Wind Energy. Wind Engineering and Renewable Energy Laboratory (WIRE) Swiss Federal Institute of Technology - Lausanne (EPFL), Switzerland

Transcription

1 Wind Energy Majid Bastankhah Fernando Porté Ágel Wind Engineering and Renewable Energy Laboratory (WIRE) Swiss Federal Institute of Technology - Lausanne (EPFL), Switzerland

2 Overview I. History of Wind Energy II. Present and Future of Wind Energy III. Wind Turbines IV. Wind Resource Assessment V. Wind Farms

3 Wind machines: A long history Wind power has been very popular for many centuries: - Navigation - Milling - Water pumping - Electricity production

4 Historical development of wind turbines (Wind turbine technology, Spera 2009)

5 Historical development of wind turbines Ancient Persian windmills (Wind turbine technology, Spera 2009)

6 Historical development of wind turbines Vertical axis Drag-based machines Low efficiency (Wind turbine technology, Spera 2009)

7 Historical development of wind turbines Chinese windmills Vertical axis Drag-based machines Used to drain rice fields Made of bamboo and fabric

8 Historical development of wind turbines Horizontal axis Lift-based machines (Wind turbine technology, Spera 2009)

9 Early wind mills in Europe (after 1200 AD): Dutch type Horizontal axis Lift-based machines These machines were used since the 14 th century to drain water from polders in the Rhine river delta.

10 The invention of the Wind Turbine Early electric wind turbines helped electrify remote farms in the US and Europe in the early 1900 s 12 kw 144 blades 17 m diameter 3 kw 3 blades 3-4 m diameter Charles Brush s first wind turbine ( ) Jacobs commercial wind turbine (1932)

11 The birth of the modern wind turbine Smith-Putnam turbine Vermont (USA), ,250 kw wind turbine 53 m diameter Turbine operated for 1100 hours before a blade failed. Smith-Putnam 1.25 MW Turbine Vermont, 1940's

12 I. History of Wind Energy II. Present and Future of Wind Energy III. Wind Turbines IV. Wind Resource Assessment V. Wind Farms

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14 The growth of renewable energies ADVANTAGES Renewable, plentiful and widely distributed power sources Clean, emissions-free (no effect on air quality and climate change) Wind power does not require water, which, in an increasingly water-stressed world, is a major environmental benefit It strengthens energy security by diversifying and decentralizing energy infrastructure Helps spur economic development (job creation and income source in rural areas) New technologies have made wind energy competitive in price Source: REN21 Renewable Energy Global Status Report

15 Motivation Fast Growth of Wind Energy Sector Percentage of electricity (2013): Denmark 33% Spain 21% Germany 8% USA 4% Future targets: UK (Renewables) 20% by 2020 China (Renewables) 12% by 2020 USA (Wind) 20% by 2030

16 Growth of Wind Turbine Size and Power

17 Blades Traditionally built in one piece (limits the size of the turbines due to transportation issues) New models use modular blades

18 Turbine Installation The Enercon E-126 is a wind turbine with a hub height of 135 m, rotor diameter of 126 m and a total height of 198 m, and it can generate up to 7.58 MW. The total weight is about 6,000 t. The list price of one unit is 14 million dollar plus install costs.

19 Growth of Number and Size of Wind Farms Top proposed offshore wind farms Wind Farm Total (MW) Country Blekinge Offshore 2,500 Sweden Korea Offshore 2,500 South Korea Moray Firth 1,300 United Kingdom Triton Knoll 1,200 United Kingdom Creyke Beck A 1,200 United Kingdom Creyke Beck B 1,200 United Kingdom East Anglia 1,200 United Kingdom Irish Sea 1,200 United Kingdom Teesside A 1,200 United Kingdom Teesside B 1,200 United Kingdom Bristol Channel 1,000 United Kingdom Hornsea 1,000 United Kingdom Fukushima Farm 1,000 Japan Top proposed onshore wind farms Wind farm Total (MW) Country Titan Wind Project 5,050 USA Markbygden Wind Farm 4,000 Sweden Dobrogea Wind Farm 1,500 Romania Hartland Wind Farm 500-1,000 USA Silverton Wind Farm 1,000 Australia Aubanel Wind Project 1,000 Mexico Castle Hill Wind Farm 860 New Zealand

20 Gansu Wind Farm Installed: 5.16 GW Target: 20 GW 40 N 50 N Map of largest wind farms 30 N Jaisalmer Wind Farm 1064 MW Shepherds Flat Wind Farm Target: 845 MW 60 N 20 N 70 E 80 E 90 E 100 E 110 E 65 N 120 E 130 E Clyde Wind Farm 350 MW Whitelee Wind Farm 539 MW 45 N 60 N 55 N 30 N 50 N 15 N Alta Wind Energy Center 1020 MW 120 W Tehachapi Pass Wind Farm Target: 705 MW 105 W 90 W Top operational onshore wind farms 75 W 45 N 20 W 15 W Gwynty Môr Target: 576 MW 10 W 5 W 0 5 E 10 E 15 E Top operational offshore wind farms 20 E London Array 630 MW Top onshore wind farms under construction Top offshore wind farms under construction

21 I. History of Wind Energy II. Present and Future of Wind Energy III. Wind Turbines IV. Wind Resource Assessment V. Wind Farms

22 Types of Wind Turbines: Orientation Turbines can be categorized into two overarching classes based on the orientation of the rotor: Horizontal Axis Vertical Axis

23 Different Types of Wind Turbines 3-bladed horizontal-axis wind turbine (HAWT)

24 Number of blades Most common number of blades: 3

25 Number of blades More efficiency with more blades, but improvement becomes marginal. 1 2 blades: 6% increase in efficiency 2 3 blades: 3% increase in efficiency More blades: negligible improvement in efficiency

26 Types of Wind Turbines: Size Small Homes & Farms Remote Applications $5,000-$50, m diameter <10 kw Medium Village Power Hybrid Systems Distributed Power $80,000-$500, m diameter kw Large (250 kw 5 MW) Central Station Wind Farms Distributed Power $750,000 - $3,000,000 (per turbine) m diameter

27 Large Wind Turbine Components

28 Some new concepts: Direct drive turbines Some recent models of turbines (e.g., Enercon) use direct drive and do not need to use of gear boxes. Enercon E-126 This saves space/weight and reduces mechanical loses and maintenance. Enercon E-112

29 Airfoil aerodynamics principles Balance of Momentum Streamlines and streamtubes around a NACA 0012 airfoil. Note the overall downward deflection of the air.

30 Blade airfoils: Same aerodynamic principle as aircraft wings Airfoil shape: Lift forces dominate projection

31 Power in the Wind P wind = 1 2 rav 3 Swept area, A (A = πr 2 ) Mean wind speed, V Air density, ρ Doubling rotor diameter means 4 times more power! R Doubling wind speed means 8 times more power!

32 The wind velocity profile U z u z k zo * ( ) ln zo Aerodynamic roughness

33 The Betz Limit By using mass and energy conservation (Bernoulli s equation), Betz (1919) showed that there is a theoretical limit for the maximum efficiency of a turbine: 59% Modern turbines have efficiencies of about 40-50%.

34 The Power Curve Pitch control I II III

35 Pitch vs. Stall regulation Pitch angle control Blade designed for stalling (massive flow separation) No pitch control

36 Some new concepts: building-integrated turbines In the Bahrain World Trade Center, wind turbines are placed between the two buildings, taking advantage of the increased wind velocity between the two aerodynamic towers. In this case, special attention has to be paid to noise and vibration.

37 Aeroacoustics: noise generation Brooks et al. (1989) Oerlemans et al. (2007)

38 Turbine noise generation: laboratory experiments Surface Microphone (Brüel & Kjær)

39 Multi-rotor wind turbine DTU campus - Denmark

40 I. History of Wind Energy II. Present and Future of Wind Energy III. Wind Turbines IV. Wind Resource Assessment V. Wind Farms

41 Wind Resource Assessment

42 Wind Energy Resource: Regional Average velocity 50 metres above ground Tower with wind speed (cup anemometer) and wind-direction sensors

43 Wind Energy Resource: Numerical Weather Modelling

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45 Wind Measurements: Wind Rose

46 Orography effects Orography has a strong effect on local wind energy potential and it needs to be considered. Numerical modeling plays an important role.

47 Orography: Speed-up effects Streamlines are compressed => wind speed-up!

48 Orography: Flow separation and turbulence enhancement Cathedral Rock Wind Farm, Southern Australia Turbine siting with steep topography (e.g., cliffs or tops of buildings) is challenging due to: High turbulence intensity Locally the air flow slows down and reverses direction (flow separation and recirculation regions)

49 Orography Maps from CFD Computational Fluid Dynamics (CFD) The map must cover a radius of min. 100* hub height. 20km Height contours should be for every 10m.

50 I. History of Wind Energy II. Present and Future of Wind Energy III. Wind Turbines IV. Wind Resource Assessment V. Wind Farms

51 Challenges in design and operation of wind farms o o o Prediction of turbine performance is currently very poor [errors range between 60% underestimation and 150% overestimation of power]. Need for more accurate turbulence-resolving models capable of simulating the complex interactions between turbulent atmospheric flow and wind turbines. Wake effects in wind farms Reduced energy production (up to 50%) and increased fatigue loads associated with high turbulence levels.

52 Atmospheric boundary-layer (ABL) flow What is the atmospheric boundary-layer (ABL) flow? Variable depth Unsteady flow Highly turbulent flow

53 What is turbulence? When I meet God, I am going to ask him two questions: why relativity? And why turbulence? I really believe he will have an answer for the first. Physicist Werner Heisenberg Leonardo da Vinci s turbulent tank ( )

54 Horns Rev wind farm (Denmark) 1.0 Challenges in design (turbine siting) of wind farms Normalized Power Observed data: =270 5 o 0.5 Normalized Power Turbine Row Observed data: =270 5 o WAsP WindSim Wind Turbine Wakes affect both: Turbine Row Power production (due to reduction of wind velocity in the wake) Fatigue loads (associated with increased turbulence levels) 0.5

55 An example of bad wind-farm design: Lilgrund Wind Farm 10 km off the cost of Sweden 48 turbines Siemens SWT Turbine rotor diameter d=93 m; Turbine capacity= 2.3 MW Total capacity: 110 MW Meets electricity demands of homes Separation of only 3.3d- 4.3d between turbines!

56 Lillgrund offshore wind farm Siemens SWT MW 48 wind turbines installed Turbine diameter: d = 92.6 [m] Hub height: H hub = 65 [m] Turbine spacing: 3.3 d and 4.3 d Normalized distance [d] North Wind direction 3.3d 4.3d Row 1 Row 2 Row 3 Row 4 Row D Row C Row B Row 5 Row 6 Row 7 Row 8 Mast Wind turbines Normalized distance [d] Normalized Power Row B Row C Row D Turbine Row

57 Field measurements (real case) Wind-tunnel measurements (scaled-down case) Wind Farm Aerodynamics Numerical simulations Simple analytical model (simplifying governing equations)

58 Numerical Simulations

59 Numerical simulation framework WiRE-LES Weather Model o The numerical simulation framework developed by WiRE is based on the state-of-the-art largeeddy simulation (LES) technique, coupled with weather modeling. o It can be used to optimize the design, operation and integration of wind turbines/farms to the grid. LES with wind turbines Large-Eddy Simulation (LES)

60 Large-Eddy Simulation (LES) Major advantages: o Turbulence resolving ( less uncertainty!) o No tuning of coefficients is required. o Accurate, based on preliminary validation tests.

61 Wind Turbine Modeling: Blade Element Momentum Theory Ω projection Chord line Blade Element c c : local chord length Δr U rel : relative velocity U : incoming velocity Ω : angular velocity α : angle of attack γ : pitch angle

62 Large-Eddy Simulation (LES): Case study 1 Velocity and vorticity contours in the wake of a V112 turbine in a nocturnal boundary layer flow Lu and Porté-Agel (Phys. Fluids, 2011)

63 Case Study 2: Effect of atmospheric turbulence on wakes z o (m) Surface type I u, hub Case 1 5 x 10-1 Rough terrain 12 % Case 2 5 x 10-3 Sea 7 % Case 3 5 x 10-5 Snow-covered flat 5 % Ref: Stull (1988) Boundary-layer depth : 500 m Vestas V80 2 MW wind turbine Hub height : 70 m Rotor diameter : 80 m Wind speed : u hub = 9 m s -1 Turbulence intensity : I u, hub = 5 to 12 (%) LES with ADM-R

64 Case study: Turbine wakes over different terrains Rough z o = 5 x 10-1 m Sea z o = 5 x 10-3 m Snow-covered flat z o = 5 x 10-5 m

65 Rough : z o = 5 x 10-1 m Sea : z o = 5 x 10-3 m Snow-covered flat : z o = 5 x 10-5 m

66 Rough : z o = 5 x 10-1 m Sea : z o = 5 x 10-3 m Snow-covered flat : z o = 5 x 10-5 m

67 Predicting power output from large wind farms: Horns Rev At hub height: Inflow velocity 8.0 ± 0.5 [m s -1 ] 10-min turbulence intensity 7% 700 kw at the velocity of 8 [m s -1 ] Constant C T for wind speed < 10 [m s -1 ] Near-neutral conditions Wind directions : 270 ± 1 o Turbine spacing = 7d About 40% power deficit North (Barthelmie et al, 2009) 1.0 wind = o Normalized Power Turbine Row

68 LES+ADM-R U [m s -1 ]

69 Power prediction using ADM-R and ADM-NR LES+ADM-R U [m s -1 ] ADM-NR cannot accurately predict the power output due to two reasons: [1] ADM-NR assumes uniform thrust force and ignores wake rotation effects [2] ADM-NR uses power and thrust coefficients that are not suitable for waked conditions 69

70 Power prediction using different turbine models LES+ADM-R U [m s -1 ] WindSim: Steady RANS flow solver with a standard κ-ε turbulence model A uniform disk model (similar to ADM-NR) WAsP: A linearized wake model 70

71 Wind direction effects A total of 91 simulations were performed for a wide range of wind direction angles

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73 Wind Tunnel Experiments

74 Wind turbine Models Miniature wind turbines Poor characterization Poor performance Thrust coefficient Power coefficient C P C T Utility-scale wind turbines ~0.45 ~0.8 Miniature wind turbines

75 Wind turbine design rotor size Growth of wind turbine size ABL depth Rotor diameter was chosen to be 15 cm.

76 Wind turbine design airfoil profile Optimum airfoil for very low chord Reynolds numbers: Small thickness (Sunada et al. 1997, 2002), 5% circular arc camber (Laitone 1997; Sunada et al. 1997, 2002; Pelletier and Mueller 2000), Sharp leading edge (Laitone 1997; Sunada et al. 1997, 2002).

77 Wind turbine design chord & twist dist. 3D printer system New designed rotor Twist and chord distribution of the rotor blade

78 Experimental setup New ABL Wind Tunnel of WIRE laboratory

79 Turbine thrust force Thrust coefficient Multi-axes force sensor Thrust coefficient for the miniature turbine

80 Turbine Power Coefficient Power coefficient Electrical servo- controller Variation of C P with tip-speed ratio for different incoming velocities

81 Wind turbine: energy conversion Electromagnetic torque Shaft torque

82 Wind Farm Velocity Statistics Experiment LES+ADM-R LES+ADM-NR Non-dimensional mean wind velocity inside a 10x3-turbine wind farm

83 Wind Farm Turbulence Statistics Experiment LES+ADM-R LES+ADM-NR Turbulence intensity distribution inside a 10x3-turbine wind farm

84 Wake Analytical Models

85 Wake Analytical Models Objective: Development and validation of a new analytical model to predict the velocity profiles downwind of a wind turbine. Contours of streamwise velocity (m/s) (Chamorro and Porté-Agel 2010) Are simple analytical models of turbine wakes still useful?

86 Motivation LES computational cost 67 simulations Each simulation: 15 hours with 128 CPUs The total CPU hour is more than Analytical model computational cost less than few seconds! Variation of Horns rev wind farm power output obtained with LES for different wind directions. From Porté-Agel et al. (2013)

87 Velocity Deficit Profiles Velocity deficit profiles have an approximately Gaussian distribution regardless of inflow conditions. U U w U U w Velocity profile z x z x Velocity-deficit profile U U w U U w z x Top-hat distribution z x Gaussian distribution

88 Top-hat vs. Gaussian velocity deficit z Top-hat distribution x Gaussian distribution z x U U w U U w z x z x Conservation of mass Jensen (1986) DU U ( ) = 1-1- C T æ ç è DU = 1 æ U æ d ö ç 0 ç ç è d w ø è d 0 d w Conservation of mass & momentum Frandsen et al. (2006) 2 C T ö ø ö ø 2 d 0 = rotor diameter d w = wake diameter k * = expansion rate Conservation of mass & momentum Self-similarity of velocity deficit Bastankhah and Porté-Agel (2014) æ DU ç C = 1-1- T U çç 8 k * x / d b è ( ) 2 æ ç -1 exp çç è 8 k * x / d b ( ) 2 ì ïæ íç è îï z - z h d 0 ö ø ö ø 2 æ + y ö ç è d 0 ø 2 ö ü ï ý þï ø

89 Analytical model testing Model turbines wakes Wind tunnel measurements Chamorro and Porté-Agel (2010) Large-eddy simulation Wu and Porté-Agel (2011) Real-scale turbines wakes Large-eddy simulation Wu and Porté-Agel (2012) Vestas V80-2MW

90 Analytical model testing: Normalized velocity deficit

91 Analytical model testing: Streamwise velocity contours New proposed model Wind-tunnel measurements (Chamorro and Porté-Agel 2010)

92 Wind Farm Control

93 Wake mitigation strategies Pitch angle control Yaw angle control

94 Yaw Angle Control Yaw angle control Optimize the wind-farm power production Power Decrease Power Increase Increase the whole wind-farm production

95 Wind turbine wakes under yawed conditions Contours of normalized mean streamwise velocity for different yaw angles. white dots: wake center trajectory

96 Yaw Angle Control U 5d β: 25 Yaw angle Normalized Power NO yaw angle Decreasing yaw angles x/d 7.1 % increase in total power production

97 Recommended Reading Hansen M (2008). Aerodynamics of Wind Turbines. Earthscan Publications Ltd., London. Mathew S (2006). Wind Energy: Fundamentals, Resource Analysis and Economics. Springer, Berlin. Hau E (2005). Wind Turbines: Fundamentals, Technologies, Application, Economics. Springer, Berlin. Manwell J, McGowan J, Rogers A (2002). Wind Energy Explained: Theory, Design and Application. Wiley, New York. Burton T, Sharpe D, Jenkins N, Bossanyi E (2001). Wind Energy Handbook. Wiley, New York.

98 Thank You!