricity generation potential and technology maturity, as shown by the impressive tariff reductions recently registered in national auctions. For all the scenarios, geothermal, run of river hydro and municipal waste power generation are assumed to provide base-load generation and are set to their maximum estimated potentials. As for solar and wind generation, the actual hourly profiles recorded by the national TSO in 2015 (year 2015 is arbitrary chosen), are taken into account. In order to simplify the analysis, although electricity demand is assumed to growth to 600 TW h/year, due to the electrification of new energy sectors (e.g. transport and space heating), the same hourly profiles recorded by TSOs in 2015 are considered, without any demand response effect.
(LCOEi × Ei ) + Cstor Eload
where LCOEi is the well known levelized lifetime average cost of electricity generated by the i–th technology, Ei and Eload are the electricity generated by the i–th technology and the annual electricity demand, respectively. Cstor is the annual cost of energy storage systems, which is computed as follows:
Cstor =
s
Is
r )ns
r (1 + (1 + r )ns
1
3.1. South-Europe scenarios Italy is chosen as reference Country for the analysis of a future South-Europe power generation mix and three scenarios are simulated: a) 100%-RES, without any fusion contribution; b) fusion-baseload, where fusion power plants generate 260 TW h at 30 GW constant power; i.e. 37 GW installed capacity with 80% availability [5]; c) fusion-two-seasons, where fusion still generate 260 TW h, but at 25 GW power in the six months when solar radiation is higher (i.e. from April to September) and at 35 GW power during the rest of the year. In all the scenarios, base load generation supplies 50 TW and wind farms (mostly on-shore, with a small contribution of near-shore plants) generate 50 TWh [6]. In the 100%-RES scenario, 450 GW PV capacity must be installed, generating 590 TW h, in addition to the 100 TW h coming from base-load and wind plants. However, due to wind and PV variability, 690 TW h is not enough to satisfy the 600 TW h demand. In fact, over-generation occurs for more than 3000 h and under-generation for 5700 h (Fig. 1). Thus, in order to guarantee that power demand be covered hour by hour, dispatchable energy must be added, together with pumped-hydro and battery storage systems. In Table 1, the optimal arrangement (i.e. that giving the lowest cost of electricity) of dispatchable generators (41 GW/79 TW h), pumped-
+ O &Ms
where Is is the investment costs (Eur) of a storage technology (pumpedhydro or batteries), O&Ms its annual average O&M costs (Eur/years), ns its expected lifetime (years) and r the lifetime average discount rate. As indicated in Table 2, for each technology, investment and O&M costs, fuel cost and lifetime are varied within a range chosen according to the most recent learning factor estimations to technology maturity [4]; once probability distribution are assigned, Montecarlo analyses can be performed. It is worth noting that, due to the copper plate assumption, the LCOTE doesn’t account for investment and O&M costs necessary to cope with electric grid enhancements requested to manage overgeneration events. 3. Energy scenarios Possible decarbonized power generation mixes in Europe are studied, referring to the second half of this century (indicatively 2080 and beyond). CCS technologies are deliberately not included in the scenarios. With regards to nuclear power, a complete phase-out of fission 2190
Fusion Engineering and Design 146 (2019) 2189–2193
C. Bustreo, et al.
Table 2 Technical and economic parameters of power generation and storage technologies. Overnight cost [€/kW]
O&M costs
Lifetime [years]
FIXED [€/kW y] Photovoltaic Wind
Residential roof Commercial roof Utility-tracking on shore near shore off shore Run of River
Hydro Geothermal Municipal Waste* (η = 30%) Fusion Dispatchable Energy Dam Hydro Bioenergy** (η = 33%) Storage Pumped Hydro (η = 80%) Batteries (η = 85%)
1000 ± 15% 800 ± 15% 800 ± 15% 1100 ± 20% 2100 ± 20% 1800 ± 20% 3000 ± 40% 3500 ± 15% 4500 ± 20% 6000 ± 30% 2500 ± 40% 3000 ± 20% 1500 ± 40% 750 ± 20% (8 h storage)
VAR. [€/MWh]
20 ± 15% 20 ± 12% 20 ± 15% 20 ± 30% 30 ± 30% 50 ± 30% 80 ± 30% 80 ± 25% 130 ± 25% 110 50 ± 30% 100 ± 25% 20 ± 25% 8 ± 20%
5 30 5 8
25 ± 15% 25 ± 15% 25 ± 15% 25 ± 15% 25 ± 15% 25 ± 15% 60 ± 10% 30 ± 15% 25 ± 15% 60 60 ± 10% 15 + 35% 60 ± 10% 10 ± 25%
Load hours
LCOE [c€/kWh]
North
South
North
South
800 800 1100 2500
1200 1200 1500 1900 2200
11.5 9.7 7.1 4
7.7 6.5 5.2 5.3 8.3
3800 3200 7800 7800 7000
4500 7800 7800 7000 2500 1000 – 3000***
4.7 8 4.3 0 6.3 50-24
6 4.3 0 6.3 8
* Fuel cost is assumed as negative at -80Eur/ton; **Fuel cost at 100 Eur/ton; *** According to the hourly simulation results.
Fig. 1. Duration curves of load and PV + Wind generation (left), under-generation and over-generation (center), dispatchable energy and storage output (right) for the 100%-RES scenarios in South-Europe and North-Europe.
95% and 82% respectively. Finally, in the fusion-two-seasons scenario, the installed PV capacity is slightly higher than in the fusion-baseload scenario (153 GW, generating 200 TW h), but the optimal arrangement for dispatchable energy and storage is even more favorable: -21% dispatchable energy and capacity than in 100%-RES; 9 GW/0.1 TW h pumped-hydro and 62 GW/0.5 TW h battery storage, with 11 TW h curtailed energy and 11 TW h losses due to the battery efficiency. 3.2. North-Europe scenarios United Kingdom is chosen as reference Country for the analysis of a future North-Europe power generation mix and only two scenarios are considered because of no evident seasonal change in wind generation: a) 100%-RES; b) fusion-baseload, with the same fusion contribution as for South-Europe scenarios. In both scenarios, base load generation, provided by run of river hydro and municipal waste power plants, supplies 14 TW h and 13 GW PV plants are installed on residential roofs only, generating 11 TW h [7]. As for wind generation, in both scenarios 12 GW on-shore wind capacity is installed, supplying 30 TW h. In the 100%-RES scenario, most of the electricity is generated by off-shore wind farms: in fact, 170 GW must be installed (within the estimated potential [8]), generating 640 TW h, in addition to the 52 TW h coming from base-load, PV and on-shore wind plants. However, due to the predominant contribution of variable energy source, such as wind energy, 692 TW h are not enough to satisfy the 600 TW h demand. In fact, over-generation occurs for 5000 h and under-generation for 4000 h (Fig. 1). Thus, also in this case, dispatchable energy must be added (40 GW/41 TW h), together with energy storage systems (3 GW/ 0.05 TW h pumped-hydro which is the maximum UK potential and 125 GW/1 TW h battery storage). In the fusion-baseload scenario, the
Fig. 2. Breakdown of the LCOTE when all cost parameters are set at their middle value.
hydro (9 GW/0.1 TW h which is the maximum Italian potential) and battery storage (150 GW/1.2 TW h) are given. In the fusion-baseload scenario, the installed PV capacity is less than one third than in the 100%-RES scenario (123 GW, generating 162 TW h). As compared to the 100%-RES scenario, +17% dispatchable energy is needed but less capacity is required (−15%); as for the storage systems, the maximum Italian potential of pumped-hydro is exploited like in 100%-RES scenario but battery storage system size is reduced by 67%. Curtailed energy and energy losses due to the battery efficiency are reduced by 2191
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Fig. 3. Probability density distribution of the LCOTE.
Fig. 4. Modes of the LCOTE as a function of future fusion power plants overnight costs.
installed off-shore wind capacity is less than one half than in the 100%RES scenario, i.e. 75 GW, generating 290 TW h; the optimal arrangement for dispatchable energy is the same as in 100%-RES, but the battery storage size is reduced by 60% while the pumped-hydro potential is again exploited. Curtailed energy is reduced by 69% and losses due to the battery efficiency by 67%.
North-Europe and for the South-Europe case, the presence of fusion power plants reduces the LCOTE A sensitivity analysis has been also performed. Fig. 4 shows that fusion would be effective in reducing the LCOTE as long as its overnight costs were kept below 8500 Eur/kW in the North-Europe case and below 12,500 Eur/kW in the South-Europe case.
4. Main results
5. Conclusions
Cost analyses have been performed, as described in Section 2, to assess whether and to what extent fully decarbonized power mixes could take benefits from nuclear fusion power. Table 2 summarizes the technical and economic parameters, taken from the literature [4]; as for fusion, a steady state fusion power plant is considered, with 6000 Eur/ kW investment cost, 110 Eur/kWy O&M costs, 60 y life-time and 80% availability, which are in line with the ranges proposed by EUROfusion for “basic” commercial power plants [9] and the results of analyses carried out with the FRESCO code [10,11]. Fig. 2 shows the LCOTE recovered using the central value of all economic parameters and its breakdown among different kinds of power plants and storage. In the 100%-RES scenarios, almost one half of the LCOTE is due to dispachable energy and storage, which must face variability of renewable energy sources. Fig. 3 reports the probability density distribution of the LCOTE, as cost parameters vary as indicated in Table 2. Both for the
In a carbon-free power generation mix, likely by the end of this century, fusion would reduce the cost of electricity, in comparison with 100%-RES scenarios. This is true as long as the overnight cost of a fusion power plant will be lower than 8500 Eur/kW in the North-Europe case and lower than 12,500 Eur/kW in the South-Europe case. Actually, due to the copper plate assumption, the costs of an electric grid able to manage over-generation and storage are not taken into account; thus, the convenience of a power mix with fusion would result even higher if a detailed electric grid model were considered. In addition to cost, warnings on soil consumption, linked with hundreds GW size deployment of PV and Wind power plants, is a further issue in favour of power generation scenarios with fusion.
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References
(2007) 1524–1532. [6] Ministero dello Sviluppo Economico, Strategia Energetica Nazionale, (2017). [7] https://www.gov.uk/government/statistics/energy-trends-section-6-renewables. [8] R.J. Swart, et al., Europe’s Onshore and Offshore Wind Energy Potential: an Assessment of Environmental and Economic Constraints, European Environment Agency, 2009. [9] H. Cabal, et al., Fusion power in a future low carbon global electricity system, Energy Strategy Rev. 15 (2017) 1–8. [10] C. Bustreo, et al., The Monte Carlo approach to the economics of a DEMO-like power plant, Fusion Eng. Des. 98–99 (2015) 2108–2111. [11] C. Bustreo, et al., FRESCO, a simplified code for cost analysis of fusion power plants, Fusion Eng. Des. 88 (2013) 3141–3151.
[1] EU Coucil-General Secretariat, Working Paper 1976/2016 REV 1: Revised Technical Report on Member States Results of the EUCO Policy Scenarios, January (2017). [2] T. Donnè, et al., European Research Roadmap to the Realisation of Fusion Energy, (2018). [3] C. Bustreo, et al., COMESE, A Code to Assess the Feasibility of Power System Scenarios and Their Cost, in Presence of Variable Generation, in preparation (2019). [4] European Commission, ETRI 2014 – Energy Technology Reference Indicator Projections for 2010–2050, EC Joint Research Centre Institute for Energy and Transport, Petten, Netherland, 2014. [5] D. Maisonnier, et al., Power plant conceptual studies in Europe, Nucl. Fusion 47
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