Browsing by Author "Clifton, Andrew"

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Open Access
Flying UltraSonic - a new way to measure the wind
(2020) Hofsäß, Martin; Bergmann, Dominique; Denzel, Jan; Clifton, Andrew; Cheng, Po Wen
Measurements of flow conditions with tall meteorological measurement masts at complex sites are expensive and can only be carried out with great effort. Concepts and new measuring methods are needed to assess these sites. This work aims to validate the performance of a measuring system based on UAV in complex terrain using on-site measurement. An unmanned aerial vehicle (UAV), more precisely a helicopter, was equipped with a standard 3-D ultrasonic anemometer. This UAV was positioned closed to a meteorological measuring mast and remained stationary at a constant altitude to measure the wind speed components. The data of the UAV were compared with a sensor installed on the measurement mast. The measurements shows a good agreement with an absolute deviation of 0.004 m/s and a relative deviation of 0.047 % for the horizontal wind speed. In the frequency domain the PSDs of the wind components u, v, w match the theoretical spectrum f^(-5/3) for the inertial subrange very well. With further improvements, this UAV equipped with a 3-D ultrasonic anemometer could be a very effective measurement tool for atmospheric research.
Open Access
IEA Wind Task 32: Wind Lidar : identifying and mitigating barriers to the adoption of wind lidar
(2018) Clifton, Andrew; Clive, Peter; Gottschall, Julia; Schlipf, David; Simley, Eric; Simmons, Luke; Stein, Detlef; Trabucchi, Davide; Vasiljevic, Nikola; Würth, Ines
IEA Wind Task 32 exists to identify and mitigate barriers to the adoption of lidar for wind energy applications. It leverages ongoing international research and development activities in academia and industry to investigate site assessment, power performance testing, controls and loads, and complex flows. Since its initiation in 2011, Task 32 has been responsible for several recommended practices and expert reports that have contributed to the adoption of ground-based, nacelle-based, and floating lidar by the wind industry. Future challenges include the development of lidar uncertainty models, best practices for data management, and developing community-based tools for data analysis, planning of lidar measurements and lidar configuration. This paper describes the barriers that Task 32 identified to the deployment of wind lidar in each of these application areas, and the steps that have been taken to confirm or mitigate the barriers. Task 32 will continue to be a meeting point for the international wind lidar community until at least 2020 and welcomes old and new participants.
Open Access
On the effects of inter-farm interactions at the offshore wind farm Alpha Ventus
(2021) Pettas, Vasilis; Kretschmer, Matthias; Clifton, Andrew; Cheng, Po Wen
Open Access
An ontology for describing wind lidar concepts
(2024) Costa, Francisco; Giyanani, Ashim; Liu, Dexing; Keane, Aidan; Ratti, Carlo Alberto; Clifton, Andrew
This article reports on an open-source ontology that has been developed to establish an industry-wide consensus on wind lidar concepts and terminology. The article provides an introduction to wind lidar ontology, provides an overview of its development, and provides a summary of its aims and achievements. The ontology serves both reference and educational purposes for wind energy applications and lidar technology. The article provides an overview of the creation process, the outcomes of the project, and the proposed uses of the ontology. The ontology is available online and provides standardisation of terminology within the lidar knowledge domain. The open-source framework provides the basis for information sharing and integration within remote sensing science and fields of application.
Open Access
Reducing the uncertainty of lidar measurements in complex terrain using a linear model approach
(2018) Hofsäß, Martin; Clifton, Andrew; Cheng, Po Wen
In complex terrain, ground-based lidar wind speed measurements sometimes show noticeable differences compared to measurements made with in-situ sensors mounted on meteorological masts. These differences are mostly caused by the inhomogeneities of the ﬂow ﬁeld and the applied reconstruction methods. This study investigates three different methods to optimize the reconstruction algorithm in order to improve the agreement between lidar measurements and data from sensors on meteorological masts. The methods include a typical velocity azimuth display (VAD) method, a leave-one-out cross-validation method, and a linear model which takes into account the gradients of the wind velocity components. In addition, further aspects such as the inﬂuence of the half opening angle of the scanning cone and the scan duration are considered. The measurements were carried out with two different lidar systems, that measured simultaneously. The reference was a 100 m high meteorological mast. The measurements took place in complex terrain characterized by a 150 m high escarpment. The results from the individual methods are quantitatively compared with the measurements of the cup anemometer mounted on the meteorological mast by means of the three parameters of a linear regression (slope, offset, R2) and the width of the 5th–95th quantile. The results show that expanding the half angle of the scanning cone from 20◦ to 55◦ reduces the offset by a factor of 14.9, but reducing the scan duration does not have an observable beneﬁt. The linear method has the lowest uncertainty and the best agreement with the reference data (i.e., lowest offset and scatter) of all of the methods that were investigated.