Employing lidars to evaluate turbine performance
Welcome to the first in a series about employing lidars to evaluate turbine performance. The series will cover some basics and present real-world examples and solutions.
This blog will describe the first step of a lidar measurement campaign, which is to define the horizontal wind measurement uncertainty as outlined in Annex L of the IEC 61400-12-1 Edition 2 (the IEC Standard). This can be broken down into two main categories, the Type Classification that is analogous to cup anemometer accuracy class, and the individual lidar device uncertainty that is analogous to a cup anemometer wind tunnel test.
Lidar Type Classification
The device accuracy class is determined by the methods outlined in Annex L.2. Classification. The purpose of a Classification is to obtain the uncertainty of horizontal wind speed measurement expected from a device with regards to its sensitivity to meteorological conditions. So, like a cup anemometer accuracy class determination, the classification identifies the device’s sensitivity to various independent environmental variables under a range of conditions, such as air temperature, turbulence intensity, wind veer, rain, etc. The sensitivity analysis requires at least three verifications against an IEC compliant mast in simple terrain using at least two units for which one unit is moved to a second location as shown in the image below.
Each verification must span over three months and cover a wide range of environmental conditions. Additionally, there must be at least three common heights, with one ±25% of the lower blade-tip and one ±25% of the hub height. However, as the Classification of a device is expensive and time consuming, independent engineers, such as DNV GL, complete the classification across a greater number of heights so that the results can be applied to many different turbines.
For each unit under test, a preliminary accuracy class is defined at each measurement height by combining the independent environmental variable sensitivities as described in L.2.9 of the IEC Standard. A device-specific class number is then obtained by dividing the preliminary accuracy class by √2. The device standard uncertainty is obtained by dividing the final accuracy class by √3. It should be noted that the Classification only applies to the device model and firmware under test, unless the firmware upgrade can be shown to have absolutely no modification to the wind speed derivation.
Individual Lidar Uncertainty
For an individual cup anemometer, a calibration uncertainty is quantified in a wind tunnel. However, there is currently no industry accepted method to calibrate a lidar in a laboratory. To overcome this, Annex L.3 and L.4 outline the methods to quantify the calibration uncertainty of a lidar by a verification against an IEC compliant mast either at an offsite location with similar environmental conditions or onsite. The test configuration requirements are the same as L.3, but the database is smaller: only 180 hours of data with three datapoints in 0.5 m/s bins from 4.0 m/s to 16.0 m/s are required. Typically, this database requirement is completed in four to six weeks.
The verification is valid for up to one year and applies to sites with similar environmental conditions. It should be noted that Edition 2 requires that a lidar verification test occur before and after the power performance test to ensure that the lidar measurement did not change over the turbine evaluation. This is also required for cup anemometers. The pre- and post-lidar verification uncertainties are referred to as the calibration and monitoring test uncertainties respectively in the IEC Standard.
However, a monitoring test can be eliminated if an Annex K in-situ check against the co-located monitoring mast is successful.
Lidar Category B Uncertainty Summary
The above Category B lidar wind speed uncertainties for a power performance test are summarized in the table below.
Category B Uncertainty – Wind speed RSD (uVR,i)
I hope this helped you better understand Annex L of the IEC standard and its purpose. Please join us next time when we dive into a lidar application case study.