MULTI-WTG PERFORMANCE OFFSHORE, USING A SINGLE SCANNING DOPPLER LIDAR Rémi Gandoin 1, Benny Svardal 2, Valerie Kumer 3, Raghavendra Krishna Murthy 4, Matthieu Boquet 4 1 DONG Energy Wind Power (DK) remga@dongenergy.dk 2 Christian Michelsen Research (NO) 3 University of Bergen (NO) 4 Leosphere (FR)
Scanning LiDAR in this presentation wind speed and direction measurement across an area (km x km) using a single laser (moving in space) 2
Context and high-level goals Wind field variations influence the wind farm power output. How can we better understand those effects? Previous studies using scanning LiDARs: o Wind resource assessment o Wakes o Power curve testing 1. Feasibility offshore on our sites? 2. Wind speed and direction measurement quality? 3. What scan patterns for WTG performance and wake studies? 3
Setup and project description 6m+ campaign since July 2015 on Anholt Substation Wind farm and Leosphere Windcube v2 provided by DE Leosphere Windcube 100s provided by NORCOWE Data processing by Leosphere and NORCOWE 4
Installation and alignment Vessel transfer using standard shipping container Alignment process 1. Physical alignment of Lidar vs North azimuth 2. Horizontal leveling of lidar 3. Hard target scanning for increased pointing accuracy 5
Scan patterns (1h cycles) ~30min per hour 71 deg 2 deg/s Accumulation time: 0.5s 1 2 5 4 3 ~25min per hour 45 deg 6 1 deg/s Accumulation time: 0.5s ~5min per hour 71 deg 2 deg/s Accumulation time: 0.5s 6
LiDAR data availability Availability 70 to 90% up to 2.5 km ~50 % for ranges > 2.5 km.
LiDAR effective range vs time 3500 3000 2500 max r Maximum range [m] PPI45 @ top PPI45 @ bot PPI45 @ hub RHI PPI71 PPI71 return DBS horizontal 2000 1500 1000 vertical 500 0 Oct time Nov 8
10min wind and direction at 3 locations, using Laser Cup algorithm 9
Simple WTG analysis Much shorter distance to the WTG, but slightly higher spread using the scanning LiDAR Consistent with measured correlations between met mast and scanning LiDARs 10
Multi WTG analysis Transverse winds: Reduced wind speed spread No reduced spread in power reconstruction method more uncertain 11
Multi WTG analysis North/Middle Power vs wind speed ratio: A trend is visible despite of noisy data. Every dot corresponds to a given wind direction ± 15deg wind 12
Lessons learned and way forward Device working continuously for 6m+. Radial data availability is high (>80% in average) 10min time series: about 50% rate (satisfactory, given the length of the campaign) Reconstructions for 71deg and 45deg sectors are comparable and complement each other well We will continue exploring this dataset: Wind speed and direction variations around and towards the wind farm Validation of wake models 13
Thank you for the good collaboration Valerie-Marie Kumer Benny Svardal Joachim Reuder Damien Ceus Raghavendra Krishna Murthy Matthieu Boquet 14
Additional slides 15
Context and high-level goals Increasing focus on the use of scanning LiDAR in the Wind Industry, for: o Wind resource assessment (Courtney et al. 2014) (Couts et al. 2015) (Wagner 2014) o Wakes (Kumer et al., 2015) (Wang and Barthelmie 2015) o Power curve testing (Wagner et al. 2015) Scanning LiDAR measurements could potentially help assess the variability of wind speed in the induction zone, as well as wind farm blockage (Mitraszewski et al. 2012) and support wake studies, therefore DONG Energy and NORCORWE have teamed up to address the following questions: 1. There has only been a few offshore trials, can we confirm the feasibility of such campaigns on a DONG Energy site? 2. What is the radial wind speed data quality, as well as the reconstructed wind speed quality? 3. What are the relevant scan patterns for looking into concurrent WTG performance and wake studies? 16
Setup and project description 6m+ campaign since July 2015 on Anholt Substation Wind farm and Leosphere Windcube v2 provided by DE Leosphere Windcube 100s provided by NORCOWE Data processing by Leosphere and NORCOWE 2015 2016 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 Call for proposals Agreement Design and planning Campaign Data analysis 17
Radial data analysis and QA mean values CNR Maximum in front of the first WTG row. Lower CNR for beams hitting WTGs as hard targets. Availability 70 to 90% up to 2.5 km ~50 % for ranges > 2.5 km. Radial Wind Speed Example: wakes captured in December
Simple WTG analysis The middle WTG power is plotted as a function of 10min wind speed from: the windcube v2 LiDAR 1.8km away the laser cup wind speed (windcube 100s) Note: the LC and v2 measurements are both at the same height but not at hub height (but within 10%). The laser cup wind speed gives a higher spread than the v2 LIDAR, this has been observed for the other two WTGs, and also for the 45 deg scan. The literature reports laser cup R 2 values against reference cups on met mast of ~0.97, and such values would induce a similar spread as the one observed here. 19
References (Kumer et al. 2015) Characterisation of Single Wind Turbine Wakes with Static and Scanning WINTWEX-W LiDAR Data. Valerie-M. Kumer, Joachim Reuder, Benny Svardal, Camilla Sætre, Peter Eecen, Energy Procedia, Volume 80, 2015, Pages 245-254, ISSN 1876-6102 (Wang and Barthelmie 2015) Wind turbine wake detection with a single Doppler wind lidar. H Wang and R J Barthelmie 2015 J. Phys.: Conf. Ser. 625 012017 (Courtney et al. 2014) Optimized lidar scanning patterns for reduced project uncertainty. Courtney, Michael; Wagner, Rozenn; Murthy, Raghu Krishna ; Boquet, Matthieu. 2014. Poster session presented at European Wind Energy Conference & Exhibition 2014, Barcelona, Spain. (Wagner 2014) Comparison test of WLS200S-22 (Final). / Wagner, Rozenn. DTU Wind Energy, 2014. (DTU Wind Energy LC I; No. 046(EN)). (Wagner et al. 2015) Real world offshore power curve using nacelle mounted and scanning Doppler lidars. Wagner, Rozenn; Vignaroli, Andrea ; Courtney, Michael ; McKeown, Stephen ; Cussons, Robert ; Murthy, Raghu Krishna ; Boquet, Matthieu. 2015. European Wind Energy Association (EWEA).EWEA Offshore 2015 Conference, Copenhagen, Denmark, 10/03/2015. (Couts et al. 2015) Cost effective offshore wind measurement Couts et al., EWEA Resource Assessment 2015, Helsinki, Finland, 2-3 June 2015 (Mitraszewski et al. 2012) Wall effects in offshore wind farms Mitraszewski et al, TORQUE 2012 20