47 research outputs found
Turbulence characterization from a forward-looking nacelle lidar
We present two methods to characterize turbulence in the turbine inflow using
radial velocity measurements from nacelle-mounted lidars. The first uses a
model of the three-dimensional spectral velocity tensor combined with a model
of the spatial radial velocity averaging of the lidars, and the second uses
the ensemble-averaged Doppler radial velocity spectrum. With the former,
filtered turbulence estimates can be predicted, whereas the latter model-free
method allows us to estimate unfiltered turbulence measures. Two types of
forward-looking nacelle lidars are investigated: a pulsed system that uses a
five-beam configuration and a continuous-wave system that scans conically. For
both types of lidars, we show how the radial velocity spectra of the lidar
beams are influenced by turbulence characteristics, and how to extract the
velocity-tensor parameters that are useful to predict the loads on a turbine.
We also show how the velocity-component variances and co-variances can be
estimated from the radial-velocity unfiltered variances of the lidar beams.
We demonstrate the methods using measurements from an experiment conducted at
the NĂžrrekĂŠr Enge wind farm in northern Denmark, where both types of
lidars were installed on the nacelle of a wind turbine. Comparison of the
lidar-based along-wind unfiltered variances with those from a cup anemometer
installed on a meteorological mast close to the turbine shows a bias of just
2âŻ%. The ratios of the unfiltered and filtered radial velocity variances
of the lidar beams to the cup-anemometer variances are well predicted by the
spectral model. However, other lidar-derived estimates of velocity-component
variances and co-variances do not agree with those from a sonic anemometer on
the mast, which we mostly attribute to the small cone angle of the lidar. The
velocity-tensor parameters derived from sonic-anemometer velocity spectra and
those derived from lidar radial velocity spectra agree well under both
near-neutral atmospheric stability and high wind-speed conditions, with
differences increasing with decreasing wind speed and increasing stability.
We also partly attribute these differences to the lidar beam configuration
Effects of bearing configuration in wind turbine gearbox reliability
AbstractThis paper investigates the impact on the reliability of different configurations of planet bearings. The studied bearings are located in the low-speed planetary stage of a wind turbine gearbox. The bearing stiffness matrix for each kind, cylindrical and tapered roller bearing (CRB and TRB), is included in the electro-mechanical drive-train simulation tool presented here. The system defined in Matlab/Simulink is co-simulated along with a wind turbine defined in an aeroelastic software. Moreover, the normal production design load case (DLC 1.1) is used to compute the bearing response to different turbulence seeds. From this, the fatigue and reliability of the bearings is calculated using the damage equivalent load and the first-order reliability method (FORM), where the L10h life is used as a limit state. The results indicate a relation between the reliability index and the bearing dynamic rating. However, when the actual parameters from the manufacturer are used, the TRB shows higher reliability even though its damage equivalent load is higher across the wind speed range
Assessing the Utility of Early Warning Systems for Detecting Failures in Major Wind Turbine Components
This paper provides enhancements to normal behaviour models for monitoring major wind turbine components and a methodology to assess the monitoring system reliability based on SCADA data and decision analysis. Typically, these monitoring systems are based on fully data-driven regression of damage sensitive-parameters. Firstly, the problem of selecting suitable inputs for building a temperature model of operating main bearings is addressed, based on a sensitivity study. This shows that the dimensionality of the dataset can be greatly reduced while reaching sufficient prediction accuracy. Subsequently, performance quantities are derived from a statistical description of the prediction error and used as input to a decision analysis. Two distinct intervention policies, replacement and repair, are compared in terms of expected utility. The aim of this study is to provide a method to quantify the benefit of implementing the online system from an economic risk perspective. Under the realistic hypotheses made, the numerical example shows for instance that replacement is not convenient compared to repair