Supplementary Material for

Supplementary Material for: The transition towards a sustainable power system for Europe Michael Child1, Claudia Kemfert2, Dmitrii Bogdanov1, Christian Breyer1 1

Lappeenranta University of Technology, Skinnarilankatu 34, 53850 Lappeenranta, Finland

2

German Institute for Economic Research (DIW) and Hertie School of Governance, Mohrenstrasse 58, 10117 Berlin, Germany

 Email: [email protected]

Table S1: Technical and financial assumptions of all energy system components used in the energy transition from 2015 to 2050. Assumptions are taken from Pleßmann et al. (2014) and European Commission (Carlsson 2014) and further references are individually mentioned.

Name of component PV optimally tilted

2015

2020

2025

2030

2035

2040

2045

2050

Capex

€/kW

1000

680

560

480

420

370

330

300

Opex fix Opex var.

€/kW

15 0

10.2 0

8.4 0

7.2 0

6.3 0

5.6 0

5 0

4.5 0

Lifetime

years

30

30

35

35

35

40

40

40

PV single-axis tracking Capex

€/kW

1150

750

620

530

465

410

365

330

Opex fix Opex var. Lifetime

€/kW

17.3 0 30

11.3 0 30

9.3 0 35

8 0 35

7 0 35

6.2 0 40

5.5 0 40

5 0 40

years

Reference (Vartiainen et al. 2015; Fraunhofer ISE 2015)

(Vartiainen et al. 2015; Fraunhofer ISE 2015)

PV prosumers

Wind onshore

CSP (solar field. parabolic trough)

Capex

€/kW

1360

1090

890

760

680

610

550

500

Opex fix Opex var. Lifetime Capex Opex fix Opex var.

€/kW

20 0 30 1250 25 0

16 0 30 1150 23 0

13 0 35 1060 21 0

11 0 35 1000 20 0

10 0 35 965 19 0

9 0 40 940 19 0

8 0 40 915 18 0

8 0 40 900 18 0

Lifetime

years

25

25

25

25

25

25

25

25

years €/kW €/kW

Capex

€/m2

270

240

220

200

180

170

150

140


%

2.3 0 25

2.3 0 25

2.3 0 25

2.3 0 25

2.3 0 30

2.3 0 30

2.3 0 30

2.3 0 30

years

Geothermal power Capex

€/kW

5250

4970

4720

4470

4245

4020

3815

3610


€/kW

80.0 0 40

80.0 0 40

80.0 0 40

80.0 0 40

80.0 0 40

80.0 0 40

80.0 0 40

80.0 0 40

years

Water electrolysis Capex

€/kW


€/kW €/kWh years

800

685

500

363

325

296

267

248

32 27 20 12.7 11.4 10.4 9.4 8.7 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 30 30 30 30 30 30 30 30

(Vartiainen et al. 2015; Fraunhofer ISE 2015)

(Neij 2008)

(Haysom et al. 2015; Kutscher et al. 2010)

(Carlsson 2014; Sigfusson and Uihlein 2015)

(Agora Energiewende 2014; Breyer et al. 2015)

Methanation Capex

€/kW

492

421

310

278

247

226

204

190

Opex fix

€/kW

19.7

16.8

12.4

11.1

9.9

9

8.2

7.6

Opex var.

€/kWh

Lifetime

years


0.0015 0.0015 0.0015 0.0015 0.0015 0.0015 0.0015 0.0015 30

30

30

30

30

30

30

30

CO2 direct air capture Capex

€/kW

480

411

301

228

201

183

165

154

Opex fix Opex var.

€/kW €/kWh

19.2 7.2

16.4 7.2

12 7.2

9.1 7.2

8 7.2

7.3 7.2

6.6 7.2

6.1 7.2

Lifetime

years

30

30

30

30

30

30

30

30

Capex

€/kW

775

775

775

775

775

775

775

775

Opex fix Opex var. Efficiency

€/kW %

19.4 0 58

19.4 0 58

19.4 0 58

19.4 0 58

19.4 0 59

19.4 0 60

19.4 0 60

19.4 0 60

Lifetime

years

35

35

35

35

35

35

35

35

CCGT

OCGT Capex

€/kW

475

475

475

475

475

475

475

475


€/kW €/kWh %

9.5 0.004 43

9.5 0.004 43

9.5 0.004 43

14.25 0.004 43

14.25 0.004 43

14.25 0.004 43

14.25 0.004 43

14.25 0.004 43

Lifetime

years

35

35

35

35

35

35

35

35


(International Energy Agency 2014)


Steam turbine (CSP)

Steam turbine (coal-fired PP)

Nuclear PP

Biomass PP

Biogas CHP

Capex

€/kW

760

740

720

700

670

640

615

600


€/kW %

15.2 0 42

14.8 0 42

14.4 0 42

14 0 43

13.4 0 44

12.8 0 44

12.3 0 45

12 0 45

Lifetime

years

25

25

25

25

30

30

30

30

Capex Opex fix Opex var. Efficiency

€/kW €/kW %

1500 20 0 45

1500 20 0 45

1500 20 0 45

1500 20 0 45

1500 20 0 46

1500 20 0 46

1500 20 0 47

1500 20 0 47

Lifetime

years

40

40

40

40

40

40

40

40

Capex Opex fix Opex var. Efficiency Lifetime Capex Opex fix Opex var. Efficiency Lifetime Capex Opex fix Opex var. Efficiency Lifetime

€/kW 6210 6003 6003 5658 5658 5244 5244 5157 €/kW 162 157 157 13 137 116 116 109 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 €/kWh 0.0025 37 37 38 38 38 38 % 37 38 40 40 40 40 40 40 40 years 40 €/kW 3400 2900 2700 2500 2300 2200 2100 2000 €/kW 238 203 189 175 161 154 147 140 €/kWh 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 % 36 37 40 43 45 47 48 48 years 30 30 30 30 30 30 30 30 €/kW 503 429 400 370 340 326 311 296 €/(kW a) 20.1 17.2 16.0 14.8 13.6 13.0 12.4 11.8 €/(kWh) 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 % 35 36 39 42 44 46 46 47 years

30

30

30

30

30

30

30

30

(International Energy Agency 2014; Breyer et al. 2015)

Waste incinerator

Biogas digester

Capex

€/kW


€/kW €/kWh %

Lifetime

years

30

30

30

30

30

30

30

30


€/kW €/kW %

771 30.8 0 100

731 29.2 0 100

706 28.2 0 100

680 27.2 0 100

653 26.1 0 100

632 25.3 0 100

609 24.3 0 100

589 23.6 0 100

Lifetime

years

20

20

20

20

25

25

25

25

Capex

€/kW

340

290

270

250

230

220

210

200


€/kW %

27.2 0 98

23.2 0 98

21.6 0 98

20 0 98

18.4 0 98

17.6 0 98

16.8 0 98

16 0 98

Lifetime

years

20

20

20

20

25

25

25

25


€/kWh €/kWh €/kWh %

Lifetime

years


€/kWh €/kWh €/kWh %

Lifetime

years

5940

5630

5440

5240

5030

4870

4690

4540

267.3 253.35 244.8 235.8 226.35 219.15 211.05 204.3 0.0069 0.0069 0.0069 0.0069 0.0069 0.0069 0.0069 0.0069 27 31 32.5 34 35.5 37 29.5 42

Biogas upgrade

Battery Li-ion

Adiabatic compressed air energy storage (A-CAES)

600 300 200 150 120 100 85 75 24 9 5 3.75 3 2.5 2.125 1.875 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 96 96 96 96 96 96 96 96 15

20

20

20

20

20

20

20

35.0 35.0 33.0 31.1 30.4 29.8 28.0 26.3 0.46 0.46 0.43 0.40 0.40 0.39 0.36 0.34 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 84 84 84 84 84 84 84 84 40

55

55

55

55

55

55

55


Gas storage

Capex Opex fix Opex var. Lifetime

€/kWh €/kWh €/kWh years

0.05 0.001 0 50

0.05 0.001 0 50

0.05 0.001 0 50

0.05 0.001 0 50

0.05 0.001 0 50

0.05 0.001 0 50

0.05 0.001 0 50

0.05 0.001 0 50

Table S2: Energy to power ratio of the storage technologies. Assumptions based on (Pleßmann et al. 2014). Technology Battery A-CAES Gas storage TES PHS

Energy /Power Ratio (h) 6 100 80*24 8 8

Self-Discharge(%/h) 0 0.1 0 0.2 0

Table S3: Residential Electricity Price (€/kWh). Based on (Gerlach et al. 2014; Breyer and Gerlach 2013) Region Norway Denmark Sweden Finland Baltic Poland Iberia France Benelux British Isles Germany Czech Republic & Slovakia Austria Hungary Balkan West Balkan East Italy Switzerland Turkey, Cyprus Ukraine, Moldova Iceland

2015 0.1590 0.2640 0.1670 0.1294 0.1083 0.1420 0.1655 0.1290 0.1891 0.1511 0.2330 0.1460 0.1901 0.0915 0.1146 0.2150 0.1320 0.1443 0.0215 0.1070

2020 0.1843 0.2775 0.1936 0.1501 0.1338 0.1646 0.1918 0.1495 0.2192 0.1754 0.2649 0.1696 0.2203 0.1107 0.1387 0.2492 0.1530 0.1673 0.0275 0.1340

2025 0.2137 0.2916 0.2244 0.1740 0.1589 0.1908 0.2224 0.1734 0.2539 0.2036 0.2784 0.1967 0.2551 0.1338 0.1626 0.2671 0.1774 0.1939 0.0351 0.1553

2030 0.2477 0.3065 0.2602 0.2017 0.1874 0.2212 0.2578 0.2010 0.2703 0.2341 0.2926 0.2281 0.2716 0.1598 0.1881 0.2808 0.2057 0.2248 0.0448 0.1800

2035 0.2655 0.3221 0.2735 0.2338 0.2182 0.2565 0.2716 0.2330 0.2841 0.2643 0.3075 0.2608 0.2855 0.1859 0.2182 0.2951 0.2384 0.2602 0.0571 0.2087

2040 0.2791 0.3386 0.2874 0.2606 0.2511 0.2696 0.2855 0.2649 0.2986 0.2777 0.3232 0.2740 0.3001 0.2103 0.2490 0.3101 0.2657 0.2735 0.0729 0.2419

2045 0.2791 0.3386 0.2874 0.2606 0.2513 0.2696 0.2855 0.2649 0.2986 0.2778 0.3232 0.2740 0.3000 0.2088 0.2491 0.3101 0.2657 0.2735 0.0729 0.2419

2050 0.2933 0.3558 0.3021 0.2739 0.2699 0.2833 0.3001 0.2784 0.3138 0.2920 0.3397 0.2879 0.3153 0.2318 0.2702 0.3260 0.2793 0.2874 0.0918 0.2645

Table S4: Commercial Electricity Price (€/kWh). Based on (Gerlach et al. 2014; Breyer and Gerlach 2013) Region Norway Denmark Sweden Finland Baltic Poland Iberia France Benelux British Isles Germany Czech Republic & Slovakia Austria Hungary Balkan West Balkan East Italy Switzerland Turkey, Cyprus Ukraine, Moldova Iceland

2015 0.1180 0.1890 0.1180 0.0918 0.0887 0.1190 0.1332 0.1000 0.1512 0.1270 0.1740 0.1305 0.1572 0.0841 0.1004 0.1780 0.1080 0.1373 0.0215 0.0530

2020 0.1413 0.2081 0.1402 0.1096 0.1126 0.1436 0.1597 0.1201 0.1794 0.1627 0.2031 0.1556 0.1848 0.1039 0.1243 0.2064 0.1301 0.1596 0.0275 0.0670

2025 0.1696 0.2263 0.1676 0.1311 0.1378 0.1678 0.1856 0.1445 0.2079 0.1887 0.2211 0.1806 0.2144 0.1271 0.1484 0.2283 0.1558 0.1850 0.0351 0.1044

2030 0.1980 0.2465 0.1981 0.1571 0.1661 0.1945 0.2151 0.1702 0.2290 0.2177 0.2412 0.2095 0.2366 0.1529 0.1729 0.2502 0.1806 0.2145 0.0448 0.0900

2035 0.2187 0.2692 0.2156 0.1860 0.1943 0.2255 0.2358 0.1973 0.2509 0.2488 0.2638 0.2410 0.2595 0.1774 0.2006 0.2749 0.2094 0.2485 0.0571 0.1044

2040 0.2391 0.2946 0.2351 0.2104 0.2249 0.2476 0.2586 0.2260 0.2754 0.2693 0.2891 0.2614 0.2805 0.2031 0.2307 0.2915 0.2374 0.2686 0.0729 0.1210

2045 0.2621 0.3122 0.2570 0.2299 0.2503 0.2724 0.2821 0.2477 0.2905 0.2833 0.3039 0.2798 0.2948 0.2289 0.2572 0.3064 0.2609 0.2823 0.0918 0.1322

2050 0.2854 0.3282 0.2816 0.2516 0.2689 0.2863 0.2965 0.2721 0.3054 0.2978 0.3194 0.2940 0.3099 0.2546 0.2743 0.3221 0.2793 0.2967 0.1156 0.1390

Table S5: Industrial Electricity Price (€/kWh). Based on (Gerlach et al. 2014; Breyer and Gerlach 2013) Region Norway Denmark Sweden Finland Baltic Poland Iberia France Benelux British Isles Germany Czech Republic & Slovakia Austria Hungary Balkan West Balkan East Italy Switzerland Turkey, Cyprus Ukraine, Moldova Iceland

2015 0.0770 0.1130 0.0680 0.0542 0.0697 0.0960 0.1000 0.0710 0.1136 0.1291 0.1150 0.1155 0.1240 0.0764 0.0860 0.1410 0.0840 0.1312 0.0215 0.0000

2020 0.0983 0.1388 0.0868 0.0691 0.0914 0.1225 0.1276 0.0906 0.1395 0.1499 0.1412 0.1416 0.1493 0.0971 0.1099 0.1635 0.1072 0.1520 0.0275 0.0000

2025 0.1254 0.1609 0.1108 0.0882 0.1166 0.1448 0.1488 0.1157 0.1619 0.1737 0.1637 0.1645 0.1736 0.1205 0.1341 0.1895 0.1342 0.1762 0.0351 0.0000

2030 0.1482 0.1865 0.1360 0.1126 0.1449 0.1679 0.1725 0.1393 0.1877 0.2014 0.1898 0.1909 0.2016 0.1459 0.1577 0.2197 0.1556 0.2043 0.0448 0.0000

2035 0.1718 0.2162 0.1577 0.1383 0.1705 0.1946 0.1999 0.1615 0.2176 0.2334 0.2200 0.2213 0.2335 0.1689 0.1829 0.2547 0.1804 0.2368 0.0571 0.0000

2040 0.1992 0.2506 0.1828 0.1603 0.1987 0.2256 0.2318 0.1872 0.2522 0.2610 0.2551 0.2488 0.2609 0.1959 0.2124 0.2730 0.2091 0.2638 0.0729 0.0000

2045 0.2309 0.2687 0.2119 0.1858 0.2307 0.2615 0.2642 0.2171 0.2673 0.2747 0.2681 0.2717 0.2744 0.2253 0.2442 0.2869 0.2424 0.2773 0.0918 0.0000

2050 0.2625 0.2824 0.2457 0.2154 0.2529 0.2749 0.2776 0.2516 0.2809 0.2887 0.2818 0.2854 0.2884 0.2532 0.2647 0.3015 0.2650 0.2914 0.1156 0.0000

Table S6: Installed capacities for 2015 in units of MWth for CSP and MWel for all other technologies. Based on (Farfan and Breyer 2016) Technology Region / Unit Norway Denmark Sweden Finland Baltic Poland Iberia France Benelux British Isles Germany Czech Republic & Slovakia Austria Hungary Balkan West Balkan East Italy Switzerland Turkey, Cyprus Ukraine, Moldova Iceland Europe total

PV optimal tilt MWel

PV singleaxis tracking MWel

Wind Offshore MWel

Run-of-River Hydro MWel

Wind Onshore MWel

Hydro Dam MWel

CSP MWth

13 655 72 19 76 28 6098 6149 4614 5808 38636

0 0 0 0 0 0 0 0 0 0 0

1280 3993 7651 1151 613 4335 27888 9713 4451 14015 37386

2 1271 212 226 0 0 7 0 1688 5238 3320

9191 9 5336 3434 1119 210 5061 6077 136 796 3281

20116 0 11496 0 70 489 17691 12380 25 1561 2091

0 0 0 0 0 0 2355 2 0 0 2

2900 809 385 5299 19251 1062 150

0 0 0 0 0 0 0

289 2608 1131 8632 9012 73 5046

0 0 0 0 0 0 0

899 5577 2536 3275 5367 4141 7635

2470 4938 5991 8466 9215 8132 16457

0 0 0 0 5 0 0

856 3 92881

0 0 0

1115 0 140380

0 0 11965

2641 9 66729

1988 1943 125521

0 0 2364

Table S7: Assumed upper limits of installed capacities for generation technologies in units of GWth for CSP and GWel for all other technologies. Calculated according to (Bogdanov and Breyer 2016) Technology Region / Unit Norway Denmark Sweden Finland Baltic Poland Iberia France Benelux British Isles Germany Czech Republic & Slovakia Austria Hungary Balkan West Balkan East Italy Switzerland Turkey, Cyprus Ukraine, Moldova Iceland Europe total

PV optimal tilt GWel

PV singleaxis tracking GWel

Wind Offshore GWel

Run-of-River Hydro GWel

Wind Onshore GWel

Hydro Dam GWel

CSP GWth

1457 194 2026 1522 788 1407 2689 2484 336 1416 1607

1457 194 2026 1522 788 1407 2689 2484 336 1416 1607

109 14 151 114 59 105 201 185 25 106 120

100 101 100 100 100 100 100 100 102 105 103

14 0 8 5 2 0 8 9 0 1 5

30 0 17 0 0 1 27 19 0 2 3

2914 388 4053 3043 1576 2814 5377 4968 672 2832 3213

576 796 1281 2166 1358 186 3568

576 796 1281 2166 1358 186 3568

43 59 96 162 101 14 266

0 0 0 100 100 0 100

1 8 4 5 8 6 11

4 7 9 13 14 12 25

1151 1592 2562 4331 2715 371 7135

2868 464 29186

2868 464 29186

214 35 2179

100 100 1612

4 0 100

3 3 188

5737 927 58373

Table S8: Estimation of bioenergy potential (TWhth) for Europe from 2015 to 2050. Based on (Elbersen et al. 2012; Bunzel et al. 2009) Region

Solid waste - MSW

Solid waste - biomass

Solid residues

Biogas

Bioenergy total

Norway

0.9

1.7

8.5

1.4

12.5

Denmark

2.4

0.7

15.2

28.4

46.6

Sweden

2.0

69.7

48.3

8.4

128.5

Finland

2.5

58.1

36.5

14.8

112.0

Baltic

2.0

20.6

24.5

6.4

53.5

Poland

11.4

18.2

65.9

144.7

240.3

Iberia

10.9

28.3

47.3

93.2

179.8

France

11.9

25.8

148.0

149.5

335.2

Benelux

9.3

7.1

8.3

80.1

104.8

British Isles

15.6

11.5

36.7

114.5

178.4

Germany

17.2

58.6

122.1

77.8

275.7

Czech Republic & Slovakia

2.9

23.1

37.0

35.5

98.5

Austria Hungary

2.9

25.0

57.0

39.4

124.3

Balkan West

2.3

0.6

21.4

5.4

29.8

Balkan East

7.5

16.7

82.6

52.2

159.0

Italy

14.4

7.5

38.6

85.0

145.6

Switzerland

1.1

1.8

5.6

2.2

10.7

Turkey, Cyprus

12.5

1.4

41.3

6.4

61.5

Ukraine, Moldova

4.4

1.4

42.9

11.2

60.0

Iceland

0.1

0.0

0.0

0.0

0.1

134.3

377.9

887.8

956.6

2356.6

Europe total

Table S9: Estimation of bioenergy gate fees and prices (€/MWh) for Europe from 2015 to 2050.

Region

2015

2020

2025

2030

2035

2040

2045

2050

Solid waste – Biomass All years

Norway

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

15.2

0

Denmark

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

6.2

0

Sweden

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

15.0

0

Finland

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

14.3

0

Baltic

17.3

18.1

19.2

20.2

20.3

20.3

20.3

20.3

0

10.3

0

Poland

17.5

19.7

20.3

20.3

20.3

20.3

20.3

20.3

0

7.7

0

Iberia

19.2

19.6

20.0

20.3

20.3

20.3

20.3

20.3

0

8.6

0

France

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

6.9

0

Benelux

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

7.7

0

British Isles

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

6.8

0

Germany

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

8.5

0

Czech Republic & Slovakia

18.6

19.5

20.0

20.3

20.3

20.3

20.3

20.3

0

8.6

0

Austria Hungary

19.2

20.1

20.3

20.3

20.3

20.3

20.3

20.3

0

7.7

0

Balkan West

15.7

17.1

18.1

19.2

20.3

20.3

20.3

20.3

0

6.4

0

Balkan East

15.7

17.1

19.1

20.2

20.3

20.3

20.3

20.3

0

7.0

0

Italy

19.7

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

7.2

0

Switzerland

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

14.7

0

Turkey, Cyprus

17.5

18.8

19.5

20.3

20.3

20.3

20.3

20.3

0

5.3

0

Ukraine, Moldova

10.7

11.5

12.9

14.9

17.5

19.2

20.3

20.3

0

5.3

0

Iceland

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

0.0

0

Europe total

20.3

20.3

20.3

20.3

20.3

20.3

20.3

20.3

0

15.2

0

Solid waste – MSW gate fee

Solid residues

Biogas

All years

All years

Table S10: Total European installed capacities of different electricity generation technologies from 2015 to 2050 [GW]. Technology

2015

2020

2025

2030

2035

2040

2045

2050

PV optimally tilted PV single-axis tracking PV prosumers CSP Wind onshore Wind offshore Geothermal power Hydro RoR Hydro Dam CCGT OCGT Steam turbine Biomass PP Waste incinerator Biogas PP Coal PP Internal combustion generator Nuclear PP

49 0 54 2 127 8 2 67 192 177 96 0.3 20 8 9 234

49 90 135 2 191 8 3 67 195 172 94 0.3 19 17 21 166

49 150 362 2 355 8 5 67 209 168 130 0.6 28 19 25 111

52 229 590 2 480 7 5 67 214 173 145 0.7 31 19 39 72

57 347 781 2 537 5 6 67 222 166 141 6.6 32 19 41 51

132 409 974 2 546 0 6 67 224 137 133 7.8 33 19 56 36

197 449 1124 0 552 0 6 67 224 111 118 6.7 35 20 57 24

217 472 1268 0 560 0 6 67 224 95 130 5.8 41 20 67 20

55 138

33 133

7 105

3 58

1 22

0 13

0 8

0 2

Table S11: Full Load Hours of generation and storage technologies from 2015 to 2050 (h). Technology PV optimally tilted PV single-axis tracking CSP Wind onshore Wind offshore Hydro ROR Hydro dams Geothermal Battery prosumers (Residential) Battery prosumers (Commercial) Battery prosumers (Industrial) Battery prosumers (total) Battery system PHS TES Adiabatic compressed air energy storage (A-CAES) Power-to-gas CCGT OCGT Steam turbine Biomass PP Waste incinerator Biogas CHP Biogas upgrade Biogas digester Coal PP Internal combustion generator Nuclear PP

2015 1236 1432 2069 2546 3960 2878 2902 5179 0 0 0 0 0 1065 8285

2020 1236 1911 2068 3066 3960 2878 2916 6254 1587 1609 1664 1599 3815 1641 8017

2025 1236 1865 2059 3030 3961 2878 2977 6566 1507 1538 1584 1541 2537 1747 7862

2030 1237 1735 2059 2970 3959 2878 2983 6355 1449 1505 1550 1502 1824 1450 7732

2035 1237 1720 2059 3055 3967 2878 2966 6119 1399 1458 1494 1452 1660 1349 6850

2040 1342 1694 2056 3133 3089 2878 2960 6028 1357 1420 1444 1408 1610 1429 6226

2045 1356 1689 1137 3168 3010 2878 2966 6171 1330 1379 1403 1373 1586 1322 5838

2050 1383 1671 1115 3166 3222 2878 2971 6400 1307 1353 1371 1345 1584 1336 5221

0 0 2436 2074 5916 2595 5774 5746 0 8322 4930 1147 7104

1744 0 2780 63 5918 4998 8099 6535 8322 8322 4654 4 7446

1457 408 1703 67 3992 6084 8160 5131 8315 8322 2947 1 7446

1245 151 1688 168 3497 6031 8287 2785 8319 8322 2316 1 7446

1649 3660 1844 202 2451 5505 8322 2497 8317 8322 1626 3 7446

1963 3469 2128 267 2428 5160 8322 1899 8249 8322 726 0 7446

2699 3477 2581 311 2435 4989 8322 2091 8189 8322 286 0 7446

2768 3421 2951 303 2511 4714 8272 1896 8120 8322 0 0 7446

Fig. S1. Progression of relevance of solar PV as a function of total generation share for 2020, 2030, 2040 and 2050.

Fig. S2. Progression of relevance of wind power as a function of total generation share for 2020, 2030, 2040 and 2050.

Table S12: Installed capacities of storage systems from 2015 to 2050 Technology A-CAES storage Battery RES Battery COM Battery IND Battery System Battery total PHS storage TES storage A-CAES storage PtSNG el. input Gas storage

Units [GWh] [GWh] [GWh] [GWh] [GWh] [GWh] [GWh] [GWh] [GWh] [GW] [GWh]

2015 0 0 0 0 0 0 48 22 0 0 0

2020

2025

2030

2035

2040

2 72 30 9 0 111 49 23 2 0 5362

13 200 170 173 5 548 88 32 13 0 24979

13 316 285 332 156 1088 88 33 13 0 68267

15 403 372 449 538 1763 88 234 15 4 95766

25 482 446 558 1025 2511 88 290 25 20 141174

2045 119 535 509 651 1434 3128 88 269 119 44 196765

2020 30 0 30 10 4 0 429

2025 140 2 142 19 6 0 465

2030 233 47 281 16 6 0 527

2035 296 149 445 15 38 0 555

2040 349 275 624 16 43 0 570

2045 388 379 767 15 37 3 580

2050 198 581 555 718 1715 3569 88 268 198 45 217330

2050 416 453 869 15 33 5 569

Table S13: Output of storage systems from 2015 to 2050 Technology Battery SC output Battery system output Battery total output PHS output TES output A-CAES output Gas output

Units [TWh] [TWh] [TWh] [TWh] [TWh] [TWh] [TWh]

2015 0 0 0 6 4 0 0

Table S14: Financial results from 2015 to 2050

2015 2020 2025 2030 2035 2040 2045 2050

LCOE [€/MWh]

LCOE primary [€/MWh]

LCOC [€/MWh]

LCOS [€/MWh]

Total annualized cost [b€]

67.3 64.3 65.9 65.7 62.4 59.6 57.0 55.5

66.6 54.2 52.4 48.5 43.1 39.4 37.1 35.5

0.5 1.2 1.3 2.1 2.6 2.8 2.7 2.6

0.2 8.9 12.3 15.0 16.6 17.4 17.3 17.3

269 272 288 299 297 298 299 300

Fig. S3. Annual fixed ((left) and variable (right) operations and maintenance costs (left) from 2015 to 2050 for Europe.

Fig. S4. Curtailed electricity from 2015 to 2050 for Europe.

Fig. S5. Hourly generation profile for a representative winter period (January 1-10) in Sweden in 2050. An example of a country with a high share of hydropower.

Fig. S6. Hourly generation profile for a representative summer period (June 1-10) in Sweden in 2050. An example of a country with a high share of hydropower.

Fig. S7. Hourly generation profile for a representative winter period (January 19-28) in the UK and Ireland in 2050. An example of a country with a high share of wind power.

Fig. S8. Hourly generation profile for a representative summer period (July 23 – August 2) in the UK and Ireland in 2050. An example of a country with a high share of wind power.

Fig. S9. Hourly generation profile for a representative winter period (January 1-10) in Italy in 2050. An example of a country with a high share of solar PV power.

Fig. S10. Hourly generation profile for a representative summer period (June 13-23) in Italy in 2050. An example of a country with a high share of solar PV power.

Fig. S11. Hourly generation profile for a representative winter period (January 18-27) in Germany in 2050. An example of a country with a mix of several renewable resources.

Fig. S12. Hourly generation profile for a representative summer period (June 23 – July 2) in Germany in 2050. An example of a country with a mix of several renewable resources.

Area and Integrated scenario results for 2030 Europe Interconnection in Europe allows for lower overall installed capacities of generation technologies throughout Europe (Figures S13 and S14), again resulting in cost savings. Total capital expenditures in the Area scenario are 143 b€ lower (Table 1) than in the Regions scenario. Likewise, total annualised costs decrease from 250 b€/a in the Regions scenario to 224 b€/a in the Area scenario (-26 b€/a). This is due to less need for biomass (-23 GW) and gas turbine power plants (-72 GW) as well as hydro dams (-21 GW) in the Area scenario. In addition, onshore wind power increases slightly (+34 GW), while total solar PV installed capacity falls (-166 GW). This result suggests a rebalancing of the need for various technologies when interconnection allows effective power transfer between regions. Similarly, a balancing effect was noticed between the wind rich North Sea area and the solar rich Mediterranean area, in particular the Balkans, due to weather regimes that minimise variability between solar and wind (Grams et al. 2017). The authors suggest that pan-European technology deployment strategies take this effect into account. The results of this present study are in line with this conclusion. This effect may be of highest relevance for the UK and Ireland, where balance can be established between the region of lowest cost wind generation and hence excellent wind-based electricity export options, and continental areas with lowest cost solar PV generation to balance wind resource deficit periods with PV electricity. This also maintains high utilisation of power lines between the UK and Ireland, and the continent. Other countries between these regions could have access to both resources. To this end, while energy system policy and planning tends to be national in nature, results of this study indicate that substantial cost savings can be achieved through pan-European cooperation. Nevertheless, interconnections only contribute to 16% of the electricity demand in Europe. Approximately 84% is generated and consumed in the same region, which highlights that the overall energy system is highly decentralised but further optimised by strong interconnectors. Extending interconnections beyond the European regions defined in this study was done in previous work (Bogdanov et al. 2016). Results indicate that the integration of Europe, Eurasia and MENA energy systems could enable greater access to low cost energy generation and storage. While overall costs are reported as being the same as those reported in this study (LCOE of 56 €/MWh for Regions scenario, 51 €/MWh for Area scenario and 50 €/MWh for Integrated scenario), the conclusion is that balancing of variable RE generation over a larger geographical area is most important. However, a further integration with neighbouring major regions, such as Eurasia and MENA, may not necessarily reduce costs significantly. This study finds that Germany in particular can benefit from wind energy imports from neighbouring countries. In addition, Norway can utilise its excellent North Sea wind resources to a greater extent, thereby functioning as a regional electricity hub. This could even be more relevant than the commonly discussed smoothing capabilities of the hydropower resources of Norway.

An important issue related to high levels of interconnection between regions, as well as the transmission capacities needed within each region that support power transfer, is social acceptance. The modelling of Europe with the LUT model assumes that the current state (ENTSO-E 2016) of both high voltage alternating current (HVAC) and high voltage direct current (HVDC) lines (above ground) and cables (below ground or undersea) would be supplemented by future additions of lines and cables in a 30/70 ratio for land-based interconnections. All new undersea connections were assumed to be HVDC cables. These assumptions were made to account for levels of social resistance to visible overhead electricity lines. However, it must be noted that the model results may differ from what would be socially desired in some cases. It is beyond the scope of this work to examine such issues, but they most certainly would need to be part of the overall discourse concerning future energy system development.

Figure S13. Installed generation capacity for a 100% RE Regions scenario for Europe in 2030.

Figure S14. Installed generation capacity for a 100% RE Area scenario for Europe in 2030.

Lastly, results from 2030 simulations suggest that integrating other sectors with the energy system can result in lower LCOE. Specifically, integrating the power demands for non-energetic industrial gas and water desalination can result in cost savings. The LCOE of the Integrated scenario is 5.6 €/MWh lower than for the Regions scenario, again mostly due to lower levelised costs of curtailment and storage (Table 1). Sector integration cost reduction potentials have also been seen in other global studies (Breyer et al. 2017). In addition, several studies have indicated that further savings may be achievable through the integration of both the heat and mobility sectors (Connolly et al. 2016; Mathiesen et al. 2015). The trend towards electrified mobility will further the importance of electricity in the energy system. Moreover, the batteries of electric vehicles offer a significant source of electricity storage and flexibility through smart charging and vehicle-to-grid services. Incorporating these important aspects in energy system modelling is, therefore, an important next step.

References Agora Energiewende. 2014. “Stromspeicher in Der Energiewende.” http://www.speicherinitiative.at/assets/Uploads/19-AgoraEnergiewende-Speicherstudie-Langfassung.pdf. Bogdanov, D., and C. Breyer. 2016. “North-East Asian Super Grid for 100% Renewable Energy Supply: Optimal Mix of Energy Technologies for Electricity, Gas and Heat Supply Options.” Energy Conversion and Management 112: 176–90. doi:10.1016/j.enconman.2016.01.019. Bogdanov, D., O. Koskinen, A. Aghahosseini, and Ch. Breyer. 2016. “Integrated Renewable Energy Based Power System for Europe, Eurasia and MENA Regions.” In 5th International Energy and Sustainability Conference. Cologne, June 30-July 1. Breyer, C., D. Bogdanov, A. Gulagi, A. Aghahosseini, L. Barbosa, O. Koskinen, M. Barasa, et al. 2017. “On the Role of Solar Photovoltaics in Global Energy Transition Scenarios.” Progress in Photovoltaics 25: 727–45. doi:10.1002/pip.2885. Breyer, C., and A. Gerlach. 2013. “Global Overview on Grid-Parity.” Progress in Photovoltaics: Research and Applications. doi:10.1002/pip.1254. Breyer, C., E. Tsupari, V. Tikka, and P. Vainikka. 2015. “Power-to-Gas as an Emerging Profitable Business through Creating an Integrated Value Chain.” In Energy Procedia, 73:182–89. doi:10.1016/j.egypro.2015.07.668. Bunzel, K., V. Zeller, M. Buchhorn, F. Griem, and D. Thrän. 2009. “Regionale Und Globale Räumliche Verteilung von Biomassepotenzialen.” German Biomass Research Center, Leipzig. Carlsson, J. et Al. 2014. Etri 2014. doi:10.2790/057687. Connolly, D., H. Lund, and B. V. Mathiesen. 2016. “Smart Energy Europe: The Technical and Economic Impact of One Potential 100% Renewable Energy Scenario for the European Union.” Renewable and Sustainable Energy Reviews 60: 1634–53. doi:10.1016/j.rser.2016.02.025. Elbersen, B., I. Startisky, G. Hengeveld, M. Schelhaas, and H. Naeff. 2012. “Atlas of EU Biomass Potentials.” https://ec.europa.eu/energy/intelligent/projects/sites/ieeprojects/files/projects/documents/biomass_futures_atlas_of_technical_and_economic_biomass_potential_ en.pdf. ENTSO-E. 2016. “TYNDP 2016 Scenario Development Report.” Brussels. https://www.entsoe.eu/Documents/TYNDP documents/TYNDP 2016/rgips/TYNDP2016 Scenario Development Report - Final.pdf. Farfan, J., and C. Breyer. 2016. “Structural Changes of Global Power Generation Capacity towards Sustainability and the Risk of Stranded Investments Supported by a Sustainability Indicator.” Journal of Cleaner Production 141: 370–84. doi:10.1016/j.jclepro.2016.09.068. Fraunhofer ISE. 2015. “Current and Future Cost of Photovoltaics. Long-Term Scenarios for Market Development, System Prices and LCOE of Utility-Scale PV Systems.” Berlin. http://www.fvee.de/fileadmin/publikationen/weitere_publikationen/15_AgoraEnergiewendeISE_Current_and_Future_Cost_of_PV.pdf.

Gerlach, A., C. Breyer, and C. Werner. 2014. “Impact of Financing Cost on Global Grid-Parity Dynamics till 2030.” In 29th European Photovoltaic Solar Energy Conference. Amsterdam, September 22-26. doi:10.4229/29thEUPVSEC2014-7DO.15.4. Grams, C.M., R. Beerli, S. Pfenninger, I. Staffell, and H. Wernli. 2017. “Balancing Europe’s Wind-Power Output through Spatial Deployment Informed by Weather Regimes.” Nature Climate Change. doi:10.1038/nclimate3338. Haysom, J., O. Jafarieh, H. Anis, K. Hinzer, and D. Wright. 2015. “Learning Curve Analysis of Concentrated Photovoltaic Systems.” Progress in Photovoltaics: Research and Applications. doi:10.1002/pip.2567. International Energy Agency. 2014. “World Energy Investment Outlook.” Paris. doi:10.1049/ep.1977.0180. Kutscher, C., M. Mehos, C. Turchi, G. Glatzmaier, and T. Moss. 2010. “Line-Focus Solar Power Plant Cost Reduction Plan.” Vol. NREL/TP-55. Colorado. https://www.nrel.gov/docs/fy11osti/48175.pdf. Mathiesen, B. V., H. Lund, D. Connolly, H. Wenzel, P. A. Ostergaard, B. Möller, S. Nielsen, et al. 2015. “Smart Energy Systems for Coherent 100% Renewable Energy and Transport Solutions.” Applied Energy 145: 139–54. doi:10.1016/j.apenergy.2015.01.075. Neij, L. 2008. “Cost Development of Future Technologies for Power Generation-A Study Based on Experience Curves and Complementary Bottom-up Assessments.” Energy Policy 36 (6): 2200–2211. doi:10.1016/j.enpol.2008.02.029. Pleßmann, G., M. Erdmann, M. Hlusiak, and C. Breyer. 2014. “Global Energy Storage Demand for a 100% Renewable Electricity Supply.” Energy Procedia 46. Elsevier B.V.: 22–31. doi:10.1016/j.egypro.2014.01.154. Sigfusson, B., and A. Uihlein. 2015. 2014 JRC Geothermal Energy Status Report. JRC Science and Policy Reports. doi:10.2790/460251. Vartiainen, E., G. Masson, and C. Breyer. 2015. “PV LCOE in Europe 2015 - 2050.” In 31st European Photovoltaic Solar Energy Conference. Hamburg.