The ScanFlow project is initiated in the framework of FP7 IRPWind – 1st call for Joint Experiments.

 

Full title

High-resolution full-scale wind field measurements of the ECN’s 2.5 MW aerodynamic research wind turbine using DTU’s 3D WindScanner and SpinnerLidar for IRPWind’s and EERA’s benchmark 

Applicants

DTU and ECN. Facility: ECN test site EWTW

 

Aim

The aim is to establish a unique turbine power performance and induction zone benchmark experiment by operating a DTU developed high-resolution nacelle integrated 2D SpinnerLidar installed at an 2.5MW ECN research wind turbine.

The ScanFlow project will provide a state-of-the-art inflow dataset useful for evaluation of aerodynamic models ranging from engineering-like up to computational fluid dynamics models, models of the inflow and induction zone. A proof-of concept testing of the new advanced software for wind reconstruction using the LINCOM model based on the anti-Cyclop buster methodology program will be applied by means of extracting all three wind components of the inflow in front of the rotor from a single Spinner lidar and by validating these results with the “true” ground based measurements of the three wind speed components (u,v,w) from the three short-range WindScanner lidars that will measure from the ground.

The benchmark will be available through an open access e-science platform, i.e. this website, also beyond project time. 

Introduction

Concurrently, three ground-based short-range WindScanner lidars from DTU will be deployed to perform 3D wind velocity field observations. Previous efforts on measuring the inflow induction zone upwind of turbines include the Vestas V27 at Risø, the NM80 wind turbine at Tjæreborg and NEG Nordtank 40 at Risø to provide prevision of the inflow in an upwind vertical plane. The scientific progress beyond these previous efforts will now be to achieve data from three vertical planes 10-minute averages of all three wind components. Furthermore we will also observe turbulence along one horizontal transect from 1Hz data. The baseline inflow i.e. when the turbine is not in operation and the induction zone from the operating row of turbines will be observed and quantified by a novel solution. Furthermore the rotor plane equivalent wind speed can be reverse- calculated to wind speed from wind power production at 1Hz fast production data and compared to WindScanner turbulence observations [8] as well at turbulence data from the meteorological mast. Finally, the inflow observed from lidar is of utmost importance for control of turbines and can be used for load calculation. The innovative aspect of the proposed work, involving detailed 2D and 3D inflow wind scanning is very high.

Recently it has been experimentally demonstrated that a lidar-based feed-forward control can reduce loads and pitch activity by high factors and in certain cases more than by 60%. The impact, technologically as well as economically, achievable from integrating nacelle or spinner lidars for advanced feed-forward wind turbine control is immense: Recently, it has been experimentally demonstrated that lidar- based feed-forward control can reduce tower bending moment loads and pitch activity by factors of 50% to 30% respectively. Prognoses for turbines equipped with lidar-assisted reduction in wind load foresees to be able to prolong the turbine life time by 30 % giving LOE of 6% and in some cases an expected life time extension of as much as + 6 years.

The latter study shows that through lidar-assisted improvements in yaw and gust tracking, an installed 2.5 MW turbine face slower turbulence losses and an expected increase in power capture, which in below rated winds would yield a gross AEP increase of 0.6% for the assumed wind speed distribution. Additionally, a decrease in blade and tower fatigue loads (the assumed design life driving loads) are expected to extend the turbine useful life from 20 to 26 years, allowing an additional 30% energy capture over the life of the turbine. Further, a decrease in traditional O&M costs is expected due to fewer component failures as a product of reduced dynamic loads, yet there is also an additional annual O&M cost for maintaining the lidar itself. Because the cost to maintain the lidar is greater than the O&M cost savings due to reduced failures, the annual average O&M cost increases 16% over the base case, cf. reference.

Key Performance Indicators

  • Obtain 6 weeks measurements with WindScanner SpinnerLidar at ECN wind turbine test field
  • Obtain data from three ground-based short-range WindScanner lidars during a two week campaign
  • Deliver the wind turbine 10 minute data power production, pitch angle and rotational speed to public database.
  • Deliver WindScanner 10 minute data to public database.