Wind Power Electricity: the bigger the turbine, the ... - BioMedSearch
Wind Power Electricity: the bigger the turbine, the greener the electricity? MARLOES CADUFF,*,†,‡ MARK A. J. HUIJBREGTS, § HANS-JOERG ALTHAUS, †ANNETTE KOEHLER†, STEFANIE HELLWEG† †
ETH Zurich, Institute of Environmental Engineering, CH-8093 Zurich, Switzerland, ‡ Empa, Swiss Federal Laboratories for Materials Testing and Research, Technology and Society Laboratory, Ueberlandstrasse 129, CH-8600 Duebendorf, Switzerland, and § Department of
Environmental Science, Institute for Wetland and Water Research, Faculty of Science, Radboud University Nijmegen, P.O. Box 9010, NL-6500 GL Nijmegen, The Netherlands [email protected] Received date Corresponding author phone: +41 44 823 48 12; fax: +41 44 823 40 42; e-mail: [email protected].
S1
Supporting Information Modeling Table S1 Modeling assumptions for the use phase of the wind turbine
Source
Year of study
1
2008 2000 2009 2009 2009 2006 2007 2007 2007 2007 2000 2003
2 3 3 4 5 6 6 6 6 7 8
Rated power [kW] 660 500 850 3000 2000 1650 30 150 600 800 600 1500
Life span 20 20 20 20 20 20 20 20 20 20 25 20
Oil changing cycle [years] 2 2 1 1 1 1 4 4 2 1 2 1
Amount of oil/life cycle [kg] 840 638 1079 3788 2528 2087 84 168 714 1058 955 1898
Transport, pass. car, 1p 50km [tkm] 500 500 1000 1000 1000 1000 250 250 500 1000 550 1000
Table S2 Modeling assumptions for the end of life phase of the wind turbines Element
Disposal process
Cables Electronics Foundation
Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, concrete, 5% water, to inert material landfill/CH Disposal, steel, 0% water, to inert material landfill/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, used mineral oil, 10% water, to hazardous waste incineration/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, used mineral oil, 10% water, to hazardous waste incineration/CH Disposal, used mineral oil, 10% water, to hazardous waste incineration/CH
Nacelle Rotor Turbine Used oil
Aluminum, iron, steel (with the exception of reinforcing steel in the foundation) and copper were assumed to be recycled and modeled as cut-off processes. According to the cut-off approach, e.g. followed in the ecoinvent database v2 that was used for background data in this paper, environmental burdens of the recycling processes are allocated to processes using the secondary materials and are thus not included in the LCA of the wind turbines. 9 S2
Life Cycle Inventories Rotor. The rotors mainly consist of glass fiber reinforced plastic, steel and iron components.
Table S3 LCI of the rotors Source Rated power Glass fibre reinforced plastic, polyamide, injection moulding, at plant /RER Chromium steel 18/8, at plant /RER Sheet rolling, chromium steel /RER Cast iron, at plant/RER Section bar rolling, steel/RER Aluminium, production mix, at plant, RER Sheet rollling, aluminium/RER Epoxy resin, liquid, at plant/RER Chemicals organic, at plant /GLO Polyethylene, HDPE, granulate, at plant/RER Extrusion, plastic pipes/RER Nylon 66, at plant/RER PVC, at regional storage/RER Extrusion, plastic pipes/RER Foaming, expanding/RER Synthetic rubber, at plant/RER Transport, lorry >32t, EURO4/RER Transport, freight, rail/RER
kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg tkm tkm
3
3
4
5
6
6
6
6
7
8
850 kW 3010
3000 kW 12040
2000 kW 19810
1650 kW 25200
30 kW 146
150 kW 2500
600 kW 5880
800 kW 8400
600 kW 5750
1500 kW 6564
4980 4980
19930 19930
138 138 79 79
662 662 379 379
3900 3900 4200 4200
3100 3100 3200 3200
2500 2500
14000 14000
5700 5700 11300 11300
250 250
1598 7990
6394 31970
6762 33810
8440 42200
72.6 363
708.2 3541
2796 13980
2940 14700
99 99 5100 1575 684 912 228 1230 393 837 165 3129 15645
1700 8500
Nacelle. The rotors mainly consist of glass fiber reinforced plastic, steel and iron components.
Table S4 LCI of the nacelle Source Rated power Aluminium, production mix, at plant, RER Sheet rollling, aluminium/RER Chromium steel 18/8, at plant /RER Sheet rolling, chromium steel /RER Copper, at regional storage/RER Wire drawing, copper/RER Polyethylene, HDPE, granulate, at plant/RER Extrusion, plastic pipes/RER Lubricating oil, at plant /RER Cast iron, at plant/RER Section bar rolling, steel/RER Glass fibre reinforced plastic, polyamide, injection Moulding, at plant /RER Epoxy resin, liquid, at plant/RER MG-Silicon, at plant /NO Steel, low-alloyed, at plant/RER Section bar rolling, steel/RER Sheet rolling, steel/RER Polyester resin, unsaturated, at plant/RER Synthetic rubber, at plant/RER Transport, lorry >32t, EURO4/RER Transport, freight, rail/RER
kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg tkm tkm
3
3
4
5
6
6
6
6
7
8
850 kW 419 419 20194 20194 789 789 180 180 134
3000 kW 1621 1621 61000 61000 3051 3051 700 700 485
2000 kW
1650 kW 500 500 20800 20800 1600 1600 1000 1000 300 18000 18000 1800
30 kW 14.7 14.7 598.45 598 17 17
150 kW 70.6 70.6 2872 2872 81 81
600 kW 204 204 13880 13880 238 238
800 kW 207 207 11426 11426 242 242
1500 kW 127 127 24052 24052 9281 9281
10 189 189 60
57 907 907 288
50.4 3067 3067 1261
58.8 3279 3279 1261
600 kW 1600 1600 16350 16350 1000 1000 50 50 94
21690 21690 3500 3500
322 18500 18500 2000
750
240 21027 21027 924 654
350
4343 21716
13371 66857
9272 46362
6300 6300
49 49
235 235
2650 2650
3685 3685
10060 50300
3.2 188 941
15 905 4526
100 4290 21450
100 4052 20259
32065 12809 19256 2159 3969 19844
18106 90529
S3
Tower. Zinc coating was only included in (Burger and Bauer 2007). However it was assumed that all steel towers were zinc coated and the coating was added everywhere. Zinc coating was parameterized as a function of hub height (h). Welding arc was modeled as 3.8h. Zinc coating (ZC) pieces was modeled linear with hub height according to the 4 turbines from (Burger and Bauer 2007), hence ZC (m) = 25h 491, R2=0.96 was used.
Table S5 LCI of the towers Source Rated power
3
3
4
5
6
6
6
6
7
8
3000 kW 1240 158760 158760 3.8h 25h 491 20ZC
2000 kW 0 143000 143000 3.8h 25h 491 20ZC
1650 kW 0 126100 126100 3.8h 25h 491 20ZC
30 kW 37 5299 5299 3.8h 25h 491 20ZC
150 kW 95 15019 15019 3.8h 25h 491 20ZC
600 kW 144 38900 38900 3.8h 25h 491 20ZC
800 kW 360 69375 69375 3.8h 25h 491 20ZC
600 kW 250 37000 37000 3.8h 25h 491 20ZC
1500 kW 4217 148877 148877 3.8h 25h 491 20ZC
Epoxy resin, liquid, at plant Steel low-alloyed, at plant Sheet rolling, steel Welding arc, steel Zinc coating, pieces (ZC)
kg kg kg m m2
Zinc coating, pieces, adjustment per um Transport, lorry >32t, EURO4/RER Transport, freight, rail/RER
m2
850 kW 930 69070 69070 3.8h 25h 491 20ZC
tkm
14000
32000
28600
25220
1067
3023
7809
13947
7450
30619
tkm
70000
160000
143000
126100
5336
15114
39044
69735
37250
153094
Foundation. Land transformation and occupation was not included in many studies and was added. Transformation to traffic area was assumed independent of turbine size, with an area of 1000 m2. Occupation of the road was assumed with the life time of the turbine, 20a. The occupation and transformation of the tower base area, depends on base sizes. These were estimated by the 5 given foundation sizes: A (m2) = 4h – 89, R2=0.88. Transport lorry: 50 km for concrete, 100 km for plastics, steel and iron. Transport train: 200 km for plastics, steel and iron.
Table S6 LCI of the foundations 1
2
3
3
4
5
6
6
6
6
7
8
m3 kg
660 kW 155 3.8
500 kW 119
850 kW 202
3000 kW 479
2000 kW 294
1650 kW 338
30 kW 23
150 kW 23
600 kW 82
800 kW 102
600 kW 18
1500 kW 348
kg
45
kg kg kg m2
49 11100
12000
15000
36000
1110
1074
1147
m2
1000
1000
m2
110
m2a m2a
Source Rated power Concrete, normal, at plant Polyethylene, HDPE, granulate, at plant Polyvinylchloride, at regional storage Extrusion, plastic film Reinforcing steel, at plant Cast iron, at plant Transformation, from pasture and meadow Transformation, to traffic area, road network Transformation, to industrial area, built up Occupation, traffic area, road network Occupation, industrial area,
166
27000
2367
2367
11200
14000
4735
166 24000
1226
15000 25000 1175
1226
1004
1004
1091
1121
1049
1175
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
74
147
226
175
226
4
4
91
121
49
175
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
2205
1486
2944
4521
3496
4521
80
80
1820
2420
973
3496
S4
built up Transport, lorry >32t, EURO4/RER Transport, freight, rail/RER
tkm
19595
15325
25500
60600
39000
42950
2998
2998
10854
13538
2635
43817
tkm
2230
2400
3000
7200
8000
5400
473
473
2240
2800
947
4833
Cables and electronics. Cables have a copper core and are PVC coated with a thickness of 1mm and HDPE outside coating with 2.5 mm thickness. Additional 20 kg PP, granulate was used. Cables inside tower were dependent on hub height (h). It was assumed that there were 3 inside cables with a crosssection, A of 640 mm2. The cables from the tower base to the grid were independent of turbine size. Assumptions were: 3 outside cables with a cross-section, A of 50 mm2 and distance to the grid of 1000 m.
Table S7 LCI of the electronic cables adapted from (LIT), used in all turbine configurations Unit process Copper, at regional storage Wire drawing, copper PVC, at regional storage Polyethylene, HDPE, granulate, at plant PP, granulate, at plant Extrusion, plastic pipes Transport, lorry 16-32t, EURO4/RER Transport, freight, rail/RER
Unit kg kg kg kg kg kg tkm tkm
Outside cables 1338 1338 79 186 20 285 325 1623
Parameterization 3A ρ h 3A ρ h
/ 200 1000
The electronic box was assumed the same for all turbine sizes.
Table S8
LCI of the electronics box adapted from Martinez, 2009 used in all turbine
configurations.4 Unit process Copper, at regional storage Wire drawing, copper Tin, at regional storage Steel, low-alloyed, at plant Section bar rolling, steel Lead, at regional storage Aluminium, primary, at plant Sheet rolling, aluminium PVC, at regional storage Polyethylene, HDPE, granulate, at plant Extrusion, plastic pipes Transport, lorry 16-32t, EURO4/RER Transport, freight, rail/RER
Unit kg kg kg kg kg kg kg kg kg kg kg tkm tkm
Amount 3 3 0.5 63 63 0.5 0.04 0.04 6 27 33 20 100
Transport. Transport is modeled consistently throughout all inventories as: • •
100 km, lorry raw materials to plant 100 km, lorry, plant to erection site S5
• •
200 km, train raw materials to plant 800 km, train, plant to erection site
Densities used in the study were: • • • •
1400 kg/m3 950 kg/m3 8920 kg/m3 2380 kg/m3
PVC HDPE Copper Concrete, normal
Table S9 Additional results for scaling factor b and intercept a for ReCiPe impact categories versus D2h3/7 using the ordinary least squares regression technique. 95% CI: 95% confidence interval; R2: coefficient of determination; SE: standard error; n: number of observations. Impact category
Unit
log a (95% CI)
b (95% CI)
R2
SE
n
Ozone depletion
kg CFC-11 eq/kWh
-8.15 (-8.48 – -7.83)
-0.22 (-0.16 – -0.30)
0.79
0.066
12
Human toxicity
kg 1,4-DB eq/kWh
0.66 (0.01 – 1.32)
-0.55 (-0.42 – -0.72)
0.85
0.134
12
Photochemical oxidant formation
kg NMVOC/kWh
-3.14 (-3.55 – -2.72)
-0.28 (-0.20 – -0.39)
0.79
0.084
12
Particulate matter formation
kg PM10 eq/kWh
-3.08 (-3.49 – -2.67)
-0.30 (-0.22 – -0.41)
0.81
0.084
12
Ionising radiation
kg U235 eq/kWh
-1.65 (-2.01 – -1.28)
-0.23 (-0.17 – -0.33)
0.77
0.075
12
Terrestrial acidification
kg SO2 eq/kWh
-2.61 (-3.06 – -2.16)
-0.37 (-0.28 – -0.49)
0.85
0.092
12
Freshwater eutrophication
kg P eq/kWh
-2.75 (-3.35 – -2.15)
-0.51 (-0.39 – -0.67)
0.86
0.123
12
Marine eutrophication
kg N eq/kWh
-4.08 (-4.52 – -3.64)
-0.30 (-0.22 – -0.41)
0.79
0.089
12
Terrestrial ecotoxicity
kg 1,4-DB eq/kWh
-3.95 (-4.38 – -3.52)
-0.40 (-0.31 – -0.51)
0.88
0.087
12
Marine ecotoxicity
kg 1,4-DB eq/kWh
-1.57 (-2.05 – -1.08)
-0.40 (-0.30 – -0.52)
0.85
0.098
12
Agricultural land occupation
m2a/kWh
-2.54 (-2.88 – -2.19)
-0.24 (-0.17 – -0.33)
0.79
0.070
12 12
Natural land transformation
m2/kWh
-4.75 (-5.20 – -4.30)
-0.28 (-0.20 – -0.39)
0.76
0.092
Water depletion
m3/kWh
-2.78 (-3.11 – -2.45)
-0.25 (-0.19 – -0.34)
0.82
0.068
12
Fossil depletion
kg oil eq/kWh
-1.47 (-1.85 – -1.09)
-0.22 (-0.15 – -0.31)
0.73
0.078
12
Environmental progress rates Table S10 Wind power turbine production in EU.10 Year
Installed wind power per year (MW/a)
1990
Cumulative installed power in the EU (MW) 439
1991
190
629
1992
215
844
1993
367
1211
1994
472
1683
1995
814
2497
1996
979
3476
S6
1996
979
3476
1997
1277
4753
1998
1700
6453
1999
3225
9678
2000
3209
12887
2001
4428
17315
2001
4428
17315
2002
5913
23228
2003
5462
28690
2004
5838
34528
2005
6204
40732
2006
7592
48324
2007
8535
56859
2008
8484
65343
Table S11
Environmental progress rates (EPR) versus cumulative production. Results for
ReCiPe impact categories using the ordinary least squares regression technique. 95% CI: 95% confidence interval; n: number of observations; R2: coefficient of determination. R2
Impact category
Unit
log a (95% CI)
b (95% CI)
n
Climate change
kg CO2 eq/kWh
-0.97 (-1.30 – -0.64)
-0.22 (-0.15 – -0.31)
10 0.81
EPR 86%
Ozone depletion
kg CFC-11 eq/kWh
-8.20 (-8.51 – -7.89)
-0.22 (-0.15 – -0.30)
10 0.82
86%
Human toxicity
kg 1,4-DB eq/kWh
0.51 (-0.20 – 1.21)
-0.54 (-0.39 – -0.74)
10 0.85
69%
Photochemical oxidant formation
kg NMVOC/kWh
-3.20 (-3.59 – -2.80)
-0.28 (-0.20 – -0.39)
10 0.82
83%
Particulate matter formation
kg PM10 eq/kWh
-3.15 (-3.52 – -2.77)
-0.30 (-0.22 – -0.40)
10 0.86
81%
Ionising radiation
kg U235 eq/kWh
-1.68 (-2.00 – -1.36)
-0.23 (-0.17 – -0.32)
10 0.84
85%
Terrestrial acidification
kg SO2 eq/kWh
-2.71 (-3.16 – -2.26)
-0.36 (-0.27 – -0.49)
10 0.86
78%
Freshwater eutrophication
kg P eq/kWh
-2.89 (-3.54 – -2.25)
-0.50 (-0.37 – -0.68)
10 0.85
71%
Marine eutrophication
kg N eq/kWh
-4.18 (-4.63 – -3.72)
-0.29 (-0.20 – -0.41)
10 0.80
83%
Terrestrial ecotoxicity
kg 1,4-DB eq/kWh
-4.06 (-4.49 – -3.63)
-0.39 (-0.30 – -0.51)
10 0.89
76%
Freshwater ecotoxicity
kg 1,4-DB eq/kWh
-1.76 (-2.18 – -1.33)
-0.38 (-0.28 – -0.49)
10 0.88
77%
Marine ecotoxicity
kg 1,4-DB eq/kWh
-1.68 (-2.11 – -1.24)
-0.39 (-0.29 – -0.51)
10 0.88
76%
Agricultural land occupation
m2a/kWh
-2.57 (-2.89 – -2.25)
-0.24 (-0.17 – -0.33)
10 0.84
85%
Urban land occupation
m2a/kWh
0.19 (-0.50 – 0.88)
-0.80 (-0.65 – -0.99)
10 0.93
57%
Natural land transformation
m2/kWh
-4.80 (-5.24 – -4.37)
-0.28 (-0.19 – -0.40)
10 0.80
83%
Water depletion
m3/kWh
-2.84 (-3.18 – -2.51)
-0.25 (-0.18 – -0.34)
10 0.84
84%
Metal depletion
kg Fe eq/kWh
-0.31 (-0.71 – 0.09)
-0.34 (-0.25 – -0.45)
10 0.87
79%
Fossil depletion
kg oil eq/kWh
-1.51 (-1.87 – -1.14)
-0.22 (-0.15 – -0.32)
10 0.77
86%
Sensitivity analysis S7
Table S12 Results of the sensitivity analysis of assumed wind speed. The maximum captured power at wind speed v1A = 5 m/s and v1B = 15m/s. Source
Rated power [kW]
Maximum captured power, Pcaptured, max [kW] v1A = 5 m/s
v1B = 15 m/s
1
660
219
5920
2
500
98
2638
3
850
203
5493
3
3000
689
18612
4
2000
480
12957
5
1650
545
14706
6
30
8
206
6
150
32
855
6
600
117
3157
6
800
174
4696
7
600
116
3121
8
1500
344
9277
Table S13 Results for scaling factor b and intercept a for ReCiPe impact categories versus D2h3/7 using a wind speed of v2 = 15m/s. 95% CI: 95% confidence interval; R2: coefficient of determination; SE: standard error; n: number of observations. Impact category
Unit
log a (95% CI)
b (95% CI)
n
SE
R2
Climate change
kg CO2 eq/kWh
-2.36 (-2.70 – -2.02)
-0.22 (-0.16 – -0.31)
12 0.070
0.77
Ozone depletion
kg CFC-11 eq/kWh
-9.58 (-9.91 – -9.26)
-0.22 (-0.16 – -0.30)
12 0.066
0.79
Human toxicity
kg 1,4-DB eq/kWh
-0.77 (-1.43 – -0.11)
-0.55 (-0.42 – -0.72)
12 0.134
0.85
Photochemical oxidant formation
kg NMVOC/kWh
-4.57 (-4.98 – -4.16)
-0.28 (-0.20 – -0.39)
12 0.084
0.79
Particulate matter formation
kg PM10 eq/kWh
-4.51 (-4.93 – -4.10)
-0.30 (-0.22 – -0.41)
12 0.084
0.81
Ionising radiation
kg U235 eq/kWh
-3.08 (-3.44 – -2.71)
-0.23 (-0.17 – -0.33)
12 0.075
0.77
Terrestrial acidification
kg SO2 eq/kWh
-4.04 (-4.49 – -3.59)
-0.37 (-0.28 – -0.49)
12 0.092
0.85
Freshwater eutrophication
kg P eq/kWh
-4.18 (-4.78 – -3.58)
-0.51 (-0.39 – -0.67)
12 0.123
0.86
Marine eutrophication
kg N eq/kWh
-5.51 (-5.95 – -5.07)
-0.30 (-0.22 – -0.41)
12 0.089
0.79
Terrestrial ecotoxicity
kg 1,4-DB eq/kWh
-5.39 (-5.82 – -4.96)
-0.40 (-0.31 – -0.51)
12 0.087
0.88
Freshwater ecotoxicity
kg 1,4-DB eq/kWh
-3.09 (-3.56 – -2.61)
-0.39 (-0.29 – -0.51)
12 0.097
0.84
Marine ecotoxicity
kg 1,4-DB eq/kWh
-3.00 (-3.48 – -2.51)
-0.40 (-0.30 – -0.52)
12 0.098
0.85
Agricultural land occupation
m2a/kWh
-3.97 (-4.31 – -3.62)
-0.24 (-0.17 – -0.33)
12 0.070
0.79
Urban land occupation
m2a/kWh
-0.85 (-1.02 – -0.67)
-0.87 (-0.82 – -0.91)
12 0.036
0.995
Natural land transformation
m2/kWh
-6.18 (-6.63 – -5.73)
-0.28 (-0.20 – -0.39)
12 0.092
0.76
Water depletion
m3/kWh
-4.21 (-4.55 – -3.88)
-0.25 (-0.19 – -0.34)
12 0.068
0.82
Metal depletion
kg Fe eq/kWh
-1.65 (-2.11 – -1.20)
-0.35 (-0.26 – -0.46)
12 0.093
0.83
Fossil depletion
kg oil eq/kWh
-2.90 (-3.28 – -2.52)
-0.22 (-0.15 – -0.31)
12 0.078
0.73
S8
Calculation of the scaling factor of generator efficiency According to previous work, efficiency (ε) is expected to scale with power according to a scaling law.11 Minimum (91.6% for a generator in a 20kW turbine) and average generator efficiency (94%) were reported in literature. 12, 13 The difference between the minimum and the average efficiency was 2.4%. The maximum efficiency was defined as 96.4% (94% + 2.4%) and was allocated to the largest turbine in the study (655kW). With these estimations, a power law with the following function was derived: ε = 0.88 P0.014 This power law was used to scale the efficiency as well as the electric power output Pel of the wind turbine (see Table S14). The deviation between the scaled Pel and the non-scaled Pel could then be calculated.
Table S14 Results of the sensitivity analysis of scaling the generator efficiency versus a constant generation efficiency of 94%. Source
Rated power [kW]
Scaled efficiency Pel with scaled efficiency [kW]
Pel with average efficiency of 94% [kW]
Deviation
1
660
0.955
199
208
-1.6%
2
500
0.944
88
93
-0.4%
3
850
0.954
184
193
-1.5%
3
3000
0.964
631
655
-2.6%
4
2000
0.965
440
456
-2.7%
5
1650
0.967
500
517
-2.9%
6
30
0.916
7
7
2.6%
6
150
0.929
28
30
1.2%
6
600
0.946
105
111
-0.7%
6
800
0.952
157
165
-1.2%
7
600
0.946
104
110
-0.7%
8
1500
0.961
314
326
-2.2%
Table S15 Exponent b and intercept a for non-renewable cumulative energy demand (CED and IMPACT2002+ impact categories versus D2h3/7 using the ordinary least squares regression technique. 95% CI: 95% confidence interval; R2: coefficient of determination; SE: standard error; n: number of observations.
S9
Impact category
Unit
log a (95% CI)
b (95% CI)
R2
SE
n
Non-renewable CED
MJ/kWh
0.79 (0.41 – 1.17)
-0.23 (-0.16 – -0.33)
0.75
0.077
12
IMPACT 2002+
Pt./kWh
-3.39 (-3.77 – -3.02)
-0.31 (-0.24 – -0.41)
0.85
0.076
12
Literature Cited (1) Ardente, F.; Beccali, M.; Cellura, M.; Lo Brano, V. Energy performances and life cycle assessment of an Italian wind farm. Renew. Sust. Energ. Rev. 2008, 12 (1), 200-217. (2) Schleisner, L. Life cycle assessment of a wind farm and related externalities. Renew. Energ. 2000, 20 (3), 279288. (3) Crawford, R. H. Life cycle energy and greenhouse emissions analysis of wind turbines and the effect of size on energy yield. Renew. Sust. Energ. Rev. 2009, 13, 2653-2660. (4) Martinez, E.; et al. Life-cycle assessment of a 2-MW rated power wind turbine: CML method. Int. J. LCA. 2009, 14 (1), 52-63. (5) Life cycle assessment of electricity producede from onshore sited wind power plants based on Vestas V82-1.65 MW turbines; Vestas, 2006. (6) Burger, B.; Bauer, C. Final report ecoinvent No. 6-XIII. In Sachbilanzen von Energiesystemen: Grundlagen für den ökologischen Vergleich von Energiesystemen und den Einbezug von Energiesystemen in Ökobilanzen für die Schweiz;R. Dones, Editor. Paul Scherrer Institut Villigen, Swiss Centre for Life Cycle Inventories: Dübendorf, CH, 2007. (7) McCulloch, M.; Raynolds, M.; Laurie, M. Life-Cycle Value Assessment of a Wind Turbine; Pembina Institute for Appropriate Development: Alberty, Canada, 2000. (8) Chataignere, A.; Boulch, D. L. E. ECLIPSE - Wind turbine (WT) systems - Final report. 2003. (9) ecoinvent Centre, ecoinvent data v2.0. ecoinvent reports No. 1-25. 2007, Swiss Centre for Life Cycle Inventories, Duebendorf, Switzerland. Retrieved from www.ecoinvent.org. (10) Wind map 2008; European Wind Energy Association EWEA, 2008; www.ewea.org/index.php?id=1665. (11) Caduff, M.; Hujbregts, M. A. J.; Althaus, H.-J.; Hendriks, A. J. Power-Law Relationships for Estimating Mass, Fuel Consumption and Costs of Energy Conversion Equipments. Environ. Sci. Technol. 2011, 45 (2), 751-761. (12) Hau, E. Wind turbines fundamentals, technologies, application, economics. 2nd ed.; Springer: Berlin, 2005. (13) Wu, W.; Ramsden, V. S.; Crawford, T.; Hill, G. A low speed, high-torque, direct-drive permanent magnet generator for wind turbines. In Industry Applications Conference, 2000 Vol.1.; Rome, Italy, 2000.
S10
ETH Zurich, Institute of Environmental Engineering, CH-8093 Zurich, Switzerland, ‡ Empa, Swiss Federal Laboratories for Materials Testing and Research, Technology and Society Laboratory, Ueberlandstrasse 129, CH-8600 Duebendorf, Switzerland, and § Department of
Environmental Science, Institute for Wetland and Water Research, Faculty of Science, Radboud University Nijmegen, P.O. Box 9010, NL-6500 GL Nijmegen, The Netherlands [email protected] Received date Corresponding author phone: +41 44 823 48 12; fax: +41 44 823 40 42; e-mail: [email protected].
S1
Supporting Information Modeling Table S1 Modeling assumptions for the use phase of the wind turbine
Source
Year of study
1
2008 2000 2009 2009 2009 2006 2007 2007 2007 2007 2000 2003
2 3 3 4 5 6 6 6 6 7 8
Rated power [kW] 660 500 850 3000 2000 1650 30 150 600 800 600 1500
Life span 20 20 20 20 20 20 20 20 20 20 25 20
Oil changing cycle [years] 2 2 1 1 1 1 4 4 2 1 2 1
Amount of oil/life cycle [kg] 840 638 1079 3788 2528 2087 84 168 714 1058 955 1898
Transport, pass. car, 1p 50km [tkm] 500 500 1000 1000 1000 1000 250 250 500 1000 550 1000
Table S2 Modeling assumptions for the end of life phase of the wind turbines Element
Disposal process
Cables Electronics Foundation
Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, concrete, 5% water, to inert material landfill/CH Disposal, steel, 0% water, to inert material landfill/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, used mineral oil, 10% water, to hazardous waste incineration/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH Disposal, used mineral oil, 10% water, to hazardous waste incineration/CH Disposal, used mineral oil, 10% water, to hazardous waste incineration/CH
Nacelle Rotor Turbine Used oil
Aluminum, iron, steel (with the exception of reinforcing steel in the foundation) and copper were assumed to be recycled and modeled as cut-off processes. According to the cut-off approach, e.g. followed in the ecoinvent database v2 that was used for background data in this paper, environmental burdens of the recycling processes are allocated to processes using the secondary materials and are thus not included in the LCA of the wind turbines. 9 S2
Life Cycle Inventories Rotor. The rotors mainly consist of glass fiber reinforced plastic, steel and iron components.
Table S3 LCI of the rotors Source Rated power Glass fibre reinforced plastic, polyamide, injection moulding, at plant /RER Chromium steel 18/8, at plant /RER Sheet rolling, chromium steel /RER Cast iron, at plant/RER Section bar rolling, steel/RER Aluminium, production mix, at plant, RER Sheet rollling, aluminium/RER Epoxy resin, liquid, at plant/RER Chemicals organic, at plant /GLO Polyethylene, HDPE, granulate, at plant/RER Extrusion, plastic pipes/RER Nylon 66, at plant/RER PVC, at regional storage/RER Extrusion, plastic pipes/RER Foaming, expanding/RER Synthetic rubber, at plant/RER Transport, lorry >32t, EURO4/RER Transport, freight, rail/RER
kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg tkm tkm
3
3
4
5
6
6
6
6
7
8
850 kW 3010
3000 kW 12040
2000 kW 19810
1650 kW 25200
30 kW 146
150 kW 2500
600 kW 5880
800 kW 8400
600 kW 5750
1500 kW 6564
4980 4980
19930 19930
138 138 79 79
662 662 379 379
3900 3900 4200 4200
3100 3100 3200 3200
2500 2500
14000 14000
5700 5700 11300 11300
250 250
1598 7990
6394 31970
6762 33810
8440 42200
72.6 363
708.2 3541
2796 13980
2940 14700
99 99 5100 1575 684 912 228 1230 393 837 165 3129 15645
1700 8500
Nacelle. The rotors mainly consist of glass fiber reinforced plastic, steel and iron components.
Table S4 LCI of the nacelle Source Rated power Aluminium, production mix, at plant, RER Sheet rollling, aluminium/RER Chromium steel 18/8, at plant /RER Sheet rolling, chromium steel /RER Copper, at regional storage/RER Wire drawing, copper/RER Polyethylene, HDPE, granulate, at plant/RER Extrusion, plastic pipes/RER Lubricating oil, at plant /RER Cast iron, at plant/RER Section bar rolling, steel/RER Glass fibre reinforced plastic, polyamide, injection Moulding, at plant /RER Epoxy resin, liquid, at plant/RER MG-Silicon, at plant /NO Steel, low-alloyed, at plant/RER Section bar rolling, steel/RER Sheet rolling, steel/RER Polyester resin, unsaturated, at plant/RER Synthetic rubber, at plant/RER Transport, lorry >32t, EURO4/RER Transport, freight, rail/RER
kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg kg tkm tkm
3
3
4
5
6
6
6
6
7
8
850 kW 419 419 20194 20194 789 789 180 180 134
3000 kW 1621 1621 61000 61000 3051 3051 700 700 485
2000 kW
1650 kW 500 500 20800 20800 1600 1600 1000 1000 300 18000 18000 1800
30 kW 14.7 14.7 598.45 598 17 17
150 kW 70.6 70.6 2872 2872 81 81
600 kW 204 204 13880 13880 238 238
800 kW 207 207 11426 11426 242 242
1500 kW 127 127 24052 24052 9281 9281
10 189 189 60
57 907 907 288
50.4 3067 3067 1261
58.8 3279 3279 1261
600 kW 1600 1600 16350 16350 1000 1000 50 50 94
21690 21690 3500 3500
322 18500 18500 2000
750
240 21027 21027 924 654
350
4343 21716
13371 66857
9272 46362
6300 6300
49 49
235 235
2650 2650
3685 3685
10060 50300
3.2 188 941
15 905 4526
100 4290 21450
100 4052 20259
32065 12809 19256 2159 3969 19844
18106 90529
S3
Tower. Zinc coating was only included in (Burger and Bauer 2007). However it was assumed that all steel towers were zinc coated and the coating was added everywhere. Zinc coating was parameterized as a function of hub height (h). Welding arc was modeled as 3.8h. Zinc coating (ZC) pieces was modeled linear with hub height according to the 4 turbines from (Burger and Bauer 2007), hence ZC (m) = 25h 491, R2=0.96 was used.
Table S5 LCI of the towers Source Rated power
3
3
4
5
6
6
6
6
7
8
3000 kW 1240 158760 158760 3.8h 25h 491 20ZC
2000 kW 0 143000 143000 3.8h 25h 491 20ZC
1650 kW 0 126100 126100 3.8h 25h 491 20ZC
30 kW 37 5299 5299 3.8h 25h 491 20ZC
150 kW 95 15019 15019 3.8h 25h 491 20ZC
600 kW 144 38900 38900 3.8h 25h 491 20ZC
800 kW 360 69375 69375 3.8h 25h 491 20ZC
600 kW 250 37000 37000 3.8h 25h 491 20ZC
1500 kW 4217 148877 148877 3.8h 25h 491 20ZC
Epoxy resin, liquid, at plant Steel low-alloyed, at plant Sheet rolling, steel Welding arc, steel Zinc coating, pieces (ZC)
kg kg kg m m2
Zinc coating, pieces, adjustment per um Transport, lorry >32t, EURO4/RER Transport, freight, rail/RER
m2
850 kW 930 69070 69070 3.8h 25h 491 20ZC
tkm
14000
32000
28600
25220
1067
3023
7809
13947
7450
30619
tkm
70000
160000
143000
126100
5336
15114
39044
69735
37250
153094
Foundation. Land transformation and occupation was not included in many studies and was added. Transformation to traffic area was assumed independent of turbine size, with an area of 1000 m2. Occupation of the road was assumed with the life time of the turbine, 20a. The occupation and transformation of the tower base area, depends on base sizes. These were estimated by the 5 given foundation sizes: A (m2) = 4h – 89, R2=0.88. Transport lorry: 50 km for concrete, 100 km for plastics, steel and iron. Transport train: 200 km for plastics, steel and iron.
Table S6 LCI of the foundations 1
2
3
3
4
5
6
6
6
6
7
8
m3 kg
660 kW 155 3.8
500 kW 119
850 kW 202
3000 kW 479
2000 kW 294
1650 kW 338
30 kW 23
150 kW 23
600 kW 82
800 kW 102
600 kW 18
1500 kW 348
kg
45
kg kg kg m2
49 11100
12000
15000
36000
1110
1074
1147
m2
1000
1000
m2
110
m2a m2a
Source Rated power Concrete, normal, at plant Polyethylene, HDPE, granulate, at plant Polyvinylchloride, at regional storage Extrusion, plastic film Reinforcing steel, at plant Cast iron, at plant Transformation, from pasture and meadow Transformation, to traffic area, road network Transformation, to industrial area, built up Occupation, traffic area, road network Occupation, industrial area,
166
27000
2367
2367
11200
14000
4735
166 24000
1226
15000 25000 1175
1226
1004
1004
1091
1121
1049
1175
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
74
147
226
175
226
4
4
91
121
49
175
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
2205
1486
2944
4521
3496
4521
80
80
1820
2420
973
3496
S4
built up Transport, lorry >32t, EURO4/RER Transport, freight, rail/RER
tkm
19595
15325
25500
60600
39000
42950
2998
2998
10854
13538
2635
43817
tkm
2230
2400
3000
7200
8000
5400
473
473
2240
2800
947
4833
Cables and electronics. Cables have a copper core and are PVC coated with a thickness of 1mm and HDPE outside coating with 2.5 mm thickness. Additional 20 kg PP, granulate was used. Cables inside tower were dependent on hub height (h). It was assumed that there were 3 inside cables with a crosssection, A of 640 mm2. The cables from the tower base to the grid were independent of turbine size. Assumptions were: 3 outside cables with a cross-section, A of 50 mm2 and distance to the grid of 1000 m.
Table S7 LCI of the electronic cables adapted from (LIT), used in all turbine configurations Unit process Copper, at regional storage Wire drawing, copper PVC, at regional storage Polyethylene, HDPE, granulate, at plant PP, granulate, at plant Extrusion, plastic pipes Transport, lorry 16-32t, EURO4/RER Transport, freight, rail/RER
Unit kg kg kg kg kg kg tkm tkm
Outside cables 1338 1338 79 186 20 285 325 1623
Parameterization 3A ρ h 3A ρ h
/ 200 1000
The electronic box was assumed the same for all turbine sizes.
Table S8
LCI of the electronics box adapted from Martinez, 2009 used in all turbine
configurations.4 Unit process Copper, at regional storage Wire drawing, copper Tin, at regional storage Steel, low-alloyed, at plant Section bar rolling, steel Lead, at regional storage Aluminium, primary, at plant Sheet rolling, aluminium PVC, at regional storage Polyethylene, HDPE, granulate, at plant Extrusion, plastic pipes Transport, lorry 16-32t, EURO4/RER Transport, freight, rail/RER
Unit kg kg kg kg kg kg kg kg kg kg kg tkm tkm
Amount 3 3 0.5 63 63 0.5 0.04 0.04 6 27 33 20 100
Transport. Transport is modeled consistently throughout all inventories as: • •
100 km, lorry raw materials to plant 100 km, lorry, plant to erection site S5
• •
200 km, train raw materials to plant 800 km, train, plant to erection site
Densities used in the study were: • • • •
1400 kg/m3 950 kg/m3 8920 kg/m3 2380 kg/m3
PVC HDPE Copper Concrete, normal
Table S9 Additional results for scaling factor b and intercept a for ReCiPe impact categories versus D2h3/7 using the ordinary least squares regression technique. 95% CI: 95% confidence interval; R2: coefficient of determination; SE: standard error; n: number of observations. Impact category
Unit
log a (95% CI)
b (95% CI)
R2
SE
n
Ozone depletion
kg CFC-11 eq/kWh
-8.15 (-8.48 – -7.83)
-0.22 (-0.16 – -0.30)
0.79
0.066
12
Human toxicity
kg 1,4-DB eq/kWh
0.66 (0.01 – 1.32)
-0.55 (-0.42 – -0.72)
0.85
0.134
12
Photochemical oxidant formation
kg NMVOC/kWh
-3.14 (-3.55 – -2.72)
-0.28 (-0.20 – -0.39)
0.79
0.084
12
Particulate matter formation
kg PM10 eq/kWh
-3.08 (-3.49 – -2.67)
-0.30 (-0.22 – -0.41)
0.81
0.084
12
Ionising radiation
kg U235 eq/kWh
-1.65 (-2.01 – -1.28)
-0.23 (-0.17 – -0.33)
0.77
0.075
12
Terrestrial acidification
kg SO2 eq/kWh
-2.61 (-3.06 – -2.16)
-0.37 (-0.28 – -0.49)
0.85
0.092
12
Freshwater eutrophication
kg P eq/kWh
-2.75 (-3.35 – -2.15)
-0.51 (-0.39 – -0.67)
0.86
0.123
12
Marine eutrophication
kg N eq/kWh
-4.08 (-4.52 – -3.64)
-0.30 (-0.22 – -0.41)
0.79
0.089
12
Terrestrial ecotoxicity
kg 1,4-DB eq/kWh
-3.95 (-4.38 – -3.52)
-0.40 (-0.31 – -0.51)
0.88
0.087
12
Marine ecotoxicity
kg 1,4-DB eq/kWh
-1.57 (-2.05 – -1.08)
-0.40 (-0.30 – -0.52)
0.85
0.098
12
Agricultural land occupation
m2a/kWh
-2.54 (-2.88 – -2.19)
-0.24 (-0.17 – -0.33)
0.79
0.070
12 12
Natural land transformation
m2/kWh
-4.75 (-5.20 – -4.30)
-0.28 (-0.20 – -0.39)
0.76
0.092
Water depletion
m3/kWh
-2.78 (-3.11 – -2.45)
-0.25 (-0.19 – -0.34)
0.82
0.068
12
Fossil depletion
kg oil eq/kWh
-1.47 (-1.85 – -1.09)
-0.22 (-0.15 – -0.31)
0.73
0.078
12
Environmental progress rates Table S10 Wind power turbine production in EU.10 Year
Installed wind power per year (MW/a)
1990
Cumulative installed power in the EU (MW) 439
1991
190
629
1992
215
844
1993
367
1211
1994
472
1683
1995
814
2497
1996
979
3476
S6
1996
979
3476
1997
1277
4753
1998
1700
6453
1999
3225
9678
2000
3209
12887
2001
4428
17315
2001
4428
17315
2002
5913
23228
2003
5462
28690
2004
5838
34528
2005
6204
40732
2006
7592
48324
2007
8535
56859
2008
8484
65343
Table S11
Environmental progress rates (EPR) versus cumulative production. Results for
ReCiPe impact categories using the ordinary least squares regression technique. 95% CI: 95% confidence interval; n: number of observations; R2: coefficient of determination. R2
Impact category
Unit
log a (95% CI)
b (95% CI)
n
Climate change
kg CO2 eq/kWh
-0.97 (-1.30 – -0.64)
-0.22 (-0.15 – -0.31)
10 0.81
EPR 86%
Ozone depletion
kg CFC-11 eq/kWh
-8.20 (-8.51 – -7.89)
-0.22 (-0.15 – -0.30)
10 0.82
86%
Human toxicity
kg 1,4-DB eq/kWh
0.51 (-0.20 – 1.21)
-0.54 (-0.39 – -0.74)
10 0.85
69%
Photochemical oxidant formation
kg NMVOC/kWh
-3.20 (-3.59 – -2.80)
-0.28 (-0.20 – -0.39)
10 0.82
83%
Particulate matter formation
kg PM10 eq/kWh
-3.15 (-3.52 – -2.77)
-0.30 (-0.22 – -0.40)
10 0.86
81%
Ionising radiation
kg U235 eq/kWh
-1.68 (-2.00 – -1.36)
-0.23 (-0.17 – -0.32)
10 0.84
85%
Terrestrial acidification
kg SO2 eq/kWh
-2.71 (-3.16 – -2.26)
-0.36 (-0.27 – -0.49)
10 0.86
78%
Freshwater eutrophication
kg P eq/kWh
-2.89 (-3.54 – -2.25)
-0.50 (-0.37 – -0.68)
10 0.85
71%
Marine eutrophication
kg N eq/kWh
-4.18 (-4.63 – -3.72)
-0.29 (-0.20 – -0.41)
10 0.80
83%
Terrestrial ecotoxicity
kg 1,4-DB eq/kWh
-4.06 (-4.49 – -3.63)
-0.39 (-0.30 – -0.51)
10 0.89
76%
Freshwater ecotoxicity
kg 1,4-DB eq/kWh
-1.76 (-2.18 – -1.33)
-0.38 (-0.28 – -0.49)
10 0.88
77%
Marine ecotoxicity
kg 1,4-DB eq/kWh
-1.68 (-2.11 – -1.24)
-0.39 (-0.29 – -0.51)
10 0.88
76%
Agricultural land occupation
m2a/kWh
-2.57 (-2.89 – -2.25)
-0.24 (-0.17 – -0.33)
10 0.84
85%
Urban land occupation
m2a/kWh
0.19 (-0.50 – 0.88)
-0.80 (-0.65 – -0.99)
10 0.93
57%
Natural land transformation
m2/kWh
-4.80 (-5.24 – -4.37)
-0.28 (-0.19 – -0.40)
10 0.80
83%
Water depletion
m3/kWh
-2.84 (-3.18 – -2.51)
-0.25 (-0.18 – -0.34)
10 0.84
84%
Metal depletion
kg Fe eq/kWh
-0.31 (-0.71 – 0.09)
-0.34 (-0.25 – -0.45)
10 0.87
79%
Fossil depletion
kg oil eq/kWh
-1.51 (-1.87 – -1.14)
-0.22 (-0.15 – -0.32)
10 0.77
86%
Sensitivity analysis S7
Table S12 Results of the sensitivity analysis of assumed wind speed. The maximum captured power at wind speed v1A = 5 m/s and v1B = 15m/s. Source
Rated power [kW]
Maximum captured power, Pcaptured, max [kW] v1A = 5 m/s
v1B = 15 m/s
1
660
219
5920
2
500
98
2638
3
850
203
5493
3
3000
689
18612
4
2000
480
12957
5
1650
545
14706
6
30
8
206
6
150
32
855
6
600
117
3157
6
800
174
4696
7
600
116
3121
8
1500
344
9277
Table S13 Results for scaling factor b and intercept a for ReCiPe impact categories versus D2h3/7 using a wind speed of v2 = 15m/s. 95% CI: 95% confidence interval; R2: coefficient of determination; SE: standard error; n: number of observations. Impact category
Unit
log a (95% CI)
b (95% CI)
n
SE
R2
Climate change
kg CO2 eq/kWh
-2.36 (-2.70 – -2.02)
-0.22 (-0.16 – -0.31)
12 0.070
0.77
Ozone depletion
kg CFC-11 eq/kWh
-9.58 (-9.91 – -9.26)
-0.22 (-0.16 – -0.30)
12 0.066
0.79
Human toxicity
kg 1,4-DB eq/kWh
-0.77 (-1.43 – -0.11)
-0.55 (-0.42 – -0.72)
12 0.134
0.85
Photochemical oxidant formation
kg NMVOC/kWh
-4.57 (-4.98 – -4.16)
-0.28 (-0.20 – -0.39)
12 0.084
0.79
Particulate matter formation
kg PM10 eq/kWh
-4.51 (-4.93 – -4.10)
-0.30 (-0.22 – -0.41)
12 0.084
0.81
Ionising radiation
kg U235 eq/kWh
-3.08 (-3.44 – -2.71)
-0.23 (-0.17 – -0.33)
12 0.075
0.77
Terrestrial acidification
kg SO2 eq/kWh
-4.04 (-4.49 – -3.59)
-0.37 (-0.28 – -0.49)
12 0.092
0.85
Freshwater eutrophication
kg P eq/kWh
-4.18 (-4.78 – -3.58)
-0.51 (-0.39 – -0.67)
12 0.123
0.86
Marine eutrophication
kg N eq/kWh
-5.51 (-5.95 – -5.07)
-0.30 (-0.22 – -0.41)
12 0.089
0.79
Terrestrial ecotoxicity
kg 1,4-DB eq/kWh
-5.39 (-5.82 – -4.96)
-0.40 (-0.31 – -0.51)
12 0.087
0.88
Freshwater ecotoxicity
kg 1,4-DB eq/kWh
-3.09 (-3.56 – -2.61)
-0.39 (-0.29 – -0.51)
12 0.097
0.84
Marine ecotoxicity
kg 1,4-DB eq/kWh
-3.00 (-3.48 – -2.51)
-0.40 (-0.30 – -0.52)
12 0.098
0.85
Agricultural land occupation
m2a/kWh
-3.97 (-4.31 – -3.62)
-0.24 (-0.17 – -0.33)
12 0.070
0.79
Urban land occupation
m2a/kWh
-0.85 (-1.02 – -0.67)
-0.87 (-0.82 – -0.91)
12 0.036
0.995
Natural land transformation
m2/kWh
-6.18 (-6.63 – -5.73)
-0.28 (-0.20 – -0.39)
12 0.092
0.76
Water depletion
m3/kWh
-4.21 (-4.55 – -3.88)
-0.25 (-0.19 – -0.34)
12 0.068
0.82
Metal depletion
kg Fe eq/kWh
-1.65 (-2.11 – -1.20)
-0.35 (-0.26 – -0.46)
12 0.093
0.83
Fossil depletion
kg oil eq/kWh
-2.90 (-3.28 – -2.52)
-0.22 (-0.15 – -0.31)
12 0.078
0.73
S8
Calculation of the scaling factor of generator efficiency According to previous work, efficiency (ε) is expected to scale with power according to a scaling law.11 Minimum (91.6% for a generator in a 20kW turbine) and average generator efficiency (94%) were reported in literature. 12, 13 The difference between the minimum and the average efficiency was 2.4%. The maximum efficiency was defined as 96.4% (94% + 2.4%) and was allocated to the largest turbine in the study (655kW). With these estimations, a power law with the following function was derived: ε = 0.88 P0.014 This power law was used to scale the efficiency as well as the electric power output Pel of the wind turbine (see Table S14). The deviation between the scaled Pel and the non-scaled Pel could then be calculated.
Table S14 Results of the sensitivity analysis of scaling the generator efficiency versus a constant generation efficiency of 94%. Source
Rated power [kW]
Scaled efficiency Pel with scaled efficiency [kW]
Pel with average efficiency of 94% [kW]
Deviation
1
660
0.955
199
208
-1.6%
2
500
0.944
88
93
-0.4%
3
850
0.954
184
193
-1.5%
3
3000
0.964
631
655
-2.6%
4
2000
0.965
440
456
-2.7%
5
1650
0.967
500
517
-2.9%
6
30
0.916
7
7
2.6%
6
150
0.929
28
30
1.2%
6
600
0.946
105
111
-0.7%
6
800
0.952
157
165
-1.2%
7
600
0.946
104
110
-0.7%
8
1500
0.961
314
326
-2.2%
Table S15 Exponent b and intercept a for non-renewable cumulative energy demand (CED and IMPACT2002+ impact categories versus D2h3/7 using the ordinary least squares regression technique. 95% CI: 95% confidence interval; R2: coefficient of determination; SE: standard error; n: number of observations.
S9
Impact category
Unit
log a (95% CI)
b (95% CI)
R2
SE
n
Non-renewable CED
MJ/kWh
0.79 (0.41 – 1.17)
-0.23 (-0.16 – -0.33)
0.75
0.077
12
IMPACT 2002+
Pt./kWh
-3.39 (-3.77 – -3.02)
-0.31 (-0.24 – -0.41)
0.85
0.076
12
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