Carbon Trust Offshore Wind Accelerator. OWA floating LiDAR campaign: Babcock trial at Gwynt Y Môr Copenhagen, 11 March 2015 Megan Smith

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Carbon Trust Offshore Wind Accelerator OWA floating LiDAR campaign: Babcock trial at Gwynt Y Môr Copenhagen, 11 March 2015 Megan Smith 1

Trial Overview Using RWE s Gwynt y Mor mast in the Irish Sea MeasNet-calibrated cup anemometers at 90m and 50m above LAT, wind vane at 70m Fixed LiDAR (ZephIR 300) on met mast platform Waverider buoy Reasonably benign wave climate but large tidal range (8m) Validation mapped against OWA Floating LiDAR Roadmap 1. Three assessment criteria: Availability Accuracy Sensitivity to metocean conditions 1 http://www.carbontrust.com/resources/reports/technology/owa-roadmap-for-commercial-acceptance-of-floating-lidar-technologies 2

FORECAST Device Overview Platform 3.2m x 3.2m platform housing all systems Wind turbines mounted on outriggers Main lifting points for whole buoy Access from ladder below Handrails all around Low Motion Buoy Inherently stable, shallow draft spar buoy Low pitch, roll and heave Modular design Three-point mooring design Three main sections Main Tube 812mm OD Pipe Buoyancy Tank 3800mm Ø tank with internal stiffeners Ballast Tank 2600mm Ø tank filled with high density concrete 3

Wind Speed Accuracy Reference: Cup anemometer Height above LAT Regression Slope Regression r 2 90m 0.993 0.987 50m 0.997 0.987 Roadmap best practice 0.98 1.02 >0.98 Height above LAT Reference: Fixed LiDAR Regression Slope 50m 0.998 0.900 90m 0.997 0.976 Regression r 2 LAT = Lowest astronomical tide Correlation between wind speed measurements from the floating LIDAR and the cup anemometer at 90m above LAT 4

Wind Direction Accuracy Reference: Wind Vane Height above LAT Regression Slope Regression r 2 30m 0.989 0.972 Roadmap best practice 0.97 1.03 > 0.97 Scatter at +/- 108deg due to the flow reversal at the ZephIR met station Additional scatter thought to be due to magnetic interference with the compass. Babcock are now working on using a GPS compass to improve the accuracy Correlation between wind direction measurements from the floating LIDAR and the wind vane at 30m above LAT Note: data at 70m height is not presented due to a suspected offset in the 70m wind vane 5

Turbulence Accuracy Comparison Floating LIDAR vs Cup Anemometer Fixed LIDAR vs Cup Anemometer Regression at 90m Slope r 2 1.106 0.520 1.158 0.455 Comparison between fixed and floating LiDAR data sets shows that the floating LiDAR (right) gives no worse correlation to the cup anemometer than the fixed LiDAR (below) Correlation between turbulence intensity measurements from the floating LIDAR and the cup anemometer at 90m above LAT Correlation between turbulence intensity measurements from the fixed LIDAR and the cup anemometer at 90m above LAT 6

Gust Accuracy Gust speeds are captured well Reference: Cup Anemometer Height above LAT Regression Slope Regression r 2 90m 0.988 0.978 50m 0.998 0.978 Correlation between maximum gust speed measurements from the floating LIDAR and the cup anemometer at 90m above LAT 7

Sensitivity of Wind Speed Accuracy to Metocean Conditions Overall the device showed good performance to the various metocean conditions experienced during the trial Sensitivity to error in wind speed to significant wave height No sensitivity to wave height, wave steepness, or wave period are evident Sensitivity to error in wind speed to wave steepness Sensitivity to error in wind speed to peak wave period 8

Sensitivity of Wind Speed and Direction Accuracy to Metocean Conditions Negligible sensitivity to tide height Some sensitivity in wind direction to buoy orientation, addition of a DGPS compass for future deployments should remedy this error Sensitivity to error in wind speed to tide height Sensitivity to error in wind direction to buoy bearing 9

Availability Overall system availability for the 6 month trial was 99.86% Roadmap criteria: >95% Every month of the trial had (post-processed) data availability of over 95% Roadmap criteria: >90% Processing of data consists of removal of 9999 and NAN values only As the graph shows, consistent and good data availability for all measurement heights Summary of overall availability for the trial by height above LAT 10

How does this trial fit in with the OWA programme? OWA: customer-driven offshore wind R&D FLiDAR OWA Roadmap Completed projects Babcock Upcoming trials EOLOS Axys TBC TBC 11

Conclusions Availability is very good 99.86% Overall System Availability, with monthly availabilities all over 95% Wind speed accuracy is very good 0.993 slope 0.991 r 2 Wind direction accuracy is good 0.984 slope 0.976 r 2 Gust prediction is good 0.988 slope 0.978 r 2 Turbulence intensity prediction is no worse than fixed LiDAR measurements Wind speed measurements are largely insensitive to metocean conditions over the range experiences (Hs = 3m) 12

Assessment against the Roadmap The Babcock device has reached Stage 2, as validated by Frazer-Nash and DNV GL. Babcock intend to implement modifications to the compass as recommended by DNV GL and will validate the updated system In summary: Results of the GyM trial are extremely encouraging Causes of wind direction offset have been identified and resolved Technology is definitely on the right track 13

Questions? Megan.Smith@carbontrust.com 14

KPIs / Acceptance Criteria Data Quality KPI Xmws Definition / Rationale Mean Wind Speed Slope single variant regression with the regression constrained through origin. Acceptance Criteria Best Practice Minimum 0.98 1.02 0.97 1.03 R2mws Mean Wind Speed Coefficient of Determination >0.98 >0.97 Mmwd Mean Wind Direction Slope two-variant regression 0.97 1.03 0.95 1.05 OFFmwd Mean Wind Direction Offset < 5 < 10 R2mwd Mean Wind Direction Coefficient of Determination > 0.97 > 0.95 15

KPIs / Acceptance Criteria Availability KPI MSA 1M OSA CA Definition / Rationale Monthly System Availability 1 Month Average, for every month Overall System Availability Campaign Average Acceptance Criteria across total of six (6) months data 90% 95% 95% MPDA 1M Monthly Post-processed Data Availability 1 Month Average for every month 80% OPDA CA Overall Post-processed Data Availability 85% In the above table, during periods of maintenance; the system is deemed unavailable. 16

OWA Floating LiDAR programme objectives Define criteria required of a floating LiDAR system to achieve various stages commercial acceptance Stage at which measurement data recorded using a particular floating LIDAR technology is accepted by funders of commercial scale offshore wind projects Support trials to validate floating LiDAR technology Gwynt Y Môr Irish Sea site Narec / Neart na Gaoithe East Anglia IJmuiden Formulate and promote best practice by sharing lessons learned OWA Floating LiDAR Workshop OWA Roadmap IEA Annex 32 17

Babcock datasets The data sets shown are from 6 months of continuous operation from May to November 2014 This data includes ~2 months of data which has been corrected for a 37 direction offset identified early in the deployment This offset was caused by magnetic interference with the compass. The correction was performed in-situ DGPS compass will be used on future projects Babcock have now developed a compass commissioning procedure to address the direction offset, which have been reviewed and supported by DNV-GL for future trials 18

Roadmap describes KPIs required of a successful trial Key areas for assessment are accuracy and availability and sensitivity to metocean conditions KPIs are defined for each areas as well as acceptance criteria, when relevant, for example Monthly system availability 90% Wind Speed R 2 97% (minimum) 98% (best practice) Data coverage requirements and guidance on the analysis needed are also provided in the Roadmap document 19

Roadmap Assessment Criteria 3 key areas for assessment Accuracy Wind speed and direction Turbulence intensity & gust speeds Sensitivity to metocean conditions Wave height, period, steepness Tide height Availability Applied to ten-minute-averaged data 20

Examples of commercial uses of floating LiDAR at various stages Increasing # trials Maturity Level 3: Commercial Scenario F 1 floating LiDAR(s) deployed Scenario G Fixed met mast supplemented by 1 floating LiDARs Maturity Level 2: Precommercial Scenario C 1 floating LiDAR(s) deployed Scenario D Fixed met mast supplemented by 1 floating LiDARs Maturity Level 1: Baseline Scenario A Fixed met mast supplemented by 1 floating LiDARs Increased bankability 21