Next Article in Journal
Automatic Building Segmentation of Aerial Imagery Using Multi-Constraint Fully Convolutional Networks
Next Article in Special Issue
Coherent Focused Lidars for Doppler Sensing of Aerosols and Wind
Previous Article in Journal
Modeling Wildfire-Induced Permafrost Deformation in an Alaskan Boreal Forest Using InSAR Observations
Previous Article in Special Issue
Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data
Article Menu
Issue 3 (March) cover image

Export Article

Open AccessProject Report
Remote Sens. 2018, 10(3), 406; https://doi.org/10.3390/rs10030406

IEA Wind Task 32: Wind Lidar
Identifying and Mitigating Barriers to the Adoption of Wind Lidar

1
WindForS, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
2
Wood-Clean Energy, 2nd Floor, St. Vincent Plaza, 319 St. Vincent Street, Glasgow G2 5LP, UK
3
Fraunhofer Institute for Wind Energy Systems IWES, Am Seedeich 45, 27572 Bremerhaven, Germany
4
Stuttgart Wind Energy, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
5
Envision Energy USA Ltd., 1201 Louisiana St. Suite 500, Houston, TX 77002, USA
6
DNV GL—Measurements, 1501 9th Avenue, Suite 900, Seattle, WA 98001, USA
7
Multiversum GmbH, Shanghaiallee 9, 20457 Hamburg, Germany
8
ForWind, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
9
Department for Wind Energy, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
10
Stuttgart Wind Energy, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
*
Author to whom correspondence should be addressed.
Received: 24 January 2018 / Revised: 19 February 2018 / Accepted: 23 February 2018 / Published: 6 March 2018
(This article belongs to the Special Issue Remote Sensing of Atmospheric Conditions for Wind Energy Applications)
View Full-Text   |   Download PDF [1361 KB, uploaded 9 March 2018]   |  

Abstract

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. View Full-Text
Keywords: wind energy; resource assessment; power performance testing; wind turbine controls; complex flow; Doppler lidar wind energy; resource assessment; power performance testing; wind turbine controls; complex flow; Doppler lidar
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Clifton, A.; Clive, P.; Gottschall, J.; Schlipf, D.; Simley, E.; Simmons, L.; Stein, D.; Trabucchi, D.; Vasiljevic, N.; Würth, I. IEA Wind Task 32: Wind Lidar
Identifying and Mitigating Barriers to the Adoption of Wind Lidar. Remote Sens. 2018, 10, 406.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top