1. Investigating the influence of farm layout on the energy production of simple wind park configurations Sercan Uysal Renewable Energy (MSc RENE) Master Thesis September 5, 2014 KTH Royal Institute of Technology In cooperation with

2. Outline Objectives Wind Energy Wake Concept ◦ Aerodynamics ◦ Wake Models Simulations ◦ Methodology ◦ Simulation Settings Results Conclusions & Future Works Questions & Answers 2

3. Objectives Investigating wake loss phenomenon depending on wind farm parameters : Wind farm layout and number of wind turbines Downwind and crosswind turbine spacing Power and thrust characteristics of wind turbines Wind farm terrain conditions Ambient turbulence intensity Single and multiple/overlapping wake cases 3

4. Wind Energy A long journey from 1 B.C. To 21 th century 4

5. Wake Concept Decrease in wind energy Velocity Deficit Enhanced fatigue load Increased Turbulence Characteristics of Wake Region 5

6. Wake Concept Wake Aerodynamics 6 Near Wake Rotor Aerodynamics Far Wake Wind Turbine Interactions Wake Region Development Ambient TurbulenceTurbine Induced Turbulence

7. Wake Concept Wake Models 7 Modified surface roughness length Distributed roughness approach Explicit models (PARK Model) Conservation equations Implicit models (Eddy Viscosity Model) Navier-Stoke equations Individual wake formation approach

8. Simulations Methodology 8 WindFarmer MS Excel MATLAB WAsP Tools Map EditorClimate Analyst Map Data Wind Speed and Dirct. Distribution Freq. Data Wake model selection Running simulations Recording simulation results Farm layout creation Processing the results

9. Simulations Simulation Parameters 9 Normal direction to turbine rows (30 o width) Weibull distribution : A = 11.9 m/s, k = 2.04, U = 10.50 m/s Wind Conditions z0 = 0.0002 m (open sea) z 0 = 0.0300 m (agricult. area ) z 0 = 0.1000 m (agricult. area with housing) Terrain Conditions I0 = 5 % I 0 = 10 % I 0 = 15 % Ambient Turbulence Type 1 (P = 750 kW, zhub = 46 m, D = 48 m) Type 2 (P = 1.5 MW, z hub = 80 m, D = 70 m) Type 3 (P = 3.0 MW, z hub = 100 m, D = 100 m) Turbine Type Modified PARK Eddy Viscosity (EV) Wake Model

10. Results Case 1 10 A - Abreast PlacementB - Tandem Placement Case Settings Varying crosswind (CS) and downwind (DS) turbine spacing All terrain conditions All ambient turbulence intensities All turbine types Both wake model Incident Wind

11. Results Case 1A – Modified PARK & EV Models Simulations ◦ No significant interaction for CS > 2 rotor diameter (D) ◦ Interactions for CS < 2D cannot be interpreted  WindFarmer is not validated  Not a realistic configuration 11

12. Results Case 1B – Modified PARK Model Simulations 12 Type 1 (750 kW) Turbine Type 3 (3.0 MW) Turbine Wake recovery with increasing DS Stronger initial wake deficit with higher C T Faster wake recovery with higher surface roughness Conclusions

13. Results Case 1B – Eddy Viscosity Model Simulations 13 Type 1 (750 kW) Turbine Type 3 (3.0 MW) Turbine Consistency between Modified PARK and EV models Faster wake recovery with higher ambient turbulence intensity Conclusions

14. Results Case II 14 Case II - ACase II - B Case Settings Varying crosswind (CS) and downwind (DS) turbine spacing z 0 = 0.03 m I 0 = 12.5 % Type 3 (3.0 MW) Turbine EV wake model Incident Wind

15. Results Case II - A 15 Minimum energy production within full wake region CS determines full wake region distance Conclusions

16. Results Case II - B 16 Larger energy deficit compared to Case II-A due to multiple wake effect Conclusions

17. Results Case III 17 Case III - ACase III - B Case Settings Varying crosswind (CS) and downwind (DS) turbine spacing z 0 = 0.03 m I 0 = 12.5 % Type 3 (3.0 MW) Turbine EV wake model Incident Wind

18. Results Case III - A 18 Almost negligible effect of partial wake as compared to full wake Conclusions

19. Results Case III - B 19 More complex energy production trend Larger energy deficit due to accumulated wake effect of 2 rows Conclusions

20. Results Case IV 20 Incident Wind Case Settings Varying crosswind (CS) and downwind (DS) turbine spacing; and offsetting of second row z 0 = 0.03 m I 0 = 12.5 % Type 3 (3.0 MW) Turbine EV wake model

21. Results Case IV – Outer Turbine 21 2D Crosswind Spacing 5D Crosswind Spacing Maximum energy deficit with zero offset More symmetrical trends for larger CS Weaker response to shifting with increasing DS Conclusions

22. Results Case V ◦ 8 wind turbines ◦ 10 different farm layouts ◦ Investigation of total farm efficiency actual energy production maximum achievable energy production 22 Case Settings Varying crosswind (CS) and downwind (DS) turbine spacing; and total farm area z 0 = 0.003 m I 0 = 12.5 % Type 3 (3.0 MW) Turbine EV wake model Eff =

23. Results 23 RectangleBowReverse Bow Incident Wind Half CircleModified Half Circle ReverseHalf CircleSquareCircle Modified Rectangle Modified Rectangle 2

24. Results Case V ◦ For 95% farm efficiency 24 Modified rectangle perfoms the best due to offset based layout Square and Modified rectangle 2 perform the worst Conclusions LayoutFarm Area (D 2 )Crosswind Length (D)Downwind Length (D) Rectangle28.86.04.8 Bow28.15.25.4 Reverse Bow28.15.25.4 Half Circle26.35.25.5 Modified Half Circle22.85.25.4 Reverse Half Circle26.35.25.5 Square90.29.5 Circle34.26.6 Modified Rectangle16.04.0 Modified Rectangle 242.03.014

25. Conclusions Simulations are performed in the existence of a predominant wind direction No significant interaction is observed in abreast placement Higher surface roughness length and ambient turbulence intensity enable faster wake recovery Higher C T results in stronger wake initiation Full wake region dominates wake loss up to 4-5D DS Layouts created considering these observations, such as “Modified Rectangle” performs the best in terms of required farm area 25

26. Future Works Larger wind direction bins can be used More terrain characteristics can be added Larger wind farms can be tested 26

27. Questions & Answers Thank you! 27