Comparison study between wind

turbine and power kite wakes

Thomas Haas

Ph.D. candidate and AWESCO fellow

Supervision: Prof. Dr. Ir. Johan Meyers

Wake Conference 2017

May 30th – June 1st, 2017, Visby

Airborne Wind Energy Principle

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• Emerging wind energy technology

• Power harvesting tethered airborne devices

• High-altitude operation

• On-board and ground-based generation

[Airborne Wind Energy, Springer]

Airborne Wind Energy Generation modes

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Ground-based generation

• Fast flying tethered wing

• High tension unrolls tether from drum

• Drum drives electric generator on ground

• Cyclic power generation (reel in/out phases)

On-board generation

• Tethered plane with on-board turbines

• High relative airspeed of crosswind

• Tether conducts electricity

• Vertical take-off and landing

→ “Pumping mode”

→ “Drag mode”

Airborne Wind Energy Technology

Advantages

• Stronger and more consistent winds

• Require less material as wind turbines

• Eased ground-based maintenance

• Rapid and flexible deployment

Challenges

• Operation in variable wind conditions

• Autonomous launch and landing

• No prevalent design or concept

• Large scale commercial operation

Implementation

• Several companies in the field

• Prototypes of 50kW and 600kW

• Upscaling to multiple MW in future

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[https://x.company/makani]

Research question:

How do kite systems interact

with their wind environment?

Outline

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1. Introduction

2. Motivation

3. Methodology

4. Results

5. Outlook

Motivation Background

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Objective

• Difference between wind turbine-like wake and power kite wake

• Investigate the influence of torque on the wake development

Turbine mode

- Inspired from wind turbine operation

- Torque virtually captured by the generator

- Net addition of torque onto the flow

Drag mode

- Additional forces for on-board turbines

- Aero. torque balances turbine torque

- Total torque added to flow is zero

Outline

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1. Introduction

2. Motivation

3. Methodology

4. Results

5. Outlook

Methodology CFD code

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Large Eddy Simulation

• Filtered incompressible Navier-Stokes equations

• Subgrid scale modelling using Smagorinsky model

Inhouse code from KULeuven

• Pseudo-spectral flow solver SPWind [1,2]

• Fringe region technique to circumvent BC periodicity

• Synthetic turbulence generation using Mann model (tugen library)

Actuator Line Technique

• No implicit force computation from airfoil characteristics

• Optimal force distribution based on Betz-Joukowski limit

• Smearing out of local forces onto LES grid using Gaussian filter

[1] Calaf et al. 2010, [2] Munters, Meneveau and Meyers 2016

Methodology Force distribution

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Optimality condition from Betz-Joukowski limit

• Aerodynamic drag is neglected

• Optimal induction factors: 𝑎 = 1 3 and 𝑎′ = 𝑎(1 − 𝑎) 𝜆2𝜇2

• Derive flow angle and lift distribution

𝐿 = 𝜌4𝜋𝑅

𝑈∞2

𝐵𝜆𝑎(1 − 𝑎) (1 − 𝑎)2+(𝜆𝜇(1 − 𝑎′))2 tan(𝜙) =

1 − 𝑎

𝜆𝜇(1 − 𝑎′)

Methodology Force distribution

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Optimality condition from Betz-Joukowski limit

• Aerodynamic drag is neglected

• Optimal induction factors: 𝑎 = 1 3 and 𝑎′ = 𝑎(1 − 𝑎) 𝜆2𝜇2

• Derive flow angle and lift distribution

Additional turbine forces D

• 2 turbines (33% and 66% of span)

• Additional force in tangential direction

• Distributed over 10% of the actuator line segments

• Total torque on flow is zero

𝑟 × 𝐿 sin 𝜙 𝑑𝑟 +

𝑟𝑜

𝑟𝑖

𝑟 × 𝐷 𝑑𝑟 =

𝑟𝑜

𝑟𝑖

0

Methodology Simulation setup

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Grid resolution 𝑁𝑥 × 𝑁𝑦 × 𝑁𝑧 = 640 × 160 × 320 ~ 30 ∙ 106 grid points

Kite span 𝑏 = 0.43𝑅

Cell size ∆𝑥 × ∆𝑦 × ∆𝑧≈ 0.1𝑏 × 0.1𝑏 × 0.05𝑏

Operation conditions 𝜆 = 7, 𝑈∞ = 10𝑚/𝑠

Inflow turbulence Turbulence over sea 𝐿𝑇 , 𝛼𝜖2/3, Γ = [60𝑚, 0.022𝑚

4

3𝑠−2, 2.85]

Parallel computation 320 CPUs

Outline

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1. Introduction

2. Motivation

3. Methodology

4. Results

5. Outlook

Results Wake spreading in uniform inflow

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Contours of time-averaged axial induction 𝒂 = 𝟏 − 𝒖𝒙 𝑼∞

• 3 locations x/R = 0, 3, 6

• Inward and outward wake spreading

• “Jet effect” inside annulus core region

• No difference between turbine and drag mode

a = -0,05

a = 0

a = +0,2

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Results Flow structure in uniform inflow

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Contours of instantaneous axial induction at annulus plane 𝒂 = 𝟏 −𝒖𝒙

𝑼∞

a = -0.05

a = 0

a = +0.2

Tip vortices

Results Flow structure in uniform inflow

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Contours of instantaneous tangential induction at annulus plane 𝒂′ =−𝒖𝒕

𝜴𝒓

a’ = -0.12

a’ = -0.06

a’ = -0.02

a’ ~ 0

Additional structures

Results Instantaneous fields of vorticity magnitude in uniform inflow

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Pair of counter-

rotating tip vortices

Pair of tip vortices

+ turbine vortices

Turbine mode

Drag mode

New research questions:

• Formation mechanism

• Setup dependency

Results Vortex interaction in drag mode

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• Slower downstream advection of turbine vortices

Results Vortex interaction in drag mode

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• Slower downstream advection of turbine vortices

• Outward advection

Results Vortex interaction in drag mode

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• Slower downstream advection of turbine vortices

• Outward advection

• Rapid vortex breakdown

Results Instantaneous fields of vorticity magnitude in turbulent inflow

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Turbine mode

Drag mode

• Same behavior at

annulus plane

• Additional interaction

with ambient turbulence

• Rapid loss of coherence

Results Far wake development: velocity deficit

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• Faster wake recovery with turbulent inflow 𝑥 𝑅

Outline

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1. Introduction

2. Motivation

3. Methodology

4. Results

5. Outlook

Conclusions and future work

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Investigation of wake characteristics in context of airborne wind energy

• Two different operation modes: turbine-like and torque-free operation

• Two different inflow conditions: uniform and turbulent inflow

Principal outcome

• Wake spreading in both inward and outward direction

• Shedding from additional vortices at location of on-board turbines

• No substantial influence on wake development

• Faster wake recovery with turbulent inflow

Future work

• Further investigation of formation mechanism of turbine vortices

• Computation with aerodynamic model based on 2D airfoil data

• Simulation in atmospheric boundary layer

Acknowledgments

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Support from European Commission through Horizon2020 programme AWESCO

International Training Network - Grant No.642682

Computational resources provided by Flemish Supercomputer Center

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Thank you