Downloaded from orbit.dtu.dk on: Dec 16, 2018 Reducing Uncertainty of Near-shore wind resource Estimates (RUNE) using wind lidars and mesoscale models Floors, Rogier Ralph; Vasiljevic, Nikola; Lea, Guillaume; Pena Diaz, Alfredo Publication date: 2015 Document Version Peer reviewed version Link back to DTU Orbit Citation (APA): Floors, R. R. (Author), Vasiljevic, N. (Author), Lea, G. (Author), & Pena Diaz, A. (Author). (2015). Reducing Uncertainty of Near-shore wind resource Estimates (RUNE) using wind lidars and mesoscale models. Sound/Visual production (digital) General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Reducing Uncertainty of Near-shore wind resource Estimates (RUNE) using wind lidars and mesoscale models EMS 2015, Sofia, Bulgaria, Coastal meteorology session Rogier Floors, Nikola Vasiljević, Guillaume Lea, Alfredo Peña
Motivation Many offshore windfarms planned in near-coastal waters due to high winds and good grid connectivity Big uncertainty in coastal wind climate due to change in roughness and stability conditions Wind lidars and mesoscale models became reliable tools to study wind development Are mesoscale able to capture flow with sufficient accuracy in coastal areas? 2 DTU Wind Energy, Technical University of Denmark 19 October 2015
Options for measurements in coastal areas Land Sea Area of future wind farm Lidar Floating lidar Met mast Met mast Technique Pros Cons Mesoscale models Cheap Uncertainty of prediction up to 10% 3 DTU Wind Energy, Technical Mesoscale University models + of Denmark local measurements Uncertainty reduced to 3%
Which measurement solution is most cost-effective (cost vs. accuracy)? Land Sea Area of future wind farm Lidar Floating lidar Met mast Met mast Technique Pros Cons Mesoscale models Cheap Uncertainty of prediction up to 10% 4 DTU Wind Energy, Technical Mesoscale University models + of Denmark local measurements Uncertainty reduced to 3% $$$?
First attempt to answer the question: One or two lidars? Land Sea Area of future wind farm Met mast 5 DTU Wind Energy, Technical University of Denmark
Lidar measurement background Wind V wind V wind Lidar A lidar can only measure a portion of the wind vector!!! 6 DTU Wind Energy, Technical University of Denmark
Dual-Doppler V wind 7 Two independent LOS measurements Low elevation angles => neglect vertical component With two lidars it is possible to measure: - Horizontal wind speed - Wind direction DTU Wind Energy, Technical University of Denmark
Sector scan V wind θ 1 θ n θ 1 θ 2 θ 2 φ Flow horizontally homogenous Vertical component low Neglect vertical component Low elevation angle Sector scan => estimate horizontal wind speed and wind direction 8 DTU Wind Energy, Technical University of Denmark
Measurement set-up RUNE, sector scan vs. Dual-Doppler Measurement campaign: locations chosen Period: October-December 2015 Sea surface temperatures / wave parameters available (important to evaluate mesoscale model) Offshore floating lidar Onshore vertical shooting longrange lidar (wind profile 0-2000 m) Dual doppler setup scanning pattern from approximately 5 km up to shoreline over same distance (range gates 50 m) 9 DTU Wind Energy, Technical University of Denmark 19 October 2015
Pre-RUNE experiment, April-May 2014 Used filters Horizontal wind speeds from 4 to 25 m/s 90 hours Hard targets removal Wake free sectors Signal quality (-27dB <CNR<-8dB) 23 hours 10 min averaging 140 samples All LOS measurements for sector scan 75% of samples per each LOS of sector scan 10 DTU Wind Energy, Technical University of Denmark
Horizontal wind speed Cup anemometer Two lidars (Dual-Doppler) One lidar (Sector Scan 60 ) 11 DTU Wind Energy, Technical University of Denmark
Horizontal wind speed One lidar (Sector Scan 60 ) Two lidars (Dual-Doppler) dif dif Cup One lidar Two lidars Number of samples 140 140 140 Mean wind speed [m/s] 7.07 7.04 7.04 R 2 / 0.98 0.99 Difference [m/s] / 0.03 0.03 Difference [ %] / <1 <1 Standard deviation of the difference [m/s] / 0.32 0.10 12 DTU Wind Energy, Technical University of Denmark
What is the best azimuthal angle for scanning? Compromise between having a very large angle giving a large part of the sinusoidal and therefore certain wind speed, but homogeneity is questionable Small angle gives less certain wind speed but confined to a smaller spatial area Cup anemometer 13 DTU Wind Energy, Technical University of Denmark 19 October 2015
Results of comparison cup anemometer@80 m vs. scanning lidar at same point for different scanning angles 14 DTU Wind Energy, Technical University of Denmark 19 October 2015
Comparing the measurements and mesoscale models - 4 months measurements from wind lidar - Same period as RUNE experiment - Results from 5 grid points from the WRF model Wind speed (All) Wind speed (East) 15 DTU Wind Energy, Technical University of Denmark 19 October 2015
Conclusions One lidar will provide necessary local measurements, scanning with azimuthal angle of +- 45 degrees seems to give good results If you have sufficient funds there are merits of using two lidars: - Higher measurement rate - Small portion of area sampled - More measurement points - If the flow is not horizontally homogeneous A high pointing accuracy is crucial in achieving reliable measurements Unique data set for evaluating mesoscale models Thank you for your attention 16 DTU Wind Energy, Technical University of Denmark