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Inflow wind field measurements from nacelle-based lidar systems offer great potential for different applications including turbine control, load validation, and power performance measurements. On floating wind turbines nacelle-based lidar measurements are affected by the dynamic behavior of the floating foundations. Therefore, the effects on lidar wind speed measurements induced by floater dynamics must be understood. In this work, we investigate the influence of floater motions on wind speed measurements from forward-looking nacelle-based lidar systems mounted on floating offshore wind turbines (FOWTs) and suggest approaches for correcting motion-induced effects. We use an analytical model, employing the guide for the expression of uncertainty in measurements (GUM) methodology and a numerical lidar simulation for the quantification of uncertainties. It is found that the uncertainty of lidar wind speed estimates is mainly caused by the fore–aft motion of the lidar, resulting from the pitch displacement of the floater. Therefore, the uncertainty is heavily dependent on the amplitude and the frequency of the pitch motion. The bias of 10 min mean wind speed estimates is mainly influenced by the mean pitch angle of the floater and the pitch amplitude. We correct motion-induced biases in time-averaged lidar wind speed measurements with a model-based approach, employing the developed analytical model for uncertainty and bias quantification. Testing of the approach with simulated dynamics from two different FOWT concepts shows good results with remaining mean errors below 0.1 m s−1. For the correction of motion-induced fluctuation in instantaneous measurements, we use a frequency filter to correct fluctuations caused by floater pitch motions for instantaneous measurements. The correction approach's performance depends on the pitch period and amplitude of the FOWT design.

Presentations from the Wind Energy Science Conference 2023 Mini-Symposium OWA GloBE: Building Industry Consensus on the Global Blockage Effect in Offshore Wind.Presented as WESC in Glasgow, UK, on 24th May 2023

This is the material presented during the(first) IEA Wind Task 52 Lunch Seminar Series, which was held online onbetween 13-16 February2023 (all days 13-14 CET). The seminars were opened with an introduction by the Operating Agent, see20230215_IEA-Wind-Task52_lunch-seminar-INTRO_GotJul (1), followed by these presentations: Day 1 -- focus on Lidar-Assisted Control (LAC), organized by David Schlipf (20230213_LAC_WG) Feng Guo on "Improved modeling of lidar wind preview for wind turbine control"Feng_Guo_LunchSeminar_v2n Axel Schild on "Lidar-assisted model predictive turbine control"Schild_Challenges_on_the_way_to_indstrial_reality Day 2 -- focus on Complex Terrain, organized by Alexander Stoekl Andrew Hastings Black on "Point and lidar wind field reconstruction sensitivities in complex flow"IEATask52_LunchWebinarSeries_ComplexFlowWFR_AndrewBlack_14FEB2023 Johannes Becker on "Scanning LiDAR in Complex Terrain for Wind Ressource Assessment"GEO-NET_IEA-Task52-Lunch-Session_EWINO-Approach-Scanning-LiDAR-in-WRA_20230214 Day 3 -- focus on Scanning Lidar Offshore, organized by Andrew Oldroyd Yuko Ueda on "Validation of near-shore wind measurements using a dual scanning LiDAR"230215_task52_lunch_seminar_ueda Paula Gómez, Elliot Simon, Mike Courtney on "Guidelines for the usage of scanning lidars for power curve verification"20230215_IEA52_webinar Day 4-- focus on Floating Lidar, organized by Julia Gottschall Introductory presentation "Floating lidar within the IEA Wind 'Lidar' Task so far ..."20230216_IEA-Wind-Task52_Lunch-seminar_GotJul Peter Clive on "Floating lidar standards and guidance, an update centred around the upcoming technical specification IEC 61400-50-4"FLS Standard - update - 2023-02-16 Please note that each document or presentation may have its own license. If in doubt about reusing or citing any of the material presented here, please contact the authors.

Minutes ofIEA Wind Task 52 Kick-off / General Meeting

Slides by Task 52 Operating Agent (OA) for introducing the Task and details of Kick-off / General Meeting.

Oral presentation at the EERA DeepWind Conference 2022 Understanding the local wind conditions and climatology is a fundamental requirement for the successful development of new offshore wind farms. Ship-based lidar systems are a cost-efficient alternative for this purpose, and contrary to fixed floating lidars or meteorological masts, they provide accurate wind data not in a single location but within vast regions of interest. However, while the traditionally used measurement technologies have demonstrated performance in agreement with the accuracy standards used by industry, ship-mounted lidars require a greater comprehension of the levels of uncertainty associated with this novel technology. As an answer to this, this study proposes an analytical model for estimating the uncertainty of the wind speed and direction measured through the employment of ship-based Doppler pulsed lidars. The model follows the uncertainty propagation method taking into account the relevant parameters for assessing the wind speed like the radial velocity estimation, the half cone opening angle, or the lidar beams' orientation; and those variables specifically associated with non-stationary measurement systems such as the system tilting or the vessel's velocity. Additionally, the assurance of accurate and reliable ship-mounted lidar observations requires the implementation of a post-processing motion correction algorithm. Therefore, the derived uncertainty model also includes the implementation of a motion-compensation algorithm.

Nacelle-mounted lidars are finding more and more applications in the wind industry. Their use cases range from power performance testing to lidar-assisted control. Depending on the application, different wind field parameters are reconstructed from the lidar's line-of-sight wind measurements. Hereby, the respective scan geometry of the lidar determines the capabilities and limitations for the reconstruction of wind field parameters. In this study, we introduce the fan scan, a scanning pattern made of multiple nacelle-mounted lidars with the aim of an advanced wind field assessment to reconstruct more than three wind field parameters, which has been implemented at the Testfeld BHV site in Bremerhaven, Germany. Analytically derived uncertainties as well as calibration results for both, line-of-sight speeds and reconstructed wind field parameters, are presented indicating a good agreement with reference measurements. Additionally, a method for the reconstruction of the horizontal wind shear is introduced and applied to the fan scan data, highlighting the extended utilization possibilities of nacelle lidars.

In this contribution we introduce a Fraunhofer IWES floating lidar system (FLS) equipped with an integrated pulsed lidar device, motion sensors, near-surface atmospheric variable sensors (air temperature, relative humidity and air pressure) and a sea-surface temperature sensor. All measures were compared and validated with the nearby offshore meteorological mast FINO3 in the German North Sea. Atmospheric stability information was derived using the bulk Richardson formulation from the FINO3 station at both 30-m and 100-m as well as at the FLS at a 2-m height. The stability parameter was then extrapolated to the higher heights from the FLS using the mean wind speed measured from the lidar. The FLS was able to recreate the stability conditions calculated at the 30-m height but could not effectively match that of the 100-m calculations. This is mainly attributed to the significant changes with height of the atmospheric variables and their importance in the stability calculations.

Presentation at WindEurope 2021: Resource Assessment Quickfires on the first commercial scanning lidar campaign for wind resource assessment in mountainous terrain., A portion of the content from this talk was discussed at the IEA Task 32 General Meeting 16-18 November.

Presentation at the WindEurope 2021 Conference and Exhibition: Presented at the 23rd of November 2021 in theResource Assessment - Modelling & Measurements 1 Session. Funded by the Federal Ministry for Economic Affairs and Energy under grant no.03EE3024

Presentation at the EAWE PhD Seminar 2021 Understanding the in-situ wind conditions and climatology of a region is a fundamental requirement for the successful development of new offshore wind farms. However, meteorological (met) mast measurement campaigns are expensive, and the availability of high-reliable offshore observations is still scarce [1]. Consequently, numerical models have been widely used as an alternative by the wind industry to investigate wind resources at offshore sites. On the one hand, they are able to satisfactorily resolve the most relevant features of the marine atmospheric boundary layer. On the other hand, they provide wind and atmospheric parameters within a wide time and spatial range, and thus, they can address issues like the evaluation of wind climatology. Mesoscale model outputs have been extensively compared with experimental data in onshore and near-shore locations. However, further evaluations of the performance of the numerical models are still needed to better understand the capabilities and limitations of the modeled data in offshore sites. Furthermore, this fact is highlighted when considering heights above a few hundred meters, out of reach of the vast majority of measuring devices traditionally used for wind resource characterization. With this idea, the investigation presented here focuses on comparing one of the most widely used reanalyses within the wind energy industry, ERA5 (ECMWF Reanalysis 5th Generation) [2], with the observations of a long-range Doppler lidar. For this, data retrieved during the execution of a ship-based measurement campaign as part of the EUREC4A [3] project will be used. In this experiment, a Leosphere Windcube (WLS70) vertical profiler was installed onboard the research vessel Meteor, retrieving wind data up to 2,000 m height over the central Atlantic Ocean. With this comparison, we aim to investigate the performance of ERA5 in the offshore environment along the region covered by the vessel route, as well as to evaluate the potential influence of the elevation in the capabilities of this reanalysis dataset. References: [1] A. M. Sempreviva; R. J. Barthelmie; S. C. Pryor (2008): Review of Methodologies for Offshore Wind Resource Assessment in European Seas. In Surv Geophys 29 (6), pp.471–497. DOI: 10.1007/s10712-008-9050-2. [2] Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS).https://cds.climate.copernicus.eu/cdsapp#!/home [3] B. Stevens; S. Bony; D. Farrell; F. Ament; A. Blyth; C. Fairallet al. (2021): Eurec4A. In Earth System Science Data 132 (8), pp. 4067-4119. DOI:10.5194/essd-13-4067-2021

Ship-based lidar systems are a cost-efficient alternative for retrieving highly-reliable offshore wind data. However, the non-stationary nature of ship-mounted lidars hinders the comparison against reference datasets and, therefore, a straightforward characterization of the uncertainty levels associated with these sorts of measurements. For this reason, in this paper we have set up and report an analytical model for estimating the uncertainties of ship-based lidar measurements. The model follows the standard uncertainty propagation method considering the relevant parameters for assessing the wind speed from pulsed Doppler-lidar observations, such as the half cone opening angle, the radial velocity estimation, or the lidar beams' orientations. Additionally, the derivation of the presented uncertainty model contemplates the technology-specific variables and considerations like the ship linear velocity or tilting, as well as the implementation of a motion correction algorithm. &nbsp

A presentation part of the IEA Wind Task 32 webinar series on how to tackle challenges associated with wind resource assessment in complex terrain. We introduce the developed approach for combining scanning lidar measurements with flow modelling in order to improve numerical wind flow performance.

IEA Wind Task 32 on wind lidar for wind energy applications is planning a new phase, starting in 2022. This PDF contains an overview of the concept for the phase. It was presented at a Task 32 workshop on 4th August 2021. The participants in the workshop were split into breakout rooms where they added feedback and new ideas to the slides for each of the four themes. This input is included in slides 21 to 35. A previous workshop on the next phase of Task 32 took place on 15th July 2021. Results from the first workshop are available here., Please send any feedback about Task 32's plans to the Operating Agents at ieawind.task32@ifb.uni-stuttgart.de.

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IEA Wind Task 32 coordinates a range of research and development activities for wind lidar for wind energy applications. In order to help Task members and others keep an overview of what's happening in the Task, we have created a visual road map showing these activities. To find out more about specific activities, see the Task 32 website athttps://community.ieawind.org/task32/home. This repository includes: A PDF of the roadmap:"IEA_Wind_Task_32__Collaborative_RD_Roadmap.pdf". All of the files required to produce the roadmap using the LaTeX document preparation system: IEA Wind Task 32_ Collaborative RD Roadmap.zip. Please note that this document will be updated regularly. Please check for new versions athttps://doi.org/10.5281/zenodo.3374354. We welcomefeedback on the document.Please go to https://github.com/IEA-Wind-Task-32/white-paper-Task32-RnD-roadmapto find out how you can help improve this document.

The New European Wind Atlas (NEWA), the largest European project on wind resource assessment technology, has developed mesoscale-to-microscale wind atlas and site assessment methodologies alongside a validation strategy that leverages data from large field experiments as well as wind resource campaigns from industry through a formal verification and validation process. A probabilistic wind atlas approach, based on a multi-physics ensemble, provides means to quantify the uncertainty associated to the mesoscale configuration. Offline meso-micro coupling has been adopted to provide a modular approach for microscale models of different fidelities to share common mesoscale input data. An open-source model chain based on WRF and OpenFOAM codes has been released as reference for future model development and validation activities in connection to wind assessment best practices and standards.