ATLAS Principle to Product - PDF Free Download

ATLAS Principle to Product SUPERGEN 26th May 2016 Wind and tidal energy control experts

SgurrControl Experts in wind and tidal energy control Engineering organisation providing control solutions to wind and tidal turbines to: Optimise energy capture Reduce damage on wind turbines Minimise O&M costs Founded in 2008, joined SgurrEnergy in 2013

Principle to Product 07 08 09 10 11 12 13 14 15 16 TRL Strathclyde University Supergen Wind Supergen Phase One WP Y.3.2 1 2 3 Strathclyde/ SgurrControl Industry sponsored Research/PhD 3 4 SgurrControl/ DECC IBC Individual Blade Control DECC Project 5 7 ATLAS Advanced Turbine Load Alleviation System

Idea Development Implementation Demonstration

Control Overview Supervisory Control Oversees total operation of wind turbine including Start up/shutdown Safety of turbine operation Fault handling Data collection Operational Control Continuously adjusts dynamic state of wind turbine Pitch, generator reaction torque and yaw

Operational Control Alters the pitch and generator torque demand to control the speed of the rotor Control is used to limit the power output above rated power and optimise power extraction below rated power Control is increasingly used to manage loads on the turbine Drivetrain load alleviation Tower load alleviation Blade loads and rotor imbalance

Importance of Control on Load Alleviation Increase in turbine size Square cube law between energy capture and material requirements Size of wind field incident on the rotor Abnormal wind conditions Low level jets Sites with high shear, veer and turbulence

Underlying Cause of Loads Turbulence Non uniform wind fields damaging the turbine Particularly at the harmonics of the rotational frequency of the rotor Wind shear Yaw misalignment Low Level Jets strong shear veer Coherent eddy Tower shadow

The Solution Wind field Collective Pitch Control Individual Blade Control Load imbalance reduced

SUPERGEN Funding Individual Blade Control for Fatigue Load Reduction of Large scaled Wind Turbines: Theory and Modelling (2010), Victoria Neilson

Turbine Control Structure reference inputs central controller collective pitch demand d blade controller blade controller blade moments M 1 1 M 2 2 wind turbine dynamics rotor speed blade controller M 3 3 individual pitch demands

Blade Control Design set point collective pitch demand d blade controller 3 individual wind turbine dynamics M 3 pitch demand blade moment 160 Transfer function of pitch to moment Magnitude [db] 150 140 130 Effect of tower motion on the blade 120 10-1 10 0 10 1

Blade Control Design set point collective pitch demand d blade controller 3 individual blade dynamics M 3 pitch demand blade moment 160 Transfer function of pitch to moment Magnitude [db] 150 140 130 120 10-1 10 0 10 1

Fictitious Forces A fictitious force is an apparent force that acts on all masses whose motion is described using a non inertial frame of reference, such as a rotating reference frame. fictitious forces tower motion hub rotational accelerations

Simplifying the Dynamics wind turbine dynamics fictitious forces blade dynamics

Simplifying the Dynamics pitch demand wind turbine dynamics measured moment modified moment measured accelerations fictitious forces estimator external moment pitch demand blade dynamics in inertial frame bending moment

IBC Structure accelerations modified moment fictitious forces estimator measured moment set point collective pitch demand d blade controller 3 individual pitch demand wind turbine dynamics M 3

IBC Structure accelerations modified moment fictitious forces estimator measured moment set point collective pitch demand d blade controller 3 individual pitch demand wind turbine dynamics M 3 IBC

Turbine Control Structure collective pitch demand blade moments M 1 reference inputs central controller d IBC IBC 1 M 2 2 wind turbine dynamics rotor speed M 3 IBC 3 individual pitch demands

Advantages of IBC Decoupled from turbine dynamics Decentralised control Transparent and straight forward to use No loss of information Has the flexibility to target critical loads Optimise trade off between load reduction and pitch activity Target specific loadings at positions along the blades Simple structure to implement

The Product ATLAS Problem Non uniform wind Imbalanced rotor loads Damaging to turbine Market Increased rotor diameter Rapid deployment of wind Solution IBC Control structure Tuneable Flexible ATLAS

Idea Development Implementation Demonstration

ATLAS Individual Blade Control Loads are the forces being applied onto the wind turbine component Fatigue load the aggregate effect that the forces would have on the structure over the whole lifetime Extreme load the abnormal and rare single event occurred at high level of force that the structure is generally designed to withstand

ATLAS Reducing Fatigue Load Fatigue loads: For the blades, the target component is out of plane bending moments For the drive train, the target components are hub tilt and yaw moments The main contribution is around the rated wind speed region where the wind turbine operates for most of the time Assessed by lifetime (20 years) equivalent damage loads calculated through rain flow counting

ATLAS Reducing Fatigue Load Reduction (~25%) on the blade lifetime fatigue damage Blade lifetime fatigue load [Nm] 9 x 106 8 7 6 5 4 3 2 1 CC IBC 0 4 6 8 10 12 14 16 18 20 22 24 25 Wind speed [m/s]

ATLAS Reducing Fatigue Load Reduction (~20%) on the hub lifetime fatigue damage Hub lifetime fatigue load (tilt) [Nm] 4.5 x 106 4 3.5 3 2.5 2 1.5 1 0.5 CC IBC 0 4 6 8 10 12 14 16 18 20 22 24 25 Wind speed [m/s]

ATLAS Reducing Blade Extreme Load Blade extreme loads: Contributions from both blade in plane (Mx) and out of plane (My) bending moments at various blade sections Critical scenarios can occur at both low and high wind speeds Assessed by projection of Mx and My onto specific directions in the (My,Mx) plane at the instance when the maximum load arises

ATLAS Reducing Blade Extreme Load Reduction of extreme loads 5 x 106 4 Ultimate load in My-Mx plane in low wind speed L1 3 2 Mx [Nm] 1 0-1 -2 Blade station: 14 m -3-2 0 2 4 6 8 10 12 My [Nm] x 10 6 Critical load L1 at low wind speed Critical load L2 at high wind speed

ATLAS Reducing the Load ATLAS Fatigue ATLAS Extreme ATLAS Combined Controller Designs ATLAS Fatigue ATLAS Extreme ATLAS Combined Blade fatigue load 27% 0 27% Hub fatigue load 20% 0 20% Tower fatigue load Blade extreme load 4% 0 3% L1 L2 L1 L2 L1 L2 0 14% 33% 24% 33% 24%

400 300 200 100 ATLAS Application for Low Level Jets Low Level Jet event phenomenon observed shows the wind speed rising dramatically with the height Wind turbines have been experiencing higher loads and higher component failure rates 0 0 200 400 600 800 1000 1200 Distance [m]

ATLAS Application for Low Level Jets 7 x 106 6 Normal wind condition without IBC LLJ without IBC LLJ with IBC Blade Fatigue Load [Nm] 5 4 3 2 1 0 3 5 7 9 11 13 15 17 19 21 23 25 Wind speed [m/s] Not only are the blade loads reduced, but also the loads on the hub and the shaft are reduced

ATLAS Pitch Trade off Investigation on pitch duty against load reduction -4 Lifetime fatigue load reduction [%] -5-6 -7-8 -9-10 -11-12 -13 Hub Blade -14 0 50 100 150 200 250 300 350 Lifetime increase of pitch duty [%]

Idea Development Implementation Demonstration

ATLAS Field Demonstration Field demonstration funded by the Department of Energy and Climate Change (DECC) Partner with Romax as an independent third party for analysis Field test and assessment on a Clipper C96 2.5MW wind turbine owned by University of Minnesota

ATLAS Field Demonstration Key aims: Demonstration of the effectiveness of ATLAS in reducing the loads on a real turbine Validation of the model and analysis and validation of the design process on a real turbine

Implementation Process Original turbine layout ATLAS layout

Implementation Process Location of strain gauges and hub accelerometer Main controller (TCU) Blade root strain gauges Pitch Control Unit (PCU) x3 Hub accelerometer

Implementation Process Hardware configuration Requirements for the extra measurements bending moments and hub accelerations

Implementation Process Three triaxial accelerometers to calculate angular rates

Implementation Process Installing the three triaxial accelerometers

Implementation Process Identifying the environmental constrains IP rating, temperature range, vibrations, etc.

Implementation Process Turbine Control Unit (TCU) requirements Identifying the communication protocols Feedback required from Pitch Control Unit (PCU) according to the command issued in the same cycle The process of issuing commands and receiving an appropriate feed back should not take longer than 50ms

Implementation Process Testing before deployment: Hardware in the loop (HiL) Implementing extra alarms Testing the communications with the spare parts available

Implementation Process Deployment stages ATLAS hardware mounted in the hub, tested to make sure it runs without any errors before connecting to TCU and PCU

Implementation Process Deployment stages ATLAS hardware connected to TCU and PCU and run as a bypass Human Machine Interface (HMI) changed to provide the capability to enable/disable ATLAS ATLAS enabled, controlling each blade individually

Idea Development Implementation Demonstration

Demonstration Main Objectives: Test the effectiveness of ATLAS Reduce blade loads Does not interfere with speed controller Same energy capture Does it work? Validate the model results Same blade load reduction Same pitch activity Does it work as supposed to? Predict the lifetime benefits of ATLAS on a wind turbine

Demonstration Commissioning What do I need to test ATLAS? Reduced gain controller & running under safe conditions 1.8 1.7 1.6 Pitch angle [deg] 1.5 1.4 1.3 1.2 1.1 136 138 140 142 144 146 Time [s]

Experimental Campaign Smooth switching Compare collective/ ATLAS Similar conditions 11 minutes on/off Pitch angle [deg] 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 12 11 10 3 2.5 2 6400 6402 6404 6406 6408 6410 Time [s] Wind speed [m/s] 9 8 7 Pitch angle [deg] 1.5 1 0.5 0 6-0.5-1 5 6000 7000 8000 9000 10000 11000 12000 13000 Time [s] Wind Speed -1.5 6000 7000 8000 9000 10000 11000 12000 13000 Time [s] Pitch Angles

Experimental Campaign Results Blade loads reduction (out plane bending moment) Collective pitch ATLAS x 10 7 5 PSD (knm 2 /rad) 2 Cumulative PSD (knm 2 ) 0 10-2 10-1 10 0 10 1 Frequency (rad/s)

Experimental Campaign Results Blade loads reduction (out plane bending moment) 7000 6000 Collective IBC 5000 DEL [knm] 4000 3000 2000 1000 7.5 8 8.5 9 9.5 10 10.5 11 11.5 Wind speed [m/s]

Experimental Campaign Results ATLAS does not interfere with the speed/power control 1700 1600 1500 1400 Collective IBC Power [kw] 1300 1200 1100 1000 900 800 8.5 9 9.5 10 10.5 11 11.5 12 12.5 13 13.5 14 Wind speed [m/s] Power curve

Experimental Campaign Results ATLAS does not interfere with the speed/power control 10 6 10 4 Collective pitch ATLAS PSD [rpm/rad] 10 2 10 0 10-2 10-4 10-2 10-1 10 0 10 1 10 2 Frequency [rad/s] Generator speed spectrum

Model Validation Wind conditions: Wind speed Turbulence intensity Wind shear Air density Loads, generator speed, pitch angle Signals recoded Pitch angle 1/2/3 Flapwise loads 1/2/3 Edgewise loads 1/2/3 Pitch motor torques 1/2/3 Generator speed Generated power MET mast anemometers/wind vanes x6

Model Validation Flapwise blade root load PSD [knm/rad] 10 14 10 12 10 10 10 8 10 6 Collective Real Simulated 10 4 10-2 10-1 10 0 10 1 10 2 Frequency [rad/s] 10 13 10 12 Real Simulated 10 11 Blade loads reduction ~10 % PSD [knm/rad] 10 10 10 9 10 8 10 7 ATLAS 10 6 10 5 10-2 10-1 10 0 10 1 10 2 Frequency [rad/s]

Model Validation Pitch angle real vs simulated 10 4 10 2 Real Simulated 10 4 10 2 Real Simulated 10 0 10 0 PSD [deg/rad] 10-2 10-4 PSD [deg/rad] 10-2 10-4 10-6 10-6 10-8 10-2 10-1 10 0 10 1 10 2 Frequency [rad/s] 10-8 10-2 10-1 10 0 10 1 10 2 Frequency [rad/s] Collective ATLAS

Model validation Generator speed 10 5 Real Simulated 10 8 10 6 Real Simulated 10 4 PSD [rpm/rad] 10 0 PSD [rpm/rad] 10 2 10 0 10-2 10-4 10-5 10-2 10-1 10 0 10 1 10 2 Frequency [rad/s] Collective 10-6 10-2 10-1 10 0 10 1 10 2 Frequency [rad/s] ATLAS

Independent 3 rd Party Analysis Romax assessed lifetime of key components RomaxWIND Detailed models of gearbox and bearings Standard and bespoke calculation methods RomaxWIND models

ATLAS Main Benefits Blade fatigue loads reduction (10 25 %) Alleviate gearbox loads Less risk of main bearing failures CAPEX and OPEX reduction Minimum pitch activity > does not impact the pitch bearing life

End of the Story? Idea Development Implementation Demonstration

Next Steps Idea Development Implementation Demonstration Commercialisation

Commercialisation Moving to TRL Levels 8 9 Commercialisation and market ready Using experience from field demonstration to finalise product design, packaging, marketing Rollout to multiple sites and different wind turbine types Future development of product improvements to increase capability and performance

Target Markets Wind turbine manufacturers Cost reduction of original design Increased energy capture with longer blades Essential for large wind turbines Life extension Wind farm owners and operators High wind shear, veer, turbulence Low level jets High failure rates of components Life extension