Windenergy Report Germany 2008 written within the research project „Deutscher Windmonitor“
funded by the German federal Ministry for the Environment Nature Conversation and Nuclear Safety
German Wind Energy Report 2008
The research and development project behind this report was carried out on behalf of the German Ministry for the Environment, Nature Conservation and Nuclear Safety. Its reference number is 0327584. Responsibility for its content rests with the authors. PUBLISHER’S DETAILS
German Wind Energy Report 2008
Publisher: Institut für Solare Energieversorgungstechnik (ISET) Verein an der Universität Kassel e.V. Information und Energiewirtschaft Königstor 59 34119 Kassel Germany E-mail: [email protected] www.iset.uni-kassel.de
Editorial team: Stefan Faulstich, Michael Durstewitz, Berthold Hahn, Kaspar Knorr, Kurt Rohrig
Typesetting: EDV + Grafik, Kaufungen
Printing: PRINTEC OFFSET, Kassel
Copyright ISET e.V. / the institute’s commissioning client reserves all rights to reprinting, extraction of illustra- tions and reproduction by photo-mechanical or similar means and to storage in data-processing systems, even where only in excerpt form.
4 German Wind Energy Report 2008 INHALT
Foreword ...... 6
1 Introduction...... 7
2 Current state of wind power use...... 8
3 Availability of wind power ...... 14
4 Site development ...... 18
5 Turbine development...... 24
6 Grid integration ...... 30
7 Reliability...... 36
8 Economics ...... 42
9 Appendix...... 48
10 Sources...... 52
German Wind Energy Report 2008 5 Foreword
This ‘German Wind Energy Report 2008’ has was provided by around 1,500 wind turbines been produced as part of the ‘German Wind operating within the scheme. All of the subsi- Monitor’ research project. In addition to present- dised turbines were analysed over at least 10 ing the current status of wind power systems, years in the WMEP monitoring programme run it also offers a look back over this technology’s alongside the scheme, making this programme many years of successful development. the most comprehensive examination anywhere in the world of long-term wind turbine behav- This report also sees the continuation of the iour. The WMEP’s aim was to collect statistically regular publication of operating results for the proven empirical data relating to the practical wind turbines monitored in the ‘Scientific Meas- use of wind power on a scale of relevance to the urement and Evaluation Programme’ (WMEP) economics of energy generation and to evaluate run by ISET under the ‘250 MW Wind’ develop- this based on uniform criteria. ment scheme. The German Ministry for the Environment, Na- The ‘250 MW Wind’ scheme was announced ture Conservation and Nuclear Safety (BMU) has (initially as the ‘100 MW Wind’ scheme) in been supporting the ‘German Wind Monitor’ the Federal Gazette in June 1989. Due to the project since 2007. This continues the success- great demand and to German reunification, the ful work of the WMEP on a smaller scale and scheme was extended in 1991 to 250 MW. With presents the development of wind energy use in the total target output achieved, the scheme’s Germany, with particular emphasis on changes operators were able to end its approval stage at in technology, costs and the market, in a trans- the end of 1996, with the scheme then sup- parent and objective way for politicians and the porting a total volume of 350 MW (based on public at large. Its findings are published on the turbine output, i.e. usually maximum output ‘Wind Monitor’ website (www.windmonitor.de) at relatively high wind speed). This capacity and in the ‘Wind Energy Report’.
6 German Wind Energy Report 2008 1 Introduction
Over the last two decades, the use of wind Innovation energy has rapidly developed into a technol- In addition to opening up new possibilities for ogy that many believe will play a key role in the the deployment of wind power, it is also neces- future supply of electricity. In terms of utilisation sary for its further expansion to consider aspects of renewable energy, wind power already ranks of developing new turbine sites. Special towers, alongside hydropower as the most used energy for instance, make wooded areas on low moun- form. tain ranges suitable for use. Both the equipment used for utilising wind pow- For the evaluations presented in this report we er and the general environment for this form used several different sources of data, three of of renewable energy generation have changed which warrant specific mention at this point: significantly over the years.
Logbooks The aim of this Wind Energy Report is on the one hand to illustrate these changes and on As part of the WMEP programme the operators the other to provide a look forward to future manually recorded all key incidents and data in developments. a logbook. These books contain master data on the turbines and reports on the power supplied, Due to various aspects, the wind power industry maintenance, upkeep and operating costs. As currently has a number of diverse strategic op- part of the German Wind Monitor programme tions for further development, which we aim the logbooks of numerous operators, reporting to look at in more detail in the course of this on a voluntary basis, continue to be maintained. report: ISET wind measurement network Expansion For many years, ISET has been operating a wind Germany has for many years taken a pioneering measurement network spread across the whole role in wind power utilisation. The experiences of Germany. This network was set up as part of gained in the process are now being increasingly the ‘250 MW Wind’ scheme and represents a used to make a mark with this technology on valuable source of information. The network is the international market. described in greater detail in the appendix.
Repowering IWET database The replacement of old turbines with more IWET (the ‘Ingenieurwerkstatt Energietechnik’ / powerful ones has to date not been done to any Energy Technology Engineers’ Workshop) regu- meaningful extent. In order to further drive the larly records general project data and technical use of wind power forward, this option needs to data on wind turbines, grid integration and site be given greater attention in the future. topography. This data contains a whole host of information about the ‘German wind power Offshore fleet’. Wind power utilisation is just at the start of large-scale offshore use. The use of wind tur- bines out at sea represents a momentous addi- tion to on-shore sites, but is also associated with a number of challenges.
German Wind Energy Report 2008 7 2 Current state of wind energy use
Utilisation in Germany The growth in annual construction of new wind turbines in Germany has, as can be seen in il- Wind power is set to play a key role in the future lustration 3, been rapid. While at the start of the supply of energy both in Germany and on a nineties only some 10 MW of new capacity was global scale. According to German Government being installed and taken into operation each plans, wind power’s share of gross annual elec- year, from the late nineties this figure averaged tricity consumption is due to rise to around 15 % over 2,000 MW a year and in 2002 the newly in- by 2020. In comparison with other countries, stalled capacity even reached almost 3,200 MW. Germany has been leading the way for years in Since 2003, however, it is possible to observe a the utilisation of wind power, both in terms of certain saturation of the German market. Net the number of turbines installed, the installed growth in 2007 was, nevertheless, still around capacity, domestic value added and the number 1,600 MW. of directly or indirectly created jobs. The addition of the wind turbines newly installed The reasons for these technological and each year is clearly reflected in the increase in economic successes are largely based on a electricity production. Over recent years, the long-standing, continual policy of support and amount of electricity produced by wind turbines development operated by the relevant govern- has been constantly going up. At 31.1 TWh, ment ministries, which for over 20 years have both initiated and supported R&D projects and also created important legislative framework conditions.
The graphic below (illustration 2) shows the trend of development in relation to installed nominal capacity in Germany from 1991 through to the middle of 2008. The forecasts for the second half of 2008 were taken from the figures published by BTM consult [1]. Due to the agreed changes in the Renewable Energies Act (EEG) from January 2009, a slower pace of development can be expected in the second half of 2008. Fig. 1: Wind energy use in Germany
MW 25.000 §23.690 22.090 20.470 20.000 18.290
16.480 14.500 15.000
11.850
10.000 8.680
6.050 4.380 5.000 2.830 2.040 1.090 1.520 610 100 170 320 0
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Fig. 2: Development of installed wind power capacity in Germany
8 German Wind Energy Report 2008 3.500 1. Quartal 2. Quartal 3. Quartal 4. Quartal Prognosis MW 3.174
3.000
2.624 2.645 2.500
2.181 1.981 2.000 1.814 1.674 1.617 §1.600 1.548 1.500
1.000 798 665 481 512 500 433 293 144 42 70 0 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Fig. 3: Growth in Germany
45 December TWh November October 40 September August July 35 June May April 30 March February January 25
20
15
10
5
0 Fig. 4: Electricity from wind energy 2000 2001 2002 2003 2004 2005 2006 2007 2008 in Germany 1999 to 2008
German Wind Energy Report 2008 9 wind power’s share of net electricity consump- Global utilisation tion in 2006 was over 6 %. In 2007, this figure had already been exceeded by September. By In terms of global utilisation of wind power, the the end of 2007, wind-powered electricity pro- 100 GW mark of installed nominal capacity was duction in Germany reached just under 40 TWh exceeded during the course of 2008. Due to or a share of nearly 7 %. the fact that approximately 22 % of the world’s installed capacity is installed Germany, the While electricity from wind turbines is being fed country can still be termed ‘wind power world into the general electricity supply grid, other champion’. power stations are saving on combustible fuels. These are predominantly coal-fired power sta- In terms of the construction of additional new tions in the medium-load range. Per kilowatt turbines, however, Germany is, according to hour of wind-generated electricity fed into the figures published inWind Power Monthly [3], grid around 0.26 kg of coal is thus saved [2]. only in fifth place and will therefore probably This was the figure reported in a ‘Systematic soon have to relinquish this unofficial title. In the Analysis of the Effects of Wind-powered Electric- current installation figures the USA now heads ity Production on Germany’s Conventional Power up the top 5 with 2,326 MW ahead of China Stations’ published by the University of Stutt- (1,656 MW), India (956 MW), Spain (755 MW) gart’s Institute of Energy Economics and Rational and Germany. Energy Use (IER) in 1998. It is notable that around three quarters of the
Carbon dioxide (CO2) emissions also go down in installed capacity / additional construction line with the amount of combustible fuel that is is spread out over just these five countries. saved. For every kilowatt-hour of electricity fed In respect of installed capacity, the next few
in from wind power, 0.86 kg of CO2 emissions is countries are Denmark, Italy, France and Portu- thus in turn avoided. In 2007 the CO2 emissions gal, each with c. 3 GW, which thus contribute in Germany were reduced through the use of together a further 11 % to global wind power wind power by almost 33 million tons. This is output. The remaining 10 % is spread over all 18 % of the total CO2 reduction stipulated for other countries, with the installed capacity of Germany for the period 2008 to 2012, albeit none of these being more than 250 MW. excluding any other greenhouse gases.
Installed Rated Power 25 000 MW Growth 1.Hj. 2008 worldwide: 16 640 MW 22 500 Installed power worldwide: 101 896 MW 20 000
17 500
15 000
12 500
10 000
7 500
5 000
2 500
0 Germany USA Spain India China Growth 1.Hj. 2008 665 2 326 755 956 1 656 Growth 2007 1 625 5 273 3 530 1 574 3 312 Growth 2006 2 195 2 556 1 587 1 836 1 334 Growth 2005 1 799 2 390 1 765 1 451 496 Growth 2004 2 019 400 2 061 863 198 Growth 2003 2 759 1 707 1 372 418 98 Growth 2002 3 179 400 1 495 195 69 Growth 2001 2 633 1 690 904 287 59 Growth 2000 1 648 63 893 125 79 Total 1999 4 390 2 492 1 538 1 095 261 Growth 2008 22 912 19 297 15 900 8 800 7 562 Fig. 5: Global expansion
10 German Wind Energy Report 2008 This picture of concentration on a small number Europe 60187 MW of countries is also mirrored in the spread of wind power capacity on the individual conti- North America 21153 MW nents. 96 % of capacity is divided over three Asia 16803 MW continents, i.e. Europe, North America and Asia.
Pacific area 2733 MW Grid operators Wind power in Germany is fed into the control South and Central America 547 MW areas of the transmission grid operators, i.e. Middle East & Africa 473 MW EnBW Transportnetze AG, E.ON Netz GmbH, RWE Transportnetz Strom GmbH and Vattenfall Table 1: Installed rated power by continent Europe Transmission GmbH.
Fig. 6: Location [4] and installed wind power in the four control areas of Transmission networks
Fig. 7: Wind power Feed-in 2006 & 2007 in the four transmission grids [5, 6, 7, 8]
German Wind Energy Report 2008 11 The following graphics show the geographical largest shares of the market in Germany, as seen split of these four control areas, the installed in illustration 9. Of the world’s ten largest manu- nominal capacity of the wind turbines in each facturers four have no presence in Germany and the volumes of wind-generated electricity (fifth-placed Suzlon (2,082 MW), Acciona (7th, fed into the grid in 2006 and 2007. As figures 873 MW), Goldwind (8th, 830 MW) and Sinovel for the amount of wind-generated electricity (10th, 671 MW)). In looking at the distribution fed into the EnBW grid were not available at the of installed turbines it is clear to see that two of time of going to print, this has been estimated. the manufacturers, Enercon and Vestas, account for just under 15 GW of installed capacity and thus for over 60 % of total wind power output Turbine manufacturers in Germany. This division is reflected not only In 2007, wind turbines with a nominal capacity in the share of capacity but also in the absolute of 14,983 MW [9] were newly installed around number of turbines. 7 of the 10 most frequently the world, with 1,617 MW [10] of this being used wind turbine models in Germany are pro- in Germany. The turbines installed in Germany duced, for example, by these two market lead- were supplied by 8 manufacturers. Account- ers, as can be seen from the following table. ing for 831 MW, Enercon installed the great- est number, followed by global market leader Similar to the situation with global wind power Vestas. utilisation, there is a concentration when it comes to turbine manufacturers on just a few Illustration 8 shows for 2007 the number of major manufacturing companies. While ten wind turbines installed in Germany and other years ago there were still 20 different manufac- countries. The total of the respective figures turers active on the German market, this number shows the newly erected wind turbines globally has been reduced to less than ten as a result of by manufacturer, e.g. 2,769 MW for Enercon countless takeovers (e.g. of Wind world, Micon, and 4,503 for Vestas. Shown here are the 10 NEG Micon and Nordtank by Vestas). turbine manufacturers that currently have the
Turbine type Number of turbines Installed capacity [GW]
Enercon E-40 2391 1,28
Enercon E-66 2063 3,60
Enercon E-70 1082 2,24
Vestas V80/2 999 2,00
GE 1.5 663 0,99
Vestas V90/2 619 1,29
AN Bonus 1.3 MW/62 426 0,55
Vestas V 47/660 392 0,26
REpower MD 77 390 0,59
Vestas V 66/1.65 370 0,61 Table 2: Overview of the most com- mon wind turbines in Germany
12 German Wind Energy Report 2008 5.000 MW Installations: 4.500 2007 Germany 2007 Outside Germany 4.000
3.500
3.000
2.500 4.101
Installed Capacity Installed 2.000 1.938 3.282 1.500 3.003
1.000 831 1.314 500 402 569 464 107 188 2 83 0 45 44 0 Enercon Vestas GE Energy Nordex Siemens REpower DeWind Fuhrländer Gamesa Fig. 8: New installations 2007 in and outside Germany
8000 2007 MW 2006 2005 7000 2004 2003 2002 6000 2001 2000 vor 2000 5000
4000 Installed Capacity Installed 3000
2000
1000
0 Fig.���������������������������������� 9: Installed capacity of the ma- Enercon Vestas GE Energy Nordex Siemens Repower DeWind Fuhrländer Gamesa nufacturers in Germany
German Wind Energy Report 2008 13 3 Availability of wind power
Wind conditions The table below summarises the characteristic values, such as average power density, Weibull One of the central technical and economic parameter A and Weibull parameter k, for the uncertainties in the use of wind power is the different site categories and measurement fluctuating availability of wind. In individual heights. What are shown are the multi-year operating years this can also show – quite apart averages, with the figures for 2007 in brackets. from short-term fluctuations – clear variances as an annual figure from the long-term average. In addition to the annually occurring fluctuations When it comes to financing wind turbines it is in the wind power supply, we can also clearly therefore not only the average supply of wind see the regional differences in wind availabil- energy at the site that plays an important role, ity caused by geographical and topographical but also the more long-term pattern. Especially factors. It shows that the supply of wind power at the start of the financing and also in oper- works out significantly higher right on the coast ating years in which additional high costs are than it is inland. Wind supply can in particu- incurred (e.g. for maintenance work), significant lar end up being appreciably less in the more shortfalls can endanger a wind power project’s southern parts of the North German Plain and liquidity and economic viability. at several less favourable sites on the country’s relatively low mountain ranges. On the other Illustration 10 shows on the left side the fre- hand, at good, exposed sites within these ranges quency distribution curves of the wind speed economically viable wind turbine operation is and on the right the annual averages of the also possible. power contained within the wind (in the unit of W/m²) for 1993 to mid-2008 for different The extent on which wind power density de- site categories. The bottom illustrations here pends on height is also very clear to see. Illustra- relate to a measurement height of 10 metres tion 11 shows some indicators for theoretical above ground level, while the top ones relate to gains through the choice of site and an increase a height of 30-40 metres. The values are based in hub height. While at a forest site increasing on the WMEP’s wind speed measurements, the hub height from 75 to 150 metres means which have been converted for indicating power almost 50 % greater wind power density, the density into annual averages of wind output lower the roughness level at the site the more (assuming in such conversion a standard atmos- this effect is reduced. When comparing turbines phere and correcting the standard air density of the same hub height at differing sites, the by the influence of the height above sea level). possible gain therefore goes down as the hub The wind speed distribution curves show the height goes up. averages over many years, while the dotted lines represent the spreads for 2007.
Power density [W/m2] Weibull A [m/s] Weibull k
30 – 40 m
Coast line 319 (319) 7,02 (7,59) 2,17 (2,28)
Low mountain range 176 (176) 5,55 (5,88) 1,91 (2,03)
North German Lowlands 170 (181) 5,52 (6,03) 1,97 (2,10)
10 m
Coast line 180 (226) 5,54 (5,96) 1,79 (1,84)
Low mountain range 113 (108) 4,50 (4,70) 1,66 (1,67)
North German Lowlands 93 (93) 4,03 (4,34) 1,58 (1,59) Table 3: Characteristic values of the wind conditions
14 German Wind Energy Report 2008 20%
500 W/m²
15% 400
300 10% Frequency 200
5%
100
0% 0 0 2 4 6 8 10 12 14 16 18 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 1.Hj. Wind Speed [m/s] 2008
20%
500 W/m²
15% 400
300 10% Frequency
200
5%
100
Fig. 10: Gross wind energy supply 0% 0 0 2 4 6 8 10 12 14 16 18 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 1.Hj. 1993 – 2008 and the frequency distri- Wind Speed [m/s] 2008 butions of wind speed for different categories of landscape in different Coast Line, Islands Low Mountain Range North German Lowlands heights
Fig. 11: Height profile of wind power
German Wind Energy Report 2008 15 Wind index each case to the wind energy supply’s multi-year average. The reference period is the period since In the course of the WMEP programme the 1993. fluctuations in the annual availability of wind in Germany were examined and a procedure de- The multi-year wind supply trend is shown in the veloped that describes the relation of individual diagram below. The fluctuations in the trend of years’ wind energy supply relative to the ‘typical’ wind power densities shown in illustration 10 wind energy supply using a single indicator, the are also reflected in this representation. ‘wind index’. This is based on the wind meas- urements made by the nationwide ISET wind- Compared to the long-term average, 2007 was measuring network (described in more detail a good year for wind. While the other years of in the appendix to this report) set up as part of the 21st century tended to be below average, the the ‘250 MW Wind’ programme. Illustration positive trend from 2007 has continued in the 13 shows example representations of the wind first half of 2008. The windy month of March index for the first half of 2008 and for the indi- in particular has so far ensured relatively good vidual months. The percentages given relate in wind conditions.
30
25
20
15
10
5
0
-5
-10
Deviation from long term average [%] average term long from Deviation -15
-20
-25 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Fig. 12: Wind-Index of previous years
16 German Wind Energy Report 2008 First half of 2008
January (126 %) February (85 %) March (153 %)
April (73 %) May (68 %) June (81 %)
Fig. 13: Exemplary representation of the Wind-Index for the first half of 2008 and for the individual months
German Wind Energy Report 2008 17 4 Site development
The spread of sites Wind farm size
In the 1980s and through until the middle of There are almost 20,000 wind turbines being the nineties, the installation of wind turbines in operated in Germany. These are spread over c. Germany took place predominantly in northern 6,600 wind power sites. ‘Wind power site’ here coastal regions, as the prevailing wind conditions can mean a wind farm or just a single turbine. here made economic utilisation most likely. Over It should be noted, however, that a wind farm the years, more and more wind turbines were is seen merely as an economically connected also erected at sites away from the coast in the unit. A further geographic interrelationship of interior and in the low mountain regions of Ger- individual wind farms could also exist if multiple many. Wind turbines are now being operated in wind farms are located next to each other within all of Germany’s Federal States and within the a so-called wind district. Such a relationship, most varied of terrain structures. An appor- however, cannot be looked at here. tionment of all German turbine sites into the landscape categories of ‘Coast’, ‘North German Illustration 15 shows the development of sites Plain’ and ‘Low Mountain Range’ reflects the used for wind power. The size of the wind farms great proportion of usable areas on the North in terms of numbers of turbines and installed German Plain. All sites on islands and within a capacity has grown significantly over time. The strip of around 5km in width along the coastline average number of turbines per newly built wind were allocated to the ‘Coast’ category. farm has more than doubled, while the installed capacity of each wind farm has increased more According to this apportionment, at present than tenfold. With well over ten wind turbines, around 13 % of the installed wind capacity is some individual farms achieve 20 MW of output, being operated in the coastal regions, 59 % in while the biggest wind district in Germany the ‘North German Plain’ region and 28 % in the achieves as much as 100 MW and more. It low mountain locations. can be reasonably assumed that in contrast to the early days of wind power utilisation in the 1990s, it is today increasingly professional oper- ating companies that are setting up and operat- ing wind farms rather than private individuals.
Share of new installed power 100%
90%
80%
70%
60% Landscape category (share of the stock) 50% Low Mountain Range (28 %) North German Lowlands (59 %) 40% Coast Line (13 %)
30%
20%
10%
0%
8 989 990 991 992 993 994 995 996 997 998 999 000 001 002 003 004 005 006 007 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 Fig. 14: Share of newly installed .Hj. 200 1 power in the location categories
18 German Wind Energy Report 2008 Repowering Illustration 16 shows the age profile of the wind turbines installed in Germany. Were one to as- The term repowering is used for the replacement sume that turbines over 15 years old can sensibly of old, less powerful wind turbines with more be replaced by repowering, then the number of powerful, state-of-the-art ones. A rule of thumb turbines falling into that category would be c. frequently used in relation to this is 50 % more 900 or around 5 % of the total number. Howev- yield with 50 % fewer turbines. er, due to the direct correlation between turbine age and size the proportion in relation to the The thinning of the wind farm landscape pro- installed capacity is much lower. The boom that duced by repowering will in future enable not is to be anticipated in repowering will therefore only the number of wind turbines in Germany to probably still have to wait a while longer. be lowered and levels of electricity production to be increased, but will at the same time also enable the impact on people, nature and the ap- pearance of the countryside to be reduced.
Amount & MW Amount 9,0 25000
8,0
20000 7,0
6,0
15000 5,0
4,0 10000
3,0
2,0 5000
1,0
0,0 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Fig. 15: Expansion of wind power Ø Power per WT Ø Number of WT per Windfarm Ø Power per Windfarm Number of WTs Number of Windfarms locations
2500 Rated power class: P < 500 kW 500 kW P < 1000 kW 1000 kW P < 2000 kW P 2000 kW
2000
1500
Number of WTs 1000
500
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Fig. 16: Age and power class of the Age [Years] currently operating wind turbines
German Wind Energy Report 2008 19 Offshore the coast in fairly calm waters, as more experi- ence is gained increasing numbers of projects The world’s first offshore wind farm near are being undertaken at greater distances from Vindeby in Denmark went into operation as land and in deeper water. far back as 1991. After only a few wind farms were added to this during the nineties, from the While other European countries have already start of the 21st century there began to be, as gained experience in the field of offshore wind can be seen in illustration 18, a clear increase power, Germany has not yet made the move in offshore installed wind power capacity. Yet into the offshore business. Expansion in Germa- the expansion of offshore wind power is only in ny has been delayed above all by consideration its infancy. According to a study by the Euro- of ecological concerns. The German projects pean Wind Energy Association between 20 and are being predominantly planned in water over 40 GW of wind power capacity is due to be 15m deep and more than 10km from the coast installed in the waters of Europe by 2020. in order not to have any detrimental effect on the Wadden Sea National Park. As shown in To date the move from the coast into offshore illustration 17, the available sites for offshore areas has been slow. While the initial offshore wind power in Germany thus differ significantly wind farms were still being built for experimen- from the sites of existing international offshore tal purposes at a relatively short distance from projects.
Fig. 17: Comparison of the planned sites in Germany with the existing international locations
20 German Wind Energy Report 2008 1400
1200
1000
800
600 Installed Capacity [MW] Capacity Installed
400
200
0 2000 2001 2002 2003 2004 2005 2006 2007
Fig. 18: Development of installed New Installed Capacity Comulative Installed Capacity wind power offshore
Mean coastal distance Mean water depth
12
10
8
6
4 Meancoastal distance [km] /Mean water depth [m] 2
0 Fig. 19: Development of locations in 2000 2001 2002 2003 2004 2005 2006 2007 use for offshore wind turbines
German Wind Energy Report 2008 21 At present (October 2008), 23 wind farms have approval process in the Exclusive Economic Zone been approved in Germany, 18 in the North Sea (EEZ) lies with the Federal Maritime and Hydro- and 5 in the Baltic. The Nordergründe (North graphic Agency. To date wind farms with a total Sea), Baltic I and GEOFReE (Baltic Sea) wind maximum nominal capacity (at least in the initial farms are located within the 12 nautical mile stage of expansion) of over 7 GW have been boundary, i.e. in the area of coastal waters in approved over an area of 800 km2 . Numerous which the respective Federal States are responsi- other farms are planned or are in some cases ble for granting approval. Responsibility for the already going through the approval process.
Park name Planned maximum Water Coastal dis- Area capacity [MW] depth [m] tance [km] [km2]
alpha ventus (Borkum West) 60 28 – 30 43 6,47
Amrumbank West 400 20 – 25 36 31,93
BARD Offshore I 400 39 – 41 89 58,35
Borkum Riffgrund 231 23 – 29 34 35,64
Borkum Riffgrund West 280 29 – 33 50 29,64
Borkum West II 400 22 – 30 45 69,01
Butendiek 240 16 – 22 37 33,12
DanTysk 400 21 – 33 70 65,83
Global Tech I 400 39 – 41 93 41,16
Gode Wind I 400 26 – 35 45 36,49
Hochsee Windpark He dreiht 400 37 – 43 85 34,20
Hochsee Windpark Nordsee 400 26 – 39 90 41,70
Meerwind 288 23 – 50 23 40,48
Nördlicher Grund 360 27 – 38 84 54,54
Nordsee Ost 400 19 – 24 30 35,62
OWP Delta Nordsee 1 240 29 – 35 39 16,74
Sandbank 24 420 30 – 40 90 59,70
WP Nordergründe 125 2 – 18 13 3,77
Summe 5844 — — 694,39 Table 4: Approved wind farms in the German North Sea
Park name Planned maximum Water Coastal dis- Area capacity [MW] depth [m] tance [km] [km2]
Arkona-Becken Südost 400 21 – 38 35 38,49
Baltic I 57,5 15 – 19 15 6,97
GEOFReE 25 20 20 1,55
Kriegers Flak 320,5 20 – 35 31 30,14
Ventotec Ost 2 400 29 – 41 35 33,67 Table 5: Approved wind farms in the Summe 1203 — — 110,82 German Baltic Sea
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! ! 5 Turbine development
Technical concepts One notable aspect of the development of such technical concepts is the fact that at the start of The continual expansion in the utilisation of large-scale utilisation of wind power trends ini- wind power over the last 15 to 20 years enabled tially emerged in the direction of concepts that the manufacturers to make significant enhance- have today been almost completely forced out ments in wind turbine technology. of the market (i.e. in the type of output regula- tion, of generator construction and in rotary The extent to which typical features of turbine speed characteristics). As can be clearly seen in construction have gained / maintained a hold illustration 22, the proportion of stall-regulated in the market can be seen from table 6. The wind turbines, for example, initially rose until percentages shown represent the proportion of around 1995 and was practically on a par with wind turbines with the respective feature out of the proportion of pitch-regulated turbines. The the total number of newly installed turbines dur- trend for rotary speed characteristics shows ing the relevant period. a similar picture. Dominating the scene here until 1995 was constant / sliding scale speed. Turbines recorded in the table as having ‘variable However, this subsequently became less and less rotary speed’ are turbines with a rotary speed prevalent and today is no longer used. Another range that covers at least 70-100 % of their temporal trend that is also very clear to see, maximum rotor speed. The stall effect actively but that is not yet fully complete, comes in the regulated through blade adjustment (also called choice of the type of generator construction. ‘active stall’ or ‘combi stall’) is classified under Until 1990 two thirds of all wind turbines were ‘pitch’ regulation in order to differentiate from fitted with a simple asynchronous generator and the passive, unregulated limitation of output in the period from 1991 to 1995 the figure was through use of the ‘stall effect’. already up to three thirds. Double-fed asynchro- nous motors (a design that had already been The clearest trend is the move to what has long used 25 years earlier in the ‘Growian’, but that since become the standard use of three-blade was regarded for a long time as too cost-inten- units as windward rotors. All other forms of sive) and synchronous generators have, however, rotor construction have disappeared from the increasingly gained in significance and have market. Over recent years, the trend in electro- been heavily used in the recent past. mechanical power train and regulation design has moved relatively clearly in the direction of speed variability and rotor blade adjustment.
24 German Wind Energy Report 2008 stall pitch
100% 80% 60% 40% 20% 0%
induction double-fed synchronous
100% 80% 60% 40% 20% 0%
constant/stepped variabel
100% 80% 60% 40% 20% 0% Fig. 22: Technical characteristics of bis 1990 1991-1995 1996-2000 2001-2005 2006-2008 newly installed wind turbines
bis 1990 1991-1995 1996-2000 2001-2005 2006-2008
Number of blades
2 blades 21 % 7 % 0 % 0 % 0 %
3 blades 77 % 93 % 100 % 100 % 100 %
4 blades 1 % 1 % 0 % 0 % 0 %
Rotor position
lee 9 % 2 % 0 % 0 % 0 %
luv 91 % 98 % 100 % 100 % 100 %
Power control
stall 49 % 59 % 37 % 11 % 0 %
Pitch (incl.“active stall”) 51 % 41 % 63 % 89 % 100 %
Generator
induction generator 67 % 74 % 54 % 17 % 0 %
double-fad 0 % 0 % 12 % 46 % 51 %
synchronous 33 % 26 % 35 % 37 % 49 %
Speed characteristics
constant 57 % 70 % 53 % 17 % 0 %
Table 6: Technical characteristics of variable 43 % 30 % 47 % 83 % 100 % newly installed wind turbines
German Wind Energy Report 2008 25 Turbine size relation to various categories of output capacity. From 1989 until 1993, for example, turbines in The increasing development of less windy inland the range up to 499 kW of capacity dominated sites requires the use of higher towers and larger the market, with these having percentage shares rotor diameters. These are needed in order to of around 60 % to 100 % of all newly installed be able to position the rotors at greater heights turbines. From 1994 to 1997 it was the range above the ground so that they can exploit the from 500 to 999 kW that dominated, from 1998 better wind currents up at such positions and/or to 2003 turbines with a capacity of 1,000 to in order to optimise the area of yield commen- 1,999 kW and from 2004 those with nominal surate to the circular area of rotation. Generator capacity of 2,000 kW or more. capacity here generally remains unchanged. From the small turbines of the mid-80s with a Around 11 % (about 2,200) of all wind turbines capacity of on average around 30 kW and ro- in Germany still come from the sub-500 kW ca- tor diameters of less than 15m, manufacturers pacity range. It was with these types of turbines developed successive machines with 5 MW and that the boom-like expansion of wind power more of nominal capacity and rotor diameters of utilisation began in the first half of the 1990s. over 120 metres. By the middle of 2008, however, these turbines combined were no longer providing any more The trend towards ever larger and more power- than 1.5 % (380 MW) of the installed capacity. ful turbines is a feature of the development of wind power technology to date. New wind tur- It is the turbines of the 1,000 to 1,999 kW cat- bine models with generally greater nominal ca- egory (some 7,260 of them) that make up the pacity and/or rotor diameters / hub height have greatest share of installed wind power capacity been appearing up until now every year. The (47 %). The turbines with a capacity of 500 to demand for ever larger wind turbines is having 999 kW (around 6,460) and those in the 2,000 the effect that after around five years ‘smaller to 3,999 kW category (around 3,780) make up turbines’ are losing their previous dominant mar- between them a 51 % share of the installed ket position to the next generation. This cycle of capacity. The 4 MW and above category (with model change is shown in illustration 24, which 25 turbines) so far provides 0.5 %. summaries the wind turbines in Germany in
#23_Rotor Nabe Lstg
Rotor Diameter [m] Hub Height [m] Rated Power [kW] 100 2000
[m] [kW]
80 1600
60 1200
40 800
20 400
0 0
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
1.Hj. 2008 Fig. 23: Development of WT Size
Seite 1
26 German Wind Energy Report 2008 #24_Dia_Lstg_Jahre D bunt
< 500 kW 500 kW P < 1000 kW 1000 kW P < 2000 kW 2000 kW P < 4000 kW 4000 kW 120%
100%
80%
60%
40%
20%
0% 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 Fig. 24: Annual share of power classes
Seite 1
ISET Projektbereich Wind energie Hn 25.01.98
Installed Capacity [MW] Amount 100.000 100.000 Installed Capacity: 22.880 MW
Number of WTs: 19.644
10.000 10.000
1.000 1.000
100 100
10 10
1 1 1- 499 500 - 999 1000 - 1999 2000 - 3999 ab 4000
Fig. 25: In Germany installed wind WT-Rated Power [kW] turbines according to power classes
i:\home\w\berthold\dokument\vortrag\bwe98\#25 Installierte Leistung nach Lstgklassen 2008.xls\#25_Dia LstgKlassen D (JAW)
German Wind Energy Report 2008 27 Offshore wind turbines with the growing portfolio of globally installed Wind turbines for large-scale offshore use dif- offshore turbines, in both cases from the year fer in several aspects from those used on land. 2000 onwards. Compared to turbines on land, In addition to the increased requirement for offshore wind turbines with low hub heights the turbines to be reliable, which is achieved have a clearly greater installed capacity. through various means, such as hermetic casing and component redundancy, the turbines also A further special feature of offshore wind tur- differ by virtue of how they are configured for bines comes in the need for special foundation the variations in wind energy supply described systems. In essence six possibilities come into above. The illustration below (illustration 26) question here, of which only the first three have compares the wind turbine portfolio in Germany been used to date:
Average rated power since 2000 Onshore Offshore
2500
[kW]
2000
1500
1000
500
0 2000 2001 2002 2003 2004 2005 2006 2007
Average hub height since 2000 Onshore Offshore
100 [m]
80
60
40
20
0 2000 2001 2002 2003 2004 2005 2006 2007 Fig. 26: Development of WT Size
28 German Wind Energy Report 2008 • Monopile tions are predominantly used, the proportion • Gravitation foundation of monopiles goes up as the water gets deeper. • Jacket From a water depth of above 25 metres, how- • Bucket ever, monopiles are no longer used due to the • Tripod required dimensions. Instead, more complex • Floating foundation structures are used.
In addition to the nature of the seabed at the The foundations envisaged for the planned site, the depth of the water also plays a key role Multibrid wind turbines in the first German in choosing the type of foundation (illustration offshore wind farm, alpha ventus, are tripod 28). While in shallow waters gravitation founda- constructions.
Fig. 27: Offshore foundations: left Tripod, right Jacket
120%
100% .
80%
60%
40% Proportionof the number of footing concepts 20%
0% <5 5<=x<10 10<=x<15 15<=x<25 >=25 Water depth [m]
Monopile Concrete caisson Jacket Fig. 28: Foundation concepts in use
German Wind Energy Report 2008 29 6 Grid integration
The availability of wind-generated acteristics, all of which cause major fluctuations. electricity In groupings of wind turbines over a wide area, on the other hand, short-term and local wind The availability of the electricity feed generated fluctuations are largely balanced out and the from wind power differs fundamentally from feed-in’s trend defined more by the wide-scale that from conventional generation using fossil weather pattern. Illustration 29 shows the trend fuels. For its integration into the existing electric- of 15-minute averages of the feed-in (scaled to ity supply system two aspects are of particular the relevant nominal capacity) of an individual importance: turbine situated on the North Sea coast (blue line), of a wind farm group (green line) and • the infed power fluctuates depending on the of the German nationwide feed-in (red line) availability of wind energy; over a period of c. 6 days (17th–23rd September • the infed power is generated on a decentral- 2007). The nominal capacities are 500 kW for ised basis across a wide area using a large the individual turbine, 80.8 MW for the wind number of turbines. farm group and c. 20.2 GW for Germany. The homogenisation of the feed-in where there is In a few distribution grids the installed wind a larger number of turbines or where these are power capacity reaches the level of the mini- spread over a larger area is clear to see. The mum load, so that sometimes, i.e. in situations time line shows significant fluctuations in output of weak load and strong wind, wind power for the individual turbine, while in the case of covers this load 100 % or more. If the high an- the wind farm group we can see a slower rise nual rate of new installations continues over the and fall of output over the same period. On the coming years, especially through the planned total time variation curve for all wind turbines in offshore wind farms, the installed wind power Germany the fluctuations in output are largely capacity in other regions of Germany will also smoothed out and both gradients and peak achieve this order of magnitude. values are much less pronounced.
The continual measurement of the output of the Effects on changes in output wind turbines connected within the ISET meas- The reduction in output fluctuations when the urement network (cf. appendix) provides a suit- number of turbines is greater and when they are able source of data for analysing the character- more widely spread is also clear to see in illustra- istics of the feed of electricity from wind power tion 30. This uses the 15-minute averages of the turbines in Germany. Based on this data the 2007 power output of the coastal turbine, of ISET has developed methods and procedures to the wind farm group and of the total load curve integrate the constantly growing shares of wind of Germany’s wind power capacity. In the case power into the existing electricity supply system, of the individual wind turbine the range of out- which is based on conventional generation. The put changes identified is, as expected, wide. The following assessments and interpretations draw frequency distribution of the wind farm group’s on the findings of these methods. output changes already shows the impact of homogenisation of the output fluctuations by Output trends in wide-area turbine grouping turbines together. The frequency of ex- grouping treme changes in output goes down somewhat. The output trend of individual wind turbines is Comparison of the individual turbine’s and wind determined, in addition to wide-scale weather farm group’s frequency values (as shown) with events (such as the passing through of areas of the nationwide feed-in shows the strong effect low pressure), by atmospheric turbulence, the of homogenisation where generation is spread local situation and the turbine’s individual char- over a wide area.
30 German Wind Energy Report 2008 Fig. 29: Time series of power output from an individual plant, a group of wind farms and all the WTs in Germany
Fig. 30: Power fluctuations of an individual plant, a group of wind farms and all the WTs in Germany
German Wind Energy Report 2008 31 In order to show the homogenisation effect even In the 15-minute time period the wind power more clearly, a total of 60 wind farms spread fed in across Germany changes with a prob- all over Germany with nominal capacities of ability of 92 % by not more than ± 1 % of the between 3 and 160 MW have been consolidated installed capacity. In a time period of one hour in illustration 30 into a number of groupings. the probability for the same change is still 64 % The first grouping consists solely of one wind and in the case of four hours merely still 29 %. farm. All of the other groupings have in each The greatest change in output in 2007 occurred case been formed by adding one further wind on 30th January. The wind power fed in across farm to the grouping before. This produced a Germany dropped here within a quarter of an total of 60 groupings, the largest of which has hour by 18.7 % of the installed capacity. a nominal capacity of c. 2.1 GW. The changes in the hourly averages of the feed-in of these Output duration groupings are shown in the left-hand part of Output duration curves show in a clear form the illustration 31 as frequency distributions depend- number of annual hours during which output is ent on the installed capacity. The right-hand part above a certain level. Illustration 32 shows the of illustration 31 is the view onto the frequency output duration curves of an individual wind distributions from above and clearly shows the turbine, or a wind farm group and of all of the reduction in extreme output changes as the size wind turbines in the combined German grid. of the wind farm grouping goes up. Another key Periods with measurement outages were esti- influencing factor that is not directly depicted mated. The course of the curve, the integral of here is represented by the distance of the tur- which corresponds to the annual supply of pow- bines from each other / by their spatial spread. er, is dependent on the supply of wind energy and in particular on the spread of the installed Output fluctuations within short intervals turbines over the territory. During c. 4,000 In addition to the number of wind turbines, the hours of 2007, for instance, at least 14 % of the time period looked at also has an influence on installed capacity was fed into the combined the shape of the frequency distribution of the German grid, while the maximum was 90 % changes in output. Illustration 32 shows this of installed capacity. With these geographically by using as an example the wind power fed in widespread turbines, the differently fluctuating across Germany in 2007 for several different wind speeds and outputs delivered in the vari- time periods. ous regions of Germany partially balanced each other out. The wind farm group shows some- A frequency of 0.0027 equates to an occurrence what more frequent high output levels of up to of 96 events per year, i.e. of the duration of 98.3 %, while the minimum output in the case one day. A positive value indicates an increase of high numbers of hours for these wind farms in output, while if the value is negative output is below that of the combined German grid. In goes down. the case of the individual wind turbine this effect is again clearly increased. As the time period reduces, the frequency of major changes in output also becomes less.
32 German Wind Energy Report 2008 Fig. 31: Power fluctuations for groups of wind farms with increa- sing size
Fig. 32: Frequencies of relative power fluctuation for time period of ¼ hour, 1 hour and 4 hours
Fig. 33: Power duration curve (2007) of a single plant at the coastal site in comparison with a group of wind farms, and all the widely distributed plants in Germany
German Wind Energy Report 2008 33 Forecasting the feed-in of Illustration 35 shows the trend over time in the wind-generated electricity achieved forecasting precision of the varying types of prediction. As well as the influence In order to be able to minimise the amount of of the temporal forecast horizon, we can also standby capacity needed it is necessary to know see from the illustration the influence of the the volume of wind power fed in at present and previously described homogenisation of output to be able to forecast the wind power output fluctuations due to geographical spread. In 2006 to be expected as accurately as possible. The the prediction error for the forecast for Germany transmission system operators in Germany use for the following day was on average under 5 % for this purpose a wind power management mean square error related to the installed capac- system (WPMS). Based on output measurements ity. The current short-term prediction improves of representative wind farms and from the Me- the variances to c. 4 % for a forecast period of teorological Office’s numerical weather forecasts 4 hours and to c. 2.5 % for a 2-hour short-term this system calculates with the aid of so-called prediction. artificial neuronal networks predictions for the wind output to be expected the following day. As part of the ‘German Wind Monitor’ pro- Short-range forecasts for a period of 1-8 hours gramme experts are investigating to what extent are also produced using measured output data. short-term predictions can be improved by tak- ing into account in addition to the output meas- From the predicted output data for the reference urements at wind farms the current wind speed wind farms the total feed-in is estimated for the measurements as well. Especially in situations transmission system operators’ individual regions with strong fluctuations in output, relatively and for all of Germany. Illustration 34 shows, for minor errors, for example, in the predicted time example, the time curve for the wind power fed of the arrival of a storm front, lead to significant in across Germany (coloured black), what it was variances and thus to major errors in the forecast predicted to be in each case on the preceding of wind power output. In such situations current day (red) and the short-term prediction for a wind measurements provide more information forecast horizon of one hour (blue). It can be on the wind activity than the wind farms’ power seen that the already very good match between output. the next-day prediction and the actual output is bettered still by the short-term prediction due to the shorter forecast horizon.
34 German Wind Energy Report 2008 Fig. 34: Time series: Day-ahead prediction, short-term prediction (1 hour) and the actual value
11%
10%
9%
8% Day ahead prediction control zone
7%
6% Day ahead prediction Germany 5%
4% Short-term prediction(4h) Germany
RMSE in % of installed capacity 3% Short-term prediction(2h) Germany
2%
1% Fig. 35: Time series: Day-ahead prediction, short-term prediction 0% (1 hour) and the actual value 2000 2001 2002 2003 2004 2005 2006
German Wind Energy Report 2008 35 7 Reliability
Causes of failures mer thunderstorms, the probability of a light- ing strike in the months from June to August The diagram below shows the frequency of reaches, on average over many years, values of different causes for wind turbine damage and around 15 % (i.e. 15 reports in 100 months of repairs. It is clear to see that the majority of re- operation). Despite lightning protection systems ported breakdowns are attributable to defective now being used as standard, the frequency of or loose components or to malfunctions of the breakdowns caused by lightning is thus around turbine control systems. In less than a quarter of the same as that of the other external causes. all cases were the faults caused by external influ- ences such as storms, lightning, ice accretion or As most operational problems caused by ice grid outages (shown with hatched shading). accretion arise between December and March (a period with normally good weather condi- While as a cause of breakdowns grid outages tions), a significant loss of yield can sometimes are not dependent on season or location, the be expected in the case of such breakdowns. other external conditions, as can be seen in Especially in the higher locations of Germany’s the illustrations on the right, show both a clear low mountain ranges, for which numerous cases seasonal and geographic dependency. of icing are reported as it is, weather conditions that encourage the formation of ice can still oc- For example, most damage and interruptions to cur well into the spring. For such low mountain operations caused by direct or indirect lightning locations it can also be seen that storms present damage – i.e. voltage surge damage following a significantly higher risk as a cause of turbine lightning strikes into the electricity grid – are malfunctions. reported during the summer. Triggered by sum-
Unknown Storm Grid failure 8% 5% 7% Other cause Lightning 11% 4% icing 3% Loosening of parts 3%
Plant control system 23%
Component failure 36%
Total number of reports: 32166 Fig. 36: Frequency of failure causes
36 German Wind Energy Report 2008 Number of reports per 100 operating months 70 Grid Failure Lightning Storm Icing 60
50
40
30
20
10
0 Fig. 37: Frequency of external condi- Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec tions as a cause of failure
Low Mountain Range
Grid Failure Storm North German Lowlands Lightning Icing
Coast
Fig. 38: Regional distribution of 0 10 20 30 40 50 60 70 external conditions as a cause of Number of reports per 100 operating years failure
German Wind Energy Report 2008 37 Failure rate on operations and cost-efficiency. Rather it is above all the severity of the individual incidents As part of the WMEP programme the wind of damage. As it is not possible in the German turbine operators reported all maintenance work Wind Monitor to record the repair costs per undertaken. More precise information on fail- incident of damage or per maintenance job, ures can be found in these reports themselves. the intention here is to use the outage dura- Failures may have been repaired at the same tion for assessing the severity of the failure that time as regular maintenance work was being has occurred. The annual failure rate and the done or, following operational outages, it may downtime per failure are therefore portrayed in also have initiated unscheduled work. Some- the adjacent illustrations. Illustration 41 shows times damage affects several components at once again the close link with turbine size. It is the same time, making it possible to undertake apparent that in particular the frequent incidents repairs of multiple parts simultaneously with one of failures relating to the electrics (excluding deployment. It can be seen from illustration 39 generator) could be repaired relatively quickly. how the frequency of affected subassemblies The downtime in the case of such failures is on varies with the size of the wind turbine. It is no- average 1 to 1.5 days. While failures of the gen- ticeable that in the case of turbines with greater erator and drive train needs repairing much less capacity the parts of the electrical components frequently, such failures does, however, cause are affected much more frequently. Around a outages of 5 to 7 days at a time. It can also be third of all damage is accounted for here by the assumed that the repair costs are significantly electrics, generator, control unit and sensors. higher, as a crane is often required for such repairs. It is not just the failure rate to certain subassem- blies that is the definitive factor in the impact
100%
90%
80% Electrical System
70% Sensors Electronic Control System Generator 60% Rotor Hub Hydraulic System 50% Yaw System Drive Train 40% Structural Parts Gear Box 30% Frequency of affected subassembly affected of Frequency Rotor Blade Mechanical Brake 20%
10%
0% 0 38 German Wind Energy Report 2008 Electrical system Electronic control system Sensors Hydraulic system Yaw system Rotor hub Mechanical Brake Rotor blades Gear box Generator Structural parts Drive train Fig. 40: Frequency of failures of the 1 0,75 0,5 0,25 0 2 4 6 8 subassemblies and typical downtime Annual failue rate Downtime per failure [days] per failure P1000 Electrical system 500P<1000 Electronic control system P<500 Sensors Hydraulic system Yaw system Rotor hub Mechanical Brake Rotor blades Gear box Generator Structural parts Drive train Fig. 41: Frequency of failures of the 1 0,75 0,5 0,25 0 2 4 6 8 subassemblies and typical down- time per failure for different power Annual failue rate Downtime per failure [days] classes German Wind Energy Report 2008 39 Availability over the years. While there has been a continual improvement of availability since 2002 and the The aim of maintenance work is to achieve value from 2006 (technical availability of 99 %) high availability of the wind turbines while at represents the best result of the evaluations the same time keeping costs as low as possible. conducted in the WMEP, the availability levels Unplanned outages should be avoided. The on average have actually always been between following illustrations show the technical avail- 98 and 99 % ever since the start of the monitor- ability levels of the wind turbines recorded in the ing programme. As shown already in illustration WMEP programme. The top illustration shows 41, wind turbines of larger capacity categories the availability levels achieved in the individual have a greater annual failure rate. The outage years, while the bottom one shows the availabil- period resulting from any damage is, however, ity levels for different categories of capacity and generally much shorter than in the case of location. smaller turbines, the consequence of which is only slightly lower technical availability. This, The illustrations are based on a number of however, is more likely to be thanks to quick definitions that draw on the VDEW’s (German technical support and less to the high reliability Electricity Association’s) ‘Energy Management of the turbines. Terminology’: ‘Technical availability’ is defined as the percentage ratio of available time to In illustration 38 we saw how the cause of nominal time. ‘Nominal time’ is the total con- breakdowns is regionally linked to external con- secutive reporting period. ‘Non-available time’ ditions. The technical availability of the different is the period during which the turbine was not site categories can now be seen in illustration functional. This is made up of a scheduled part 42. In this respect the sites in Germany’s low (maintenance jobs) and an unscheduled part mountain ranges, which also show the great- (breakdowns and damage). est frequency of breakdowns due to external conditions, have the lowest levels of availability. When interpreting the results it must be borne in However, as external causes (as already shown mind that the data set and thus also the sample in illustration 36) are the reason for the break- used for the evaluations show in part some down in less than a quarter of all cases, it can be major variations. There is, for instance, less infor- assumed here too, due to the wide spread of the mation available on megawatt category turbines turbines, that the importance of the mainte- than for turbines of average and smaller nominal nance and repair service is the key influencing capacity. In terms of the temporal trend in avail- factor. ability no significant change can be determined 40 German Wind Energy Report 2008 100,00% 99,50% 99,00% 98,50% Technical Availability 98,00% 97,50% 97,00% 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 100,00% 99,50% 99,00% 98,50% 98,00% Technical Availability 97,50% 97,00% Fig. 42: Average availability for se- WMEP P<500 500P<1000 P1000 North Low Coast Line veral years and for different power Average German Mountain Lowlands Range classes and location categories German Wind Energy Report 2008 41 8 Economics Onshore feed-in tariffs The most important basic provisions of the amendments to the Renewable Energies Act are Since the Electricity Feed-in Act (StrEG) came shown in table 7. into force on 1st January 1991, feed-in tariffs in Germany have been regulated by law. The level The Act makes special provisions for the ‘repow- of the payment at that time was at least 90 % of ering of wind turbines’. In the 2004 version, for the average income per kilowatt-hour accruing instance, the provisions relating to repowering from the power supply companies’ sale of elec- created the first financial incentive for replacing tricity to all end consumers [13]. In April 2000 old turbines with more powerful, modern ones. the Electricity Feed-in Act (StrEG) was supersed- The version of the Act applicable from 2009 ed by the ‘Renewable Energies Act – (EEG)’. This contains several new provisions in this area: if was in turn amended on 1st August 2004 and on machines over ten years old from the same or a 6th June 2008. The last amendment came into neighbouring district are taken down and new force on 1st January 2009. turbines providing two to five times the capacity installed, the new turbines receive, in addition The minimum payment is regulated in the to the standard initial payment, a bonus of 0.5 Renewable Energies Act by a yield-dependent cents/kWh. payment level, which is defined by a so-called ‘reference yield’. For wind turbines that went There is another new provision in the form of into operation up to a certain date it stipulates the ‘System Services Bonus’ of 0.5 cents/kWh. in the first instance an initial level of payment for This bonus rewards increased requirements in a minimum period of 5 years. Depending on the terms of grid management. Such requirements, quality of the site, the feed-in payment subse- which are defined in a separate ordinance, con- quently gets reduced to a base tariff. At very tain, for example, specifications in respect of: high yield locations the reduction takes place immediately upon expiry of the fifth year, while • How the turbines behave in the event of at sites with less wind payment of the increased faults rate gets extended by two months for every • Stability of voltage and frequency 0.75 % of minimum yield relative to the 150 % • Reactive power provision of the reference yield. Another amendment in the Act is the possibility The site quality is determined here by the use of of direct marketing. In future it is being made a reference site. At the reference site the prevail- possible for wind turbine operators to decide on ing wind conditions have by definition a Rayleigh a monthly basis whether they sell the electric- distribution with an average annual wind speed ity they have generated to the local distribution of 5.5 m/s at a height of 30m above ground, system operator at the Act’s feed-in tariff or on a logarithmic height profile and a roughness independently negotiated terms to other grid length of 0.1 metres. operators or electricity traders. If indicated in due time, it is also possible to have a specified The payment rate for new wind turbines for percentage of the electricity generated by the generating electricity from wind power also wind turbine compensated via the Act and to depends on the calendar year in which these market the other portion to buyers directly, e.g. turbines first go into operation. There will be bilaterally or via an electricity exchange such as a reduction of the payment, for instance, of EEX (the European Energy Exchange). 1 % p.a. for turbines going into operation after 1st January 2010. 42 German Wind Energy Report 2008 EEG-1 EEG-2 EEG-3 Valid from 04/2000 08/2004 01/2009 Initial tariff [c € / kWh] 9,10 8,70 9,20 Base tariff [c € / kWh] 6,19 5,50 5,02 Annual degression [ %] 1,5 2 1 Table 7: Feed-in tariff for electricity Start of degression 01/2002 01/2005 01/2010 from wind power Offshore feed-in tariffs 13 cents/kWh and thus works out significantly higher than the onshore payment. Turbines To enable offshore turbines to operate profit- that have been installed by 31st December 2015 ably as well there are special provisions in the also receive an additional 2 cents/kWh as an Renewable Energies Act for wind power turbines ‘Earlybird Bonus’. The progressive reduction is at at sea. Offshore turbines are defined here as a rate of 5 % and does not set in until 2015. wind power turbines 3 nautical miles and more beyond the coastline. In order to make entry into offshore wind energy utilisation in Germany easier, the initial tariff As no offshore turbines have yet gone into was raised to a level comparable with other EU operation in Germany, older versions of the Act countries. As a counter-move, however, the base had no effect. A more key factor for offshore tariff, at 3.5 cents/kWh, was set appreciably development is the payment rates planned for lower. 2009. The initial tariff (valid for twelve years) is Fig. 43: Feed-in tariff for electricity from wind power German Wind Energy Report 2008 43 The initial tariff period is extended for offshore The trend in respect of average operating costs, turbines erected at a distance of at least twelve expressed in euros per kW of installed capac- nautical miles from the coast and in water at ity, shows in principle lower costs as the size of least 20 metres deep. For each full nautical mile wind turbine goes up. In absolute values these in excess of twelve the period is extended by costs are around € 30/kW for wind turbines with half a month and for each additional full metre nominal capacities of less than 300 kW, around of water depth by 1.7 months. € 20/kW to € 25/kW for turbines in 300 kW to 1000 kW output category and around € 15/kW This graduation of the initial tariff period for those with nominal capacities of over depending on the distance from the coast and 1000 kW. For a wind turbine with 2,000 kW of the depth of the water is depicted in illustration nominal capacity this equates to approximate 44. As can be seen, several of the planned wind annual operating costs of € 30,000. farms are able to receive the high initial payment for four years longer, i.e. for a total of 16 years. More meaningful than the relationship of annual In addition to the provisions of the Renewable costs to turbine nominal capacity (€ / kW) are the Energies Act, the Expedition of Infrastructure figures for specific costs in comparison to annual Planning Act, which came into force on 17th electricity generation. The results of the analyses December 2006, also plays a key role in the show that yield-specific operating costs averaged development of offshore wind power. The Act over the long term are around 1-3 eurocents per stipulates amongst other things that the grid kilowatt-hour. The trend that in principle specific operators must pay the costs for connection to costs go down as the size of turbine goes up is the grid. The costs thus incurred are passed on apparent here too. to all electricity customers. When interpreting these analyses relating to Operating costs operating costs it must be borne in mind that they relate only to certain types of costs, i.e. for The development of the profitability of wind maintenance, maintenance contracts, repairs, power was assessed by ISET as part of the insurance policies, package contracts, leasing WMEP programme and German Wind Moni- and miscellaneous expenses. Costs for business tor project. The database for analyses relating management, taxes and electricity procure- to operating costs consists of a total of around ment, plus capital costs such as depreciation, are 14,300 reports from the period 1993 to 2007. explicitly excluded from these analyses. Illustration 45 shows the long-term values of average operating costs per kW of nominal capacity and the average specific operating costs per kWh of annual energy yield for different categories of capacity. 44 German Wind Energy Report 2008 Fig. 44: Duration of the initial tariff for offshore wind turbines 1 - 70 71 - 140 141 - 210 211 - 280 281 - 350 351 - 420 421 - 490 491 - 560 Rated Power Class [kW] Class Power Rated 561 - 630 800 - 1.000 >= 1500 Fig. 45: Average operating costs 30 20 10 0 1 2 3 per kW rated power, and average €/kW c€/kWh specific operating costs per kWh of Operational Costs annual energy yield German Wind Energy Report 2008 45 Changing costs of turbine equipment Although both types of presentation are based on the same base data, the results nevertheless Capital expenditure costs represent a crucial appear contradictory. While in the case of the factor in working out the economics of wind change in capacity-specific prices €( /kW) the power projects. These include the costs for the trend that can be subjectively ‘sensed’ or ‘felt’ wind turbines themselves and all additional costs towards higher turbine prices is documented, required for planning, approval, construction we see an opposing result in the yield-specific and commissioning. One of the focal points of presentation. For the years 2004 to 2006 the the evaluations conducted as part of the WMEP analysis records a constant decrease of the programme was on the analysis of the long-term yield-specific prices in€ /kWh. The explanation change in prices, especially considering the con- for this result comes from the turbines’ increased tinual enhancements both in relation to turbine efficiency. While the higher towers and larger size and also to the advances in technology and rotor diameters increasingly marketed in recent turbine efficiency. It was initially possible, in years, plus technical enhancements to the tur- addition to the nationwide wind turbine master bines, result on the one hand in higher procure- data, to also incorporate as base data for the ment costs (€/kW), they also lead on the other analyses the wind turbine prices published an- to significantly higher power yields. The scaling nually in various trade magazines. However, cur- of the wind turbine prices to the annual power rent prices for wind turbines are now no longer yields achieved at the Renewable Energies Act published and can be ascertained only through reference site thus produces the trend towards enquiries to manufacturers and operators. lower yield-specific costs. One exception here is the year 2007, for which slightly higher specific The findings reflect the tendency of the change costs were determined. in prices, namely higher turbine prices than in previous years. The following illustrations com- Using the learning curve from both illustrations press the available information in each instance the ‘progress ratio’ can be calculated in each into one data point per year, shown in one case case as the long-term trend. In the case of the as specific price per kilowatt of installed nominal capacity-specific data this is 97 % and thus still capacity (€ /kW) and once as specific price per trending downwards. A progress ratio of 97 % kilowatt-hour of annual power yield at the refer- means that for every doubling of the cumula- ence site (cents/kWh) [14]. tive installed capacity the prices go down in real terms by three percent. In the diagram of the The data for the calculated prices is shown yield-specific price trend €( /kWh) the progress weighted and adjusted for inflation. The scaling ratio is 91 %, corresponding to a long-term price to actual price levels was done by converting the reduction of 9 % per doubling of the cumulative nominal values using the GDP deflator in accord- installed capacity. If we look just at the period ance with current information from the Federal of the last ten years, we can see here a progress Office of Statistics [15]. According to this, the ratio of 93 % / a reduction in specific costs of nominal value of the specific price per kilowatt 7 % per doubling of capacity. During this period of installed nominal capacity for 2007 is around the cumulative installed capacity was doubled € 1,071/kW and the nominal value of the yield- around three times. specific price around€ 0.40/kWh. 46 German Wind Energy Report 2008 WT purchase price 5.000 [ € / kW ] 2.500 Progress Ratio = 97% Progress Ratio = 101% 1991 1996 2000 2007 1.000 500 10 100 1.000 10.000 100.000 Total installed capacity [MW] Fig. 46: WT price (real) in €/kW spec. turbine price per kWh annual energy yield (@ reference site) 1,0000 1991 1996 2000 2007 Progress Ratio = 91% Progress Ratio = 93% €|2000| / kWh reference yield 0,1000 Fig. 47: Specific WT price per kWh 10 100 1000 10000 100000 of annual energy yield at the EEG cumulated installed capacity [MW] reference site in c€/kWh German Wind Energy Report 2008 47 9 Appendix A description of the wind-measuring Using an interval length of 5 minutes, the long- network term data is formed from this raw data and reduced to 22 statistical values. The data is saved The ISET measurement network was built up in so-called day files in a ring memory. Each day in stages as part of the broad-scale ‘250 MW file is made up of the following: Wind’ test programme and the supporting sci- entific project that ran alongside it, the ‘Scien- • Series of long-term measurements (288 five- tific Measurement and Evaluation Programme’ minute (WMEP). Both initiatives came to an end in • intervals) 2006. Since 2007, the German Ministry for the • Wind speed classification Environment, Nature Conservation and Nuclear • (19 categories) Safety (BMU) has been supporting the ‘German • Incident data (through incident triggering), Wind Monitor’ project, with which the WMEP’s • Diagnosis data (condition of the measuring successful work is to a large extent being contin- apparatus) ued, albeit on a smaller scale. • Measurement parameters At its maximum stage of development the The measurement data recorded each day is wind-measuring network consisted of 180 data automatically collected at night by the data logging devices. Data loggers and wind meas- processing centre and loaded into a database. In urement instruments are now installed at a total addition to the ‘long-term measurements’ it is of 60 representative sites. The data loggers also possible in the event of trigger values being are connected by modem and the public fixed exceeded to carry out ‘incident measurements’ line or mobile telephone network to the data for high-resolution recording (10 Hz) of extreme processing centre at ISET, thus forming the ISET situations. 10 Hz sampling data can also be measurement network. The following signals are accessed directly online and over periods of any registered using a sampling rate of 10 Hz: length without interrupting the long-term cap- ture of statistical data. The wind conditions are • The wind turbine’s active electrical power measured as standard at heights of 10 and 30 • The status of the grid connection metres above the ground. At many measuring • Wind speed posts 50-metre high masts have been erected on • Wind direction which wind data is recorded at various heights. Fig. 48: ISET’s wind measurement network at maximum stage of development und reduced wind measurement network (right) 48 German Wind Energy Report 2008 Climate data is also collected in each case at • Air pressure one height. These masts are fitted with special • Air humidity weather stations that work in a similar way to • Temperature the data recording devices and in addition to • Precipitation the usual wind signals at measurement heights • Solar radiation of 10, 30 and 50 metres, also collect and record the following meteorological measurements: 200 175 150 125 100 DEG-Locations 75 50 25 0 1991 1993 1995 1997 1999 2001 2003 2005 2007 Fig. 49: Development of the measu- rement network Year Fig. 50: Data flow of the measure- ment network German Wind Energy Report 2008 49 Results wind measurement network 2007 stated are the long-term averages (values for 2007 in parentheses) Measure- Postal Measure- Height Measurement Weibull Federal state ment-ID code Location ment since _NN [m] height [m] A [m/s] Weibull k Baden- 1101 79874 Breitnau Aug. 92 1.050 10 4,2 (4,5) 1,4 (1,4) Württemberg 2801 74749 Rosenberg Jul. 06 352 10 4,0 (4,2) 1,6 (1,6) Bavaria 2701 96199 Zapfendorf Feb. 00 375 30 4,1 (4,7) 1,8 (1,9) Brandenburg 52101 15326 Podelzig Feb. 97 50 10 4,7 (4,6) 1,8 (2,0) 52102 15326 Podelzig Feb. 97 50 30 5,7 (6,1) 2,2 (2,3) 53101 16845 Sieversdorf Nov. 01 25 10 3,2 (4,1) 1,4 (1,6) 53102 16845 Sieversdorf Nov. 01 25 30 4,7 (6,1) 1,9 (2,5) Hamburg 35501 21039 Hamburg-Neuengamme Aug. 95 2 10 3,7 (4,7) 1,6 (1,9) 35502 21039 Hamburg-Neuengamme Aug. 95 2 30 4,8 (5,9) 1,9 (2,1) Hessen 1301 34639 Schwarzenborn Dez. 92 590 10 4,9 (5,7) 2,0 (2,2) Mecklenburg- 52002 17509 Wusterhusen Nov. 95 20 10 5,0 (5,5) 1,9 (1,9) Western 52001 17509 Wusterhusen Nov. 95 20 30 6,2 (6,8) 2,4 (2,5) Pomerania 52402 18146 Rostock-Stuthof Apr. 99 2 10 4,8 (5,1) 1,7 (1,6) 52401 18146 Rostock-Stuthof Apr. 99 2 30 6,2 (6,5) 2,1 (2,0) Lower Saxony 11502 26897 Hilkenbrook Apr. 92 9 10 3,7 (4,8) 1,5 (1,9) 11501 26897 Hilkenbrook Apr. 92 9 30 5,4 (7,0) 1,9 (2,4) 13301 30974 Wennigsen Okt. 93 130 10 4,8 (5,0) 1,6 (1,6) 13302 30974 Wennigsen Okt. 93 130 38 6,3 (6,7) 2,0 (2,0) 14402 26434 Wangerland Jun. 01 2 10 5,8 (6,1) 2,1 (2,1) 14403 26434 Wangerland Jun. 01 2 32 7,4 (7,7) 2,8 (2,7) 15101 49685 Hoheging Sep. 95 40 10 3,9 (4,0) 1,6 (1,7) 15801 26529 Wirdum Apr. 96 0 34 6,6 (6,9) 2,3 (2,3) 16112 26506 Norden-Ostermarsch Jul. 00 0 40 7,4 (7,6) 2,5 (2,4) 17102 26723 Emden-Larrelt Apr. 02 0 10 5,4 (5,5) 2,3 (2,1) 18302 38275 Steinlah Aug. 01 160 10 4,4 (4,5) 1,6 (1,7) 18301 38275 Steinlah Feb. 99 160 30 5,7 (5,9) 1,8 (1,8) 50 German Wind Energy Report 2008 Measure- Postal Measure- Height Measurement Weibull Federal state ment-ID code Location ment since _NN [m] height [m] A [m/s] Weibull k North Rhine- 301 48157 Münster Jan. 92 55 10 2,9 (3,0) 1,5 (1,5) Westphalia 903 33184 Altenbeken Mrz. 93 360 10 4,8 (5,8) 1,7 (1,8) 901 33184 Altenbeken Jun. 92 360 30 5,4 (6,0) 1,8 (2,0) 1201 32351 Stemwede Okt. 92 46 10 2,8 (2,9) 1,4 (1,5) 2101 33181 Wünnenberg-Helmern Jul. 97 365 10 4,5 (4,8) 1,8 (1,8) 2102 33181 Wünnenberg-Helmern Jul. 97 365 30 6,6 (6,5) 2,2 (2,3) 2201 53949 Dahlem-Berk Nov. 97 610 30 5,2 (5,5) 1,8 (1,8) 203 58091 Hagen-Dahl Mai. 03 390 10 4,4 (4,5) 1,8 (1,9) 202 58091 Hagen-Dahl Mai. 03 390 30 5,5 (5,8) 2,3 (2,5) Rhineland- 2601 57612 Kroppach Okt. 99 360 10 4,2 (4,4) 1,8 (1,9) Palatinate 2602 57612 Kroppach Okt. 99 360 30 5,1 (5,3) 2,1 (2,3) Saarland 2401 66629 Freisen Jun. 98 582 10 4,7 (4,7) 1,7 (1,6) 2402 66629 Freisen Jun. 98 582 30 6,0 (6,1) 2,0 (2,0) Saxony 53201 01774 Beerwalde Jul. 03 460 10 4,2 (4,2) 1,7 (1,8) 53202 01774 Beerwalde Jul. 03 460 30 5,6 (5,7) 2,3 (2,3) Saxony-Anhalt 52801 39359 Calvörde Sep. 00 60 10 3,7 (3,9) 1,6 (1,7) 52802 39359 Calvörde Sep. 00 60 30 4,9 (5,4) 1,8 (2,0) Schleswig-Holstein 30501 23570 Lübeck-Brodten Feb. 92 25 10 3,9 (4,1) 1,6 (1,6) 31501 25826 St. Peter-Ording Apr. 92 1 10 5,8 (6,1) 2,0 (1,9) 31502 25826 St. Peter-Ording Nov. 01 1 30 7,7 (7,9) 2,5 (2,4) 33401 24872 Groß Rheide Jun. 92 10 10 4,3 (4,5) 1,6 (1,6) 33402 24872 Groß Rheide Jan. 02 10 30 6,4 (6,7) 2,3 (2,4) 34202 23769 Fehmarn Sep. 92 3 10 6,5 (6,9) 1,9 (1,8) 34201 23769 Fehmarn Sep. 92 3 30 8,0 (8,9) 2,1 (2,2) 34801 25845 Nordstrand Jan. 94 1 10 6,0 (6,2) 1,9 (1,9) 35401 24647 Wasbek Jul. 95 19 10 2,9 (2,5) 1,3 (1,5) 35402 24647 Wasbek Jul. 95 19 30 4,9 (5,2) 2,0 (2,0) 37402 25709 Kaiser-Wilhelm-Koog Aug. 97 2 10 5,7 (5,6) 1,9 (1,9) 37401 25709 Kaiser-Wilhelm-Koog Aug. 97 2 30 7,3 (7,9) 2,2 (2,4) Thuringia 52201 99510 Wormstedt Feb. 97 280 10 4,0 (4,1) 1,5 (1,6) 53002 07338 Steinsdorf Okt. 01 530 30 5,4 (5,7) 2,2 (2,3) German Wind Energy Report 2008 51 10 Sources [1] BTM Consult ApS, World Market Update 2007 – Forecast 2008 – 2012, Ringköping, DK, 2008 [2] Systemtechnische Analyse der Auswirkungen einer windtechnischen Stromerzeugung auf den konventionellen Kraftwerkspark (Systematic Analysis of the Effects of Wind-powered Electricity Generation on Ger- many’s Conventional Power Stations), Institute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, 1998 [3] The Windicator, Wind Power Monthly, July 2008 [4] BDEW Bundesverband der Energie- und Wasserwirtschaft e.V. (German Energy and Water Industry Association), http://www.vdn-berlin.de/bild_grundlagen_11.asp, Nov. 2007 [5] Details from RWE Transportnetz Strom GmbH pursuant to Article 15 of the Renewable Energies Act (EEG); www.rwe-transportnetzstrom.com/; October 2008 [6] Details from E.ON Netz GmbH pursuant to Article 15 of the Renewable Energies Act (EEG); www.eon-netz.com/; October 2008 [7] Details from Vattenfall Europe Transmission GmbH pursuant to Article 15 of the Renewable Energies Act (EEG); www.vattenfall.de/; October 2008 [8] Details from EnBW Energie Baden-Württemberg AG pursuant to Article 15 of the Renewable Energies Act (EEG); www.enbw.com/; October 2008 [9] BTM Consult ApS, World Market Update 2007 – Forecast 2008 – 2012, Ringköping, DK, 2008 [10] Ingenieurwerkstatt Energietechnik (Energy Technology Engineers’ Work- shop – IWET), Hamburg, 2008 [11] CONTIS map of offshore wind farms (pilot areas) in the German EEZ (North Sea), Federal Maritime and Hydrographic Agency (BSH), Hamburg and Rostock, 2008 [12] CONTIS map of offshore wind farms (pilot areas) in the German EEZ (Bal- tic Sea), Federal Maritime and Hydrographic Agency (BSH), Hamburg and Rostock, 2008 [13] Law on feeding renewable energies into the public grid (Stromein speisungsgesetz / Electricity Feed-in Act) of 7th December 1990 (Federal Law Gazette I p. 2633) (Federal Law Gazette III p. 754-9) last amended by the act on the revision of energy industry legislation of 24th April 1998 (Federal Law Gazette I p. 730 and 734) [14] Federal Law Gazette, 2004 volume, part I no. 40, published in Bonn on 31st July 2004, appendix to Article 10, paragraph 1 and 4, point 4; page 1929 [15] Federal Office of Statistics; Domestic product calculation – Detailed annual results – series 18, volume 1.4 – 2007; as at May 2008; https://www-ec.destatis.de 52 German Wind Energy Report 2008 Institut für Solare Energieversorgungstechnik ISET e. V. Königstor 59 34119 Kassel Tel. + 49(0)561-7294-0 Fax + 49(0)561-7294-100 [email protected] www.iset.uni-kassel.de