Investigating the Efficacy of Floating LIDAR Motion CompensationAlgorithms for Offshore Wind Resource Assessment ApplicationsEuropean Wind Energy Conference, 14 March 2011

Daniel W. JaynesGL Garrad Hassan

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1. Introduction

4. Results

5. Conclusion

6. Future work and implications for the industry

2. Technology overview

3. Offshore LIDAR comparison campaign

Introduction

Challenges for offshore wind resource assessment:• Lack of existing sources of data for prospecting purposes• On-site data needed for projects requiring external finance• Fixed met masts pose a significant capital and logistical commitment for project

developers

LIDAR remote sensing devices have made significant advancements in the on-shore domain

• Demonstrated accuracy in simple terrain conditions [1], [2], [3]• Improved autonomous operational up-time since early deployments

In the offshore domain, LIDAR has been successfully deployed on fixed platforms [4]• Terrain no longer a threat, but waves, environment and lack of redundancy are concerns

What role will LIDAR remote sensing play in offshore wind resource measurement?

Technology Overview

LIDAR’s New Frontier: floating buoys equipped with LIDAR technology

Active players:• Natural Power – SeaZephIR• Leosphere – (planned)• Catch the Wind/AXYS – WindSentinel

• Catch The Wind Vindicator LIDAR• AXYS Technologies buoy platform

Motion compensation for dynamic motion of the offshore environment:• Vindicator: Roll, Pitch and Yaw compensation• Buoy: Heave and Translation compensation• Compensation for movement in 6 degrees of freedom

Device under consideration

X

Y

Z

Translation

Heave

Technology Overview: Motion Compensation Algorithms

• Each sensor and data acquisition device records independently• Sensors are synchronized with multiple on-board GPS systems• LIDAR logs data at a frequency of 1 Hz, buoy wave data are logged at 4 Hz

“TRIAXYS” Wave motion and ocean depth sensor

LIDAR: Wind data corrected for tilt & rotational motion

Buoy motion measurements

Data recovery

“WM 500” Buoy data controller

LIDAR measurements

Data for analysisPost-process

Data

Offshore LIDAR Comparison Campaign

Test Location:• Juan de Fuca Strait between the

Olympic Peninsula and Vancouver Island in October, 2009.

• Land LIDAR located 688 meters away from Buoy LIDAR

Reference data: Land-based VindicatorExperimental data: Buoy VindicatorMeasurement Period: 1 month

Measured Variables: • Wind speed/Direction: 100, 150 and 200 m• Wave height, direction• Air and water temperature• Barometric Pressure

Results

• Data filtering criteria: minimum “valid data count” > 300 for each 10-min period• Wind Speed Correlations demonstrate consistent results at all heights

Measurement Height [m]

Buoy Mean Wind Speed [m/s]

Land Mean Wind Speed [m/s]

Percent Difference Slope Offset R2

100 6.48 6.52 -0.60% 0.966 0.093 0.99150 6.57 6.66 -1.33% 0.967 0.161 0.99200 6.68 6.70 -0.34% 0.967 0.162 0.99

Results, ContinuedData Recovery:• Excellent operational uptime during the 1-month test campaign• Net data recovery:

Direction Correlation:

Reference (Land) LIDAR:

Experimental (Buoy) LIDAR:

Measurement Height [m]

Valid Data Records - Land LIDAR [ ]

Total Possible Records - Land LIDAR [ ]

Net Valid Data - Land LIDAR [%]

100 3782 4752 79.6%150 4031 4752 84.8%200 3870 4752 81.4%

Measurement Height [m]

Valid Data Records - Buoy LIDAR [ ]

Total Possible Records - Buoy LIDAR [ ]

Net Valid Data - Buoy LIDAR [%]

100 3207 4752 67.5%150 4160 4752 87.5%200 3589 4752 75.5%

Results, Continued

Error Investigation:• Error as a function of wind speed gradient:

• Wind speed gradient correlates poorly with measurement error• Wind speed gradient was generally low, as expected in offshore wind regimes

Results, Continued

Error Investigation:• Measurement error as a function of wave height

• Relatively low measurement error relative to land-based LIDAR during higher wave height events

• Maximum wave height: approx. 2 m• Average wave height: approx. 0.5 m

Color B

ar: Wind speed [m

/s]

Color B

ar: Wind speed [m

/s]

Color B

ar: Wind speed [m

/s]

Results, ContinuedMeasurement error as a function of “valid data count”• “Valid data count” is a proxy for signal return quality

Color Bar: W

ind speed [m/s]

• Data with valid data count less than 300 have been removed

Results, Concluded

Measurement error distribution:

Mean: -1.4%

Stdev: 8.3%Mean: -0.6%

Stdev: 12.3%

Mean: -0.7%

Stdev: 15.3%

• Scatter increases as a function of range, but mean agrees well with reference measurements.

ConclusionMeasurement campaign:

• Measurement error showed little relationship with a variety of different atmospheric and environmental phenomena, including wave height.

• Experimental (buoy LIDAR) mean wind speed agreed within 2% of the reference (land LIDAR) measurements.

• Given a 688 m separation of sensors, some degree of natural wind flow variation is to be expected.

• Results show promise, but the repeatability of demonstrated findings must be explored for longer periods of time.

Floating LIDAR: Implications for the Offshore Wind Energy Industry

• Floating LIDAR is considered relatively new and has not yet completed conclusive validation testing.

• GL GH have defined broad validation protocol for floating LIDAR devices.• The Current best practice approach is to measure the wind resource near the proposed

turbine hub-height with traditional, in-situ equipment (e.g. cup anemometers).

Conclusion

• Current outlook: A new, site-specific resource measurement option is now commercially available for preliminary assessment applications.

• Future outlook: If results can be shown to agree closely and consistently with accepted reference equipment, then the floating LIDAR system may be used for more formal applications in the future.

• Remote Sensing Limitations to remember:• Turbulence – Temporal and spatial averaging effects of LIDAR measurements• Power supply and redundancy – Risk of data loss exists, but onboard power system

redundancies may help mitigate this risk (further testing to demonstrate potential)• Extreme wind speeds – Volume versus point measurement dichotomies

Comparisons against fixed met mast measurements are planned for the near future with commercial partners.

Thank you

Daniel JaynesGL Garrad HassanDan.jaynes@gl-garradhassan.com+1 (503) 222 5590 Ext. 109

References[1] Jaynes, D., LIDAR Validation and Recommendations for Wind Resource Assessments. AWEA WINDPOWER, May 2009.[2] Albers, A., Evaluation of ZephIR. 2006, Deutsche WindGuard Consulting GmbH.[3] Jorgensen, H., T. Mikkelsen, J. Mann, D. Bryce, A. Coffey, M. Harris, and D.A. Smith. Site Wind Field Determination Using a CW Doppler Lidar-

Comparison with Cup Anemometers at Riso. in The Science of Making Torque from Wind. 2004. Delft.[4] Kindler, D., Oldroyd, A., MacAskill, A., Finch, D., An 8 Month Test Campaign of the QinetiQ ZephIR System: Preliminary Results,

Meteorologische Zeitschrift, October 2007.