AckermannTh. (ed) Wind Power in Power Systems
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//INTEGRAS/KCG/PAGINATION/WILEY/WPS/FINALS_14-12-04/0470 855088 _3 1_IND 01.3 D – 691 – [677–696/20]
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management systems (WPMS) 372,
373, 375
penetration level 27, 28, 44, 46,
134, 448, 454, 455, 457, 512,
643, 644
plant 38, 39, 40, 48, 50, 144, 156,
174–7, 180, 182, 188, 203, 237,
310, 404, 433
predictability of 155, 161, 228,
366
prediction tool (WPP T) 221, 367,
368, 369, 370, 377, 379
value of 180–94
variations
hourly 154
smoothing effect of 38, 44, 106–8,
151, 153, 158, 159, 164, 379,
394, 445, 448
Wind regime 36, 204, 220
Wind speed
forecast 33, 44, 155, 210, 211,
442
forecast error 146, 148, 158, 159, 226,
375, 376, 393, 447
forecast tools 155
model 559, 568, 576
prediction of 372
Wind turbine
design approaches 22, 23
rotor, see Wind turbine rotor
technology status 8, 17, 21, 23, 36,
42, 116, 311, 340, 537
Type A 262, 264–7, 277, 283, 289,
292, 354, 360, 361, 537, 588,
603–5, 611, 612, 618, 623, 626,
655, 658, 661–3
Type B 259, 264, 537, 665
Type C 259, 261, 339, 423, 587, 588,
632, 657, 668, 669, 672
Type D 259, 261, 263, 278, 536, 542,
657, 670, 673
Wind turbine rotor
development 11
static characteristic 527
Worst-case scenario 83, 89, 90, 155,
271, 453, 463, 672, 673
Written pole synchronous
generator 537
Zephyr 370, 377–9
Index 691
Plate 1MGeographical distribution of wind power in Germany, indicating installed capacity
(MW), as of January 2004. (Reproduced by permission of ISET, Kassel, Germany)
This map was produced by Bernd Möller, Aalborg University, using a geographic information system (GIS). It has
been composed from wind turbine and transmission line data sets and a distribution of electricity consumption. Rural
areas are not included. The data base of wind turbines, their locations and technical properties originate from the
reports of the transmission system operators as of September 2003, available from the Danish Energy Authority. The
location and properties of transmission lines were derived from the online mapping system EnergyData, owned by the
Danish Energy Authority. The distribution of electricity consumption was calculated from a building density grid
available from the Area Information System of the Danish Ministry of the Environment, to which annual power
demand for the year 2003 was related by building and consumer type.
Plate 2MWind power capacity in relation to electricity consumption and the transmission grid
in Denmark as of September 2003. (Reproduced by Permission of Bernd Möller, Aalborg
University, Denmark)
Plate 3MNacelle Enercon E66 1.5 MW. (Reproduced by permission of Enercon, Germany)
Plate 4MNacelle Vestas V90 3 MW. Note: 1= oil cooler; 2 = generator cooler; 3 = transformer; 4 = ultrasonic wind sensors; 5 = VMP-Top controller
with converter; 6 = service crane; 7 = generator; 8 = composite disc coupling; 9 = yaw gears; 10 = gearbox; 11 = parking brake; 12 = machine
foundation; 13 = blade bearing; 14 = blade hub; 15 = blade; 16 = pitch cylinder; 17 = hub controller. (Reproduced by permission of Vestas Wind
Systems A/S, Denmark)