Upcoming SlideShare
×

# Wind energy I. Lesson 3. Wind field characterization

1,572 views

Published on

www.devi-renewbale.com
www.ppre.de

0 Likes
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
• Be the first to comment

• Be the first to like this

Views
Total views
1,572
On SlideShare
0
From Embeds
0
Number of Embeds
154
Actions
Shares
0
143
0
Likes
0
Embeds 0
No embeds

No notes for slide

### Wind energy I. Lesson 3. Wind field characterization

1. 1. Wind Energy I Wind field characterizationMichael Hölling, WS 2010/2011 slide 1
2. 2. Wind Energy I Class content 5 Wind turbines in 6 Wind - blades general 2 Wind measurements interaction 7 Π-theorem 8 Wind turbine characterization 3 Wind field 9 Control strategies characterization 10 Generator 4 Wind power 11 Electrics / gridMichael Hölling, WS 2010/2011 slide 2
3. 3. Wind Energy I Motivation Why should we know anything about the wind field ? Atmospheric boundary layer (ABL)Michael Hölling, WS 2010/2011 slide 3
4. 4. Wind Energy I Motivation Why should we know anything about the wind field ? Atmospheric boundary layer (ABL)Michael Hölling, WS 2010/2011 slide 3
5. 5. Wind Energy I Motivation Why should we know anything about the wind field ? Atmospheric boundary layer (ABL)Michael Hölling, WS 2010/2011 slide 3
6. 6. Wind Energy I Motivation Enercon E-126 BARD 5.0http://www.wind-energy-the-facts.org http://www.ecogeneration.com.au Michael Hölling, WS 2010/2011 slide 4
7. 7. Wind Energy I Motivation GROWIAN - Große Windkraftanlage (Big Wind energy converter)Michael Hölling, WS 2010/2011 slide 5
8. 8. Wind Energy I Resource wind m 2 ρ·V ρ·A·x 2 Kinetic energy of wind: E = ·u = ·u = 2 ·u 2 2 2 Corresponding power d ρ·A·x 2 for constant velocity u : Pair = ·u dt 2 1 2 dx = ·ρ·A·u · 2 dt 1 = · ρ · A · u3 2 Wind energy converter can NOT convert 100% of that energy ! Consequently the power of the wind energy converter is also smaller: 1 PW EC = cp · · ρ · A · u3 = cp · Pair 2Michael Hölling, WS 2010/2011 slide 6
9. 9. Wind Energy I Resource wind Power curve of wind energy converter - theory rated 2.0 P(u) 1.6 P(u) [MW] 1.2 cut out 0.8 cut in 0.4 0.0 0 10 20 30 u [m/s]Michael Hölling, WS 2010/2011 slide 7
10. 10. Wind Energy I Resource wind Power curve of wind energy converter - realityMichael Hölling, WS 2010/2011 slide 8
11. 11. Wind Energy I Resource wind Annual mean wind speed taken from wind atlasMichael Hölling, WS 2010/2011 slide 9
12. 12. Wind Energy I Resource wind Estimation of Annual Energy Production (AEP) based on annual mean wind speed from wind atlas: 2.0 P(u) 1.6 P(u) [MW] 1.2 0.8 500kW 0.4 u annual ≈ 7m/s 0.0 0 10 20 30 u [m/s]Michael Hölling, WS 2010/2011 slide 10
13. 13. Wind Energy I Resource wind Is such a calculation realistic ? How does real wind behave ? Wind velocity time series (20 days)Michael Hölling, WS 2010/2011 slide 11
14. 14. Wind Energy I Resource wind Calculation of 10-minute averaged wind speedMichael Hölling, WS 2010/2011 slide 12
15. 15. Wind Energy I Resource wind Calculation of 10-minute averaged wind speedMichael Hölling, WS 2010/2011 slide 12
16. 16. Wind Energy I Resource wind Distribution of 10-minute averaged wind speeds (u)Michael Hölling, WS 2010/2011 slide 13
17. 17. Wind Energy I Resource wind Estimation of energy production based on wind distribution (u)Michael Hölling, WS 2010/2011 slide 14
18. 18. Wind Energy I Resource wind Estimation of energy production based on wind distribution (u)Michael Hölling, WS 2010/2011 slide 14
19. 19. Wind Energy I Resource wind Estimation of energy production based on wind distribution E(u) (u)Michael Hölling, WS 2010/2011 slide 14
20. 20. Wind Energy I Resource wind Estimation of energy production based on wind distribution E(u) (u)Michael Hölling, WS 2010/2011 slide 14
21. 21. Wind Energy I Resource wind Estimation of energy production based on wind distribution E(u) (u)Michael Hölling, WS 2010/2011 slide 14
22. 22. Wind Energy I Resource wind Estimation of energy production based on wind distribution E(u) (u)Michael Hölling, WS 2010/2011 slide 14
23. 23. Wind Energy I Resource wind Estimation of energy production based on wind distribution E(u) (u)energy production: N N E= E(ui ) = counts(ui )/6 · P (ui ) i=1 i=1Michael Hölling, WS 2010/2011 slide 14
24. 24. Wind Energy I Resource wind Comparison of energy production for mean wind speed and 10- minute averaged wind speed distribution (example based on data of 20 days): u = 6.3m/s 244 kW E = counts(< u >)[h] · P (< u >) = 24 · 20 · 244 = 117120kW hMichael Hölling, WS 2010/2011 slide 15
25. 25. Wind Energy I Resource wind E(u) N NE= E(ui ) = counts(ui )/6 · P (ui ) = 166, 920kWh i=1 i=1Michael Hölling, WS 2010/2011 slide 16
26. 26. Wind Energy I Resource wind Description of wind speed distribution (u)Michael Hölling, WS 2010/2011 slide 17
27. 27. Wind Energy I Resource wind Convert to probability density by normalizationMichael Hölling, WS 2010/2011 slide 18
28. 28. Wind Energy I Resource wind Distribution can be fitted by Weibull distribution A = scaling parameter k = form parameter A=7 k = 2.59Michael Hölling, WS 2010/2011 slide 19
29. 29. Wind Energy I Resource wind Weibull distribution u [m/s]Michael Hölling, WS 2010/2011 slide 20
30. 30. Wind Energy I Resource wind Wind speed variation with height Atmospheric boundary layer (ABL)Michael Hölling, WS 2010/2011 slide 21
31. 31. Wind Energy I Wind ﬁeld characterization Meteorological approach: logarithmic profile roughness length for topographical effects thermal effects International Electrotechnical Commission (IEC) approach: power law profile standard for site assessment Alternative approach: stochastic analysis high frequency data for better understandingMichael Hölling, WS 2010/2011 slide 22
32. 32. Wind Energy I Meteorological approach Wind speed u (mean values) as a function of height z: Logarithmic profile: u* = friction velocity (typically between 0.1m/s and 0.5m/s) k = von Karman constant, about 0.4 z0 = surface roughness lengthMichael Hölling, WS 2010/2011 slide 23
33. 33. Wind Energy I Meteorological approach classes 3 2 1 0Michael Hölling, WS 2010/2011 slide 24
34. 34. Wind Energy I Meteorological approach classes 3 2 1 0Michael Hölling, WS 2010/2011 slide 25
35. 35. Wind Energy I Meteorological approach Influence of friction velocity u* on profileMichael Hölling, WS 2010/2011 slide 26
36. 36. Wind Energy I Meteorological approach Influence of friction velocity u* on profileMichael Hölling, WS 2010/2011 slide 27
37. 37. Wind Energy I Meteorological approach Thermal effects make ABL stable, neutral or unstable Monin Obukhov lengthMichael Hölling, WS 2010/2011 slide 28
38. 38. Wind Energy I IEC approach Wind speed u (mean values) as a function of height z: Power law profile: z2 α needs to be fitted from data !Velocity at height z can be determined by: α z z1 u(z) = u(z1 ) · z1Commonly used for wind energy applications !Michael Hölling, WS 2010/2011 slide 29
39. 39. Wind Energy I Wind proﬁle What is the difference between the two approaches ?Michael Hölling, WS 2010/2011 slide 30
40. 40. Wind Energy I Wind proﬁle What is the difference between the two approaches ? u(z2) u(z1)Michael Hölling, WS 2010/2011 slide 30
41. 41. Wind Energy I Wind proﬁle What is the difference between the two approaches ? u(z2) u(z1)Michael Hölling, WS 2010/2011 slide 31
42. 42. Wind Energy I Site characterization / assessment IEC demands information for site characterization: annual mean wind velocity parameters for Weibull distribution of 10-min averaged wind speeds annual mean wind profile σ<u>10min turbulence intensity Ti = < u >10minMichael Hölling, WS 2010/2011 slide 32
43. 43. Wind Energy I Alternative approach What happens in reality ?Michael Hölling, WS 2010/2011 slide 33
44. 44. Wind Energy I Alternative approach What happens in reality ?Michael Hölling, WS 2010/2011 slide 34