Lidar profilers in the context of wind energy–a verification procedure for traceable measurements
Publication: Research - peer-review › Journal article – Annual report year: 2011
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Lidar profilers in the context of wind energy–a verification procedure for traceable measurements. / Gottschall, Julia; Courtney, Michael; Wagner, Rozenn; Ejsing Jørgensen, Hans; Antoniou, I.
In: Wind Energy, Vol. 15, No. 1, 2012, p. 147-159.Publication: Research - peer-review › Journal article – Annual report year: 2011
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TY - JOUR
T1 - Lidar profilers in the context of wind energy–a verification procedure for traceable measurements
A1 - Gottschall,Julia
A1 - Courtney,Michael
A1 - Wagner,Rozenn
A1 - Ejsing Jørgensen,Hans
A1 - Antoniou,I.
AU - Gottschall,Julia
AU - Courtney,Michael
AU - Wagner,Rozenn
AU - Ejsing Jørgensen,Hans
AU - Antoniou,I.
PB - John/Wiley & Sons Ltd.
PY - 2012
Y1 - 2012
N2 - The need for measuring wind speed and direction at greater heights and at several levels simultaneously gains importance as wind turbines become larger and higher. For this purpose, remote-sensing profilers become very attractive for resource assessment and power performance testing. However, the existing standards only permit the use of cup anemometers as standard instruments. The main issue preventing the use of remote sensors in such standards is the need to maintain the traceability of the measurements in the international standard system. In this paper, we describe a verification procedure for lidar profilers that enables us to achieve the required traceability. The procedure is based on a direct comparison of the measurements from the lidar and reference sensors mounted on a mast at various height levels. First, the data are corrected and filtered to obtain a representative data set ensuring a repeatable test. Second, a linear regression is applied to the data for each height. The third step is a bin-average analysis of the lidar error, i.e. the difference between the lidar and reference measurements, forming the basis for the ensuing uncertainty estimation. The results of the verification test are both used to correct the lidar measurements and to derive a corresponding uncertainty budget. A significant limitation of the procedure is the considerable uncertainty introduced by the reference sensors themselves. The decision as to whether to apply the derived correction as a lidar calibration or not therefore mainly depends on the interpretation of this reference uncertainty and the assumed and observed biases. Copyright © 2011 John Wiley & Sons, Ltd.
AB - The need for measuring wind speed and direction at greater heights and at several levels simultaneously gains importance as wind turbines become larger and higher. For this purpose, remote-sensing profilers become very attractive for resource assessment and power performance testing. However, the existing standards only permit the use of cup anemometers as standard instruments. The main issue preventing the use of remote sensors in such standards is the need to maintain the traceability of the measurements in the international standard system. In this paper, we describe a verification procedure for lidar profilers that enables us to achieve the required traceability. The procedure is based on a direct comparison of the measurements from the lidar and reference sensors mounted on a mast at various height levels. First, the data are corrected and filtered to obtain a representative data set ensuring a repeatable test. Second, a linear regression is applied to the data for each height. The third step is a bin-average analysis of the lidar error, i.e. the difference between the lidar and reference measurements, forming the basis for the ensuing uncertainty estimation. The results of the verification test are both used to correct the lidar measurements and to derive a corresponding uncertainty budget. A significant limitation of the procedure is the considerable uncertainty introduced by the reference sensors themselves. The decision as to whether to apply the derived correction as a lidar calibration or not therefore mainly depends on the interpretation of this reference uncertainty and the assumed and observed biases. Copyright © 2011 John Wiley & Sons, Ltd.
KW - uncertainty budget
KW - lidar testing
KW - verification
KW - classification
KW - IEC 61400-12-1
KW - calibration
U2 - 10.1002/we.518
DO - 10.1002/we.518
JO - Wind Energy
JF - Wind Energy
SN - 1095-4244
IS - 1
VL - 15
SP - 147
EP - 159
ER -