2024-03-28T09:43:19Z
https://zenodo.org/oai2d
oai:zenodo.org:3240434
2020-01-20T15:22:09Z
user-wind_energy
openaire
user-newa
Soret, A
Lozano, S
Torralba, V
Lledó, L
Manrique-Suñén, A
Cortesi, N
González-Reviriego, N
Bretonnière, P-A
Doblas-Reyes, F J
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. On climatological predictions of wind resource at sub-seasonal and seasonal horizons and how to visualize, quantify and interpret predictability skill scores. </p>
https://doi.org/10.5281/zenodo.3240434
oai:zenodo.org:3240434
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.3240433
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource assessment
seasonal forecasting
sub-seasonal forecasting
climate modeling
Valuing sub-seasonal to seasonal predictions for the wind energy sector
info:eu-repo/semantics/lecture
oai:zenodo.org:3709088
2020-03-13T20:20:14Z
software
user-newa
Andrea N. Hahmann
Neil N. Davis
Martin Dörenkämper
Tija Sile
Björn Witha
Wilke Trei
2020-03-13
<p>This archive provides the configuration files (namelists, vegetation parameters tables, geo files) used in the Weather Research and Forecasting (WRF) simulations that formed the basis of the New European Wind Atlas (NEWA). The archive is divided into two sections: (a) ensembles (configuration of the sensitivity experiments) and (b) production (configuration of the ten domains of the production run). An explanation for the various ensembles is provided in the NEWA-wind GitHub <a href="https://github.com/newa-wind">https://github.com/newa-wind</a>.</p>
https://doi.org/10.5281/zenodo.3709088
oai:zenodo.org:3709088
eng
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.3709087
info:eu-repo/semantics/openAccess
MIT License
https://opensource.org/licenses/MIT
wind resource assessment
WRF
mesoscale model simulations
high performance computing
fortran
python
WRF configuration files for NEWA mesoscale ensemble and production simulations
info:eu-repo/semantics/other
oai:zenodo.org:1194744
2020-01-20T14:21:27Z
user-wind_energy
user-newa
Sanz Rodrigo, Javier
Chávez Arroyo, Roberto A.
Moya, Iván
González-Rouco, Fidel
Fernández, Sergio
Hahmann, Andrea
Soret, Albert
Avila, Matias
Ivanell, Stefan
Witha, Björn
Gottschall, Julia
Chang, Chi-Yao
Palma, Jose L
Mentes, Sibel
Dutreux, Alexis
Candaele, Arnaud
Donnelly, Rory
Meyers, Johan
2016-03-24
<p>This report describes the validation directed program that will guide the planning of experiments and model development activities of NEWA. <br>
The program follows a formal verification and validation (V&V) framework originally developed by Sandia National Laboratory. It has two phases: the integrated planning and the experimental and modeling planning and execution. This report deals with the first phase where the aim is the identification of the relevant phenomena of the model-chain that will be necessary to meet the application objectives, and the hierarchy of validation exercises (also called benchmarks) that will be done in order to demonstrate how the model-chain actually integrates those phenomena. <br>
The benchmarks hierarchy is defined in terms of three dimensions: the observational dataset from which the validation data is extracted, the part of the model-chain that is being addressed and the validation objectives. These objectives are related to the phenomena of interest for the given application, in this case, with the development of a mesoscale to microscale model-chain for wind conditions assessment.<br>
The result is a planning instrument that will provide guidance to the data gathering activities in WP2, and help with the coordination of the work within WP3 to deliver a validated methodology for the production of the New European Wind Atlas and associated modeling tools. This initial planning is subject to change depending on the success of the observational data collection from the experiments and the call for wind data. <br>
</p>
https://doi.org/10.5281/zenodo.1194744
oai:zenodo.org:1194744
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.1194743
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, benchmark, model-chain, verification, validation, wind atlas
Report on hierarchy of benchmarks
info:eu-repo/semantics/report
oai:zenodo.org:1194717
2020-01-20T14:52:38Z
user-wind_energy
user-newa
Sanz Rodrigo, Javier
Chávez Arroyo, Roberto A.
Moya, Iván
Ivanell, Stefan
Arnqvist, Johan
2017-09-18
<p>This report summarizes the first round of benchmarks conducted under the <strong>NEWA validation strategy</strong>. An update of the validation program is provided with a schedule of forthcoming benchmarking activities based on the availability of experimental data. This report is the first of a series of three annual reports on NEWA benchmarks.</p>
<p>The first phase of the project has resulted in three main activities with a common objective of defining a baseline model-chain both at mesoscale and microscale levels.</p>
<p>The <strong>Mesoscale Sensitivity Test</strong> consisted on executing a sensitivity analysis of the WRF model coordinated by the NEWA mesoscale group around four European regions. This activity has been reported separately in deliverable 3.1 and concluded with the definition of a reference WRF set-up that will be used to produce the European Wind Atlas. Validation of this reference WRF configuration will be conducted in connection to the beta run of the wind atlas using available tall mast data from research and industry sites.</p>
<p>The <strong>Ryningsnäs Blind Test</strong> benchmark gathered a group of microscale modelers to simulate the mean profile of an atmospheric boundary layer (ABL) above a heterogeneous forest canopy on flat terrain and neutral atmospheric conditions. This benchmark tested canopy models that can use high-resolution canopy maps generated from aerial lidar scans. The results are currently compiled in to an article. The main findings are that the involved modeling groups, using models ranging from advanced industrial codes to state-of-the-art research codes, shows good agreement regarding mean wind profiles. The magnitude of the turbulent kinetic energy (TKE) generally match the observed one, but does not show the same directional dependence as the observed. The inability to model non-neutral conditions was striking. The learning outcome from the benchmark consortium is large and many key questions for future studies in the Hornamossen, i.e., from the extensive Swedish measurement campaign launched within NEWA, benchmark are defined.</p>
<p>The <strong>GABLS3 diurnal-cycle</strong> benchmark for wind energy applications revisited the original case developed by the boundary-layer meteorology community and adapted it to match the specific objectives of NEWA. Here, microscale modelers were asked to demonstrate that they can reproduce a real diurnal cycle with varying atmospheric stability and using input forcing produced offline from a mesoscale model (proxy for a wind atlas database). Mesoscale tendencies generated from WRF were provided as input to drive ABL RANS and LES models. All the models showed good consistency at assimilating tendencies even though some scatter remains depending on the particular settings of each code.</p>
<p>At this stage, we arrive to the first important milestone of the NEWA model-chain development, namely, the definition of a <strong>reference model-chain</strong> that includes:</p>
<ul>
<li>A reference WRF configuration derived after sensitivity analysis in various European regions.</li>
<li>A reference canopy model implementation in microscale ABL models that can use high-resolution aerial lidar scans.</li>
<li>A methodology for offline coupling of microscale models with mesoscale tendencies and transient turbulence modeling of varying atmospheric stability conditions.</li>
</ul>
<p>Next round of benchmarks will use experimental data recently produced by NEWA experiments to test these reference models in complex terrain, coastal and offshore environments. Meso-micro methodologies will be compared in terms of annual wind resource statistics using a hierarchy of models of varying fidelity levels. This will allow differentiating methods suitable for planning (wind atlas) or design phases of wind energy projects.</p>
https://doi.org/10.5281/zenodo.1194717
oai:zenodo.org:1194717
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.1194716
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, external conditions, benchmarking, diurnal cycle, GABLS3, Ryningsnäs, model-chain
Report on First Round of Benchmarks
info:eu-repo/semantics/report
oai:zenodo.org:3228296
2020-01-21T07:22:34Z
user-wind_energy
user-oswec
openaire_data
user-newa
Semenov, Sergei
Rasmussen, Steffen
Sørensen, Steen Arne
Sjöholm, Mikael
Vasiljevic, Nikola
Sempreviva, Anna-Maria
Mortensen, Niels Gylling
Paulsen, Uwe Schmidt
Feng , Ju
2018-10-10
<p>This is the update version of the wind energy taxonomies and restricted vocabularies which has been implemented in DTU Data (https://data.dtu.dk/DTU_Wind_Energy) with the purpose of accurately describing published data sets and data collections. The work on updating and implementing the wind energy taxonomies and restricted vocabularies has been done as a part of an internally funded 'FAIR digitalization' project of DTU Wind Energy(see 10.5281/zenodo.1493874). The work on updating the taxonomies and restricted vocabularies is a continuation of the work previously done under the IRPWind Open Data initiative (see 10.5281/zenodo.1199489). </p>
https://doi.org/10.5281/zenodo.3228296
oai:zenodo.org:3228296
eng
Zenodo
https://doi.org/10.5281/zenodo.1199489
https://doi.org/10.5281/zenodo.1493874
https://data.dtu.dk/DTU_Wind_Energy
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://zenodo.org/communities/oswec
https://doi.org/10.5281/zenodo.3228295
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
taxonomy
metadata
wind energy
restricted vocabularies
wind energy vocabularies
Wind energy taxonomies and restricted vocabularies
info:eu-repo/semantics/other
oai:zenodo.org:3240040
2020-01-20T15:33:31Z
user-wind_energy
openaire
user-newa
Menteş, Sibel
Kaytancı, Tarık
Ezber, Yasemin
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. Assessment of the NEWA mesoscale production run using 47 surface stations over a period of 10 years. Analysis of errors dependency on terrain elevation, terrain complexity, land-use, geographic region and distance to coast. </p>
https://doi.org/10.5281/zenodo.3240040
oai:zenodo.org:3240040
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.3240039
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource assessment
mesoscale
WRF
Assessment of surface wind from the long term production run over Turkey
info:eu-repo/semantics/lecture
oai:zenodo.org:1194748
2020-01-20T14:21:15Z
user-wind_energy
user-newa
Sanz Rodrigo, Javier
2016-09-01
<p>NEWA will develop a new reference methodology for wind resource assessment and wind turbine site suitability based on a mesoscale to microscale mode mode-chain. This new methodology will produce a more reliable wind characterization than current models,<br>
models leading to a significant reduction of uncertainties on wind energy production and wind conditions that affect the design of wind turbines.</p>
<p>This report outlines the concept for the mesoscale-to-microscale model-chain for wind assessment applications.</p>
https://doi.org/10.5281/zenodo.1194748
oai:zenodo.org:1194748
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.1194747
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, meso-micro, wind atlas, verification, validation
NEWA Model-Chain Concept Statement
info:eu-repo/semantics/report
oai:zenodo.org:2669129
2020-01-20T13:59:10Z
openaire
user-newa
Gottschall, Julia
Witha, Björn
2019-04-02
<p>The presentation consists of two parts: in the first part, the Ferry Lidar Experiment - which is one of the NEWA Experiments, ie a set of unique flow experiments conducted as part of the New European Wind Atlas (NEWA) Project - is introduced. For the Ferry Lidar Experiment a Doppler lidar instrument was placed on a ferry connecting Kiel and Klaipeda in the Southern Baltic Sea from February to June 2017. A comprehensive set of all relevant motions was recorded together with the lidar data and processed in order to obtain and provide corrected wind time series. In the second part of the presentation, first results of a benchmark study are presented which was conducted on the basis of the NEWA Ferry Lidar dataset. In this study a number of different mesoscale model simulations, provided by different participants of the study, are compared with the measurement data. </p>
https://doi.org/10.5281/zenodo.2669129
oai:zenodo.org:2669129
eng
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.2669128
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
The Ferry Lidar Experiment and Benchmark
info:eu-repo/semantics/lecture
oai:zenodo.org:3187482
2020-01-20T17:18:00Z
user-wind_energy
user-newa
Cantero, Elena
Borbón Guillén, Fernando
Sanz Rodrigo, Javier
Santos, Pedro
Mann, Jakob
Vasiljević, Nikola
Courtney, Michael
Martínez Villagrasa, Daniel
Martí, Belén
Cuxart, Joan
2019-05-23
<p>This report ALEX17, the acronym for ALaiz EXperiment 2017, is the last full-scale experiment within the NEWA (New European Wind Atlas) project, whose primary objective is to create a wind atlas of Europe that includes the state-of-the-art in modelling the wind resource, as well as the creation of a comprehensive database. ALEX17 aims to present a utility-scale measurements campaign to characterize the wind flow in complex terrain, through a combination of measurement technologies. Having finalized the measurements campaign and processed all the information, the wind flow in the area of study can be characterized for different weather conditions. In addition, the experimental data will be able to validate the reliability of numeric simulation models of wind flow in complex terrain, in order to reduce uncertainties when evaluating the wind resource.</p>
https://doi.org/10.5281/zenodo.3187482
oai:zenodo.org:3187482
eng
Zenodo
https://doi.org/10.11583/DTU.c.4508597
https://doi.org/10.5281/zenodo.3108565
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.3187481
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy
boundary-layer meteorology
LIDAR
wind resource assessment
atmospheric turbulence
complex terrain
Alaiz Experiment (ALEX17): Campaign and Data Report
info:eu-repo/semantics/report
oai:zenodo.org:4002351
2020-08-31T06:44:05Z
openaire_data
user-newa
Andrea N. Hahmann
2020-08-27
<p>These files contain summary statistics from the NEWA WRF mesoscale ensemble for a Northern European domain.</p>
<p>Each netCDF file includes:<br>
- Mean wind speed (50, 75, 100 and 150 m AGL)<br>
- Surface mean air density<br>
- Surface static fields (latitude, longitude, surface elevation and surface roughness)<br>
- Wind speed and direction frequency distribution (100 m AGL)</p>
<p>The WRF simulation setup and parameterizations correspond to those in the README.ensemble file.</p>
https://doi.org/10.5281/zenodo.4002351
oai:zenodo.org:4002351
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.4002350
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resources
New European Wind Atlas
WRF
Summary wind statistics from NEWA WRF mesoscale ensemble
info:eu-repo/semantics/other
oai:zenodo.org:3108565
2020-01-20T17:17:32Z
user-wind_energy
user-oswec
openaire
user-newa
Cantero, Elena
Borbón Guillén, Fernando
Sanz Rodrigo, Javier
Mann, Jakob
Courtney, Michael
Vasiljevic, Nikola
Martínez-Villagrasa, Daniel
Martí, Belén
Cuxart, Joan
Santos, Pedro
2019-04-01
<p>The Alaiz Experiment (ALEX17), located in Navarre (Spain), is a full-scale experiment that aims to peer into the microscale flow of a large-scale and complex topography influenced by mesoscale forcing.</p>
<p>The experimental site site consists of a mountain range of 1000m a.s.l with a well-known wind regime. To the North, aligned with the prevailing wind, measurement equipment are located at a valley 500m lower in altitude. The measurement campaign started in November/2017, with an intense observational period (IOP) of six months as well as 1-year of met mast measurements along with long-term means from a reference mast.<br>
<br>
The multi-lidar scanning patterns can provide 2D and 3D wind reconstruction over a 125m a.s.l. Z-shaped transect 10km long, being a unique feature from this experiment. The intersecting scans used for wind speed reconstruction can also be rendered into virtual met masts.<br>
<br>
Results show this multi-lidar layout is capable of capturing main flow patterns as speed-ups on ridge tops and valley flow between ridges, with valid data from 100m to 3500m.</p>
<p>The presentation summarizes the main layout and results of the experiment, pointing the way to access the open-source dataset of all equipment and documentation of ALEX17.</p>
https://doi.org/10.5281/zenodo.3108565
oai:zenodo.org:3108565
eng
Zenodo
https://doi.org/10.11583/DTU.7931444
https://doi.org/10.5281/zenodo.3187481
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://zenodo.org/communities/oswec
https://doi.org/10.5281/zenodo.2620504
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
WindEurope 2019, WindEurope Conference & Exhibition 2019, Bilbao, Spain, 02-April-2019
wind energy
scanning lidar
full-scale experiment
multi-lidars
WindScanner
The Alaiz Experiment (ALEX17): visualizing the flow in complex terrain with multi scanning lidars
info:eu-repo/semantics/lecture
oai:zenodo.org:2643720
2020-01-20T16:46:41Z
user-wind_energy
openaire
user-newa
Jose M. Laginha M. Palma
2019-04-02
<p>Presentation at the NEWA Final Workshop in April 2019. An overview of the Perdigão double-hill experiment, a large scale field experiment with the cooperation of USA and European research groups.</p>
https://doi.org/10.5281/zenodo.2643720
oai:zenodo.org:2643720
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2643719
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
NEWA
wind energy
boundary-layer meteorology
atmospheric turbulence
The Perdigão double-hill experiment
info:eu-repo/semantics/lecture
oai:zenodo.org:1194754
2020-01-20T16:25:06Z
user-wind_energy
openaire
user-newa
Sanz Rodrigo, Javier
Mann, Jakob
Gottschall, Julia
2017-11-28
<p>An overview of the challenges being addressed by the New European Wind Atlas (NEWA) consortium is presented together with the most important insights from the research activities carried out during the first half of the project. This €14-million EU project aims at producing a more reliable characterization of wind resources across Europe through a high resolution wind atlas and an experimental database that will lead to a significant reduction of uncertainties. Experimental campaigns of unprecedented scale and coverage have been conducted to map a wide range of terrain and wind conditions. This is the basis for the development of a model chain that blends relevant atmospheric scales from mesoscale to microscale. A seamless database of wind characteristics and associated uncertainties across Europe at a horizontal resolution of 100 m and representative for a 30-year period will be produced following a probabilistic wind atlas approach.</p>
https://doi.org/10.5281/zenodo.1194754
oai:zenodo.org:1194754
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.1194753
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, wind atlas, experiments, model-chain, validation, high-fidelity modeling
Challenges and Insights from the New European Wind Atlas Project
info:eu-repo/semantics/conferencePoster
oai:zenodo.org:1194760
2020-01-20T17:13:19Z
openaire
user-newa
user-eu
Sanz Rodrigo, Javier
Chávez Arroyo, Roberto Aurelio
2017-06-26
<p>A mesoscale to microscale model chain that relates large scale wind climatologies with site conditions, for the<br>
prediction of wind resources and siting parameters, is under development within the New European Wind Atlas<br>
(NEWA) project. A statistical-dynamic downscaling method is proposed here based on the blending of long-<br>
term statistics of mesoscale forcings, extracted from the WRF mesoscale model, with site conditions simulated<br>
with unsteady k-ε Raynolds-Averaged Navier Stokes (URANS). The dynamic coupling of WRF and CFDWind<br>
has been developed using the GABLS3 diurnal cycle benchmark in flat terrain. The coupling is done offline by<br>
first running the WRF model to obtain time series of mesoscale tendencies (pressure gradient and advection<br>
terms) at a horizontal resolution of 3 km. Then, these tendencies are averaged temporally using a 1-hr rolling<br>
mean and spatially over a 3x3 grid at the site of interest to filter out small-scale forcings that will be explicitly<br>
modelled at microscale. These tendencies are reduced to a cycle of input forcings for the microscale model to<br>
simulate prevailing wind conditions. The methodology is tested at the Cabauw 100-m mast in flat terrain.</p>
https://doi.org/10.5281/zenodo.1194760
oai:zenodo.org:1194760
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1194759
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, meso-micro, URANS, tendencies, microscale, CFD, ABL, Cabauw, GABLS3
Downscaling of Wind Resources From Mesoscale Tendencies with URANS
info:eu-repo/semantics/lecture
oai:zenodo.org:3243191
2020-01-20T16:13:05Z
user-newa
Badger, Jake
Soret, Albert
Gottschall, Julia
Davis, Neil
Witha, Björn
2019-06-11
<p>This report describes the fields and quantities that are to be served by the NEWA. It divides these into two parts, fields given at microscale and fields given at mesoscale. Tables describe in what heights the fields are given and whether the data are time mean or time varying. Because predictability is one of the newer fields to be presented by NEWA the methodologies used and quantities given are described in some detail. The report also outlines considerations given to data flow and data processing. Data handling issues are inherent within the model chain used in the wind atlas, and will be part of subsequent processing of the huge modelling datasets for the future. </p>
https://doi.org/10.5281/zenodo.3243191
oai:zenodo.org:3243191
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.3243190
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Report on definitions and database setup for the Wind Atlas (Deliverable D4.5)
info:eu-repo/semantics/report
oai:zenodo.org:3581412
2020-02-19T08:39:01Z
user-wind_energy
user-newa
Kühn, Paul
Basse, Alexander
Callies, Doron
Chen, Yiyin
Döpfer, Richard
Freier, Julia
Griesbach, Timm
Klaas, Tobias
Pauscher, Lukas
2018-09-12
<p>The NEWA Forested Hill Experiment Kassel was a field campaign conducted within the EU project – New European Wind Atlas NEWA. The experiment provides a unique dataset of wind measurements for validating models for flow over forested hilly terrain. It was performed around the »Rödeser Berg«, a hill located 20 km northwest of Fraunhofer IEE Kassel, Germany. The experiment consisted of a 3 month intensive campaign and a 1 year long-term campaign (November 2016 to October 2017). In total 17 wind measurement systems were used: 9 long-range Doppler scanning lidars, 6 lidar/sodar vertical wind profilers and 2 tall met masts.</p>
<p>By the end of the NEWA project all experimental data will be freely available. The measurement data will be provided in NetCDF format.</p>
<p>This technical report provides a detailed documentation of the field campaign.</p>
https://doi.org/10.5281/zenodo.3581412
oai:zenodo.org:3581412
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.3581411
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
NEWA, Wind, Measurement, Lidar
NEWA FORESTED HILL EXPERIMENT KASSEL - EXPERIMENT DOCUMENTATION
info:eu-repo/semantics/report
oai:zenodo.org:3240441
2020-01-20T15:30:10Z
user-wind_energy
openaire
user-newa
Badger, J
Bauwens, I
Hannesdóttir, A
Olsen, B
Zagar, M
Hristov, Y
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. Preview of the interface that will provide access to the NEWA wind atlas database and how it has been validated across Europe using data from Vestas while preserving confidentiality.</p>
https://doi.org/10.5281/zenodo.3240441
oai:zenodo.org:3240441
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.3240440
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource assessment
wind atlas
Wind atlas interface and validation with industry data
info:eu-repo/semantics/lecture
oai:zenodo.org:2643283
2020-01-20T17:39:11Z
openaire
user-newa
Soret, Albert
Lozano, Sergio
Torralba, Verónica
Lledó, Llorenç
Manrique-Suñén, Andrea
Cortesi, Nicola
González-Reviriego, Nube
Bretonnière, Pierre-Antoine
Doblas-Reyes, Francisco J.
2019-04-17
<p>Both renewable energy supply and electricity demand are strongly influenced by meteorological conditions and their evolution over time in terms of climate variability and climate change. This works as a major barrier to wind energy integration in electricity networks as knowledge of power output and demand forecasting beyond a few days remains poor. Current methodologies assume that long-term resource availability is constant, ignoring the fact that future wind resources could be significantly different from the past wind energy conditions. Such uncertainties create risks that affect investment in wind energy projects at the operational stage where energy yields affect cash flow and the balance of the grid. Here we assess whether sub-seasonal to seasonal climate predictions (S2S) can skilfully predict wind speed in Europe. To illustrate S2S potential applications, two periods with an unusual climate behaviour affecting the energy market will be presented. We find that wind speed forecasted using S2S exhibit predictability some weeks and months in advance in important regions for the energy sector such as the North Sea. If S2S are incorporated into planning activities for energy traders, energy producers, plant operators, plant investors, they could help improve management climate variability related risks.</p>
https://doi.org/10.5281/zenodo.2643283
oai:zenodo.org:2643283
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.2643282
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Wind energy, climate services, S2S, cilmate predictions
Valuing sub-seasonal to seasonal predictions for the wind energy sector
info:eu-repo/semantics/lecture
oai:zenodo.org:2682604
2020-01-20T17:37:55Z
user-newa
Witha, Björn
Hahmann, Andrea
Sile, Tija
Dörenkämper, Martin
Ezber, Yasemin
García-Bustamante, Elena
González-Rouco, J. Fidel
Leroy, Grégoire
Navarro, Jorge
2019-05-09
<p>This report describes the sensitivity studies performed with the mesoscale model WRF in preparation of the mesoscale wind atlas production runs. The objective of this work was to find a model setup that is not just a best practice setup but well-founded and based on scientific evaluation.</p>
<p>We started with performing some initial sensitivity experiments changing the PBL scheme and the initialisation of the model. The work was distributed among several partners, each conducting the same set of experiments but on a different domain. The objective of this first phase was to ensure that everybody speaks the same language in terms of applying WRF in the context of NEWA. The results were analysed and compared in terms of the mean wind climate. To draw conclusions regarding the quality of the experiments, the results of one domain were compared to tall mast observations. Overall the model showed a good performance with slightly better results for one of the two tested PBL schemes (MYNN) and weekly initialisation of simulations (compared to daily).</p>
<p>In the next phase, further sensitivity tests were conducted for one of the previously defined domains, varying a multitude of parameters as e.g. model version, vertical resolution, forcing data and land surface parameterisation. These studies showed that virtually each parameter change is affecting the results in some way, while significant effects on the wind climate are mostly obtained by changes in physical parameterisation e.g. PBL scheme, representation of the land surface and surface roughness. However, also non-physical parameters as the simulation length and the domain size affects the results considerably. The results suggest to use rather small domains and not too long simulations (in the order of 1–2 weeks).</p>
<p>One of the objectives of NEWA is to create a probabilistic wind atlas, i.e. to provide uncertainty information to the mesoscale wind atlas (see Deliverables D3.1 and D4.4). This will be achieved by generating an ensemble of WRF simulations with different model configurations. While the final ensemble to be run over the complete NEWA domain will only include a few members, a much larger ensemble was run for a smaller sub-domain to find the ensemble members that generate the largest spread and will be used in the final NEWA ensemble. A second objective of this initial large ensemble was to find an optimal setup for the mesoscale production run. Based on the experience gained in the previous sensitivity experiments, a 47-member ensemble was assembled and run. The individual members were compared against each other, as well as against tall mast observations. Different metrics were explored to assess the performance of the members, i.e. not only the usual statistical measures as RMSE, BIAS and correlation but also metrics that compare the wind speed distributions.</p>
<p>In the final part of this report we present the ultimate WRF setup for the NEWA production run that was run between August 2018 and March 2019 on the MareNostrum supercomputer in Barcelona.</p>
https://doi.org/10.5281/zenodo.2682604
oai:zenodo.org:2682604
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.2682603
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource assessment
wind atlas
WRF
mesoscale
WRF model sensitivity studies and specifications for the NEWA mesoscale wind atlas production runs
info:eu-repo/semantics/report
oai:zenodo.org:3358598
2020-01-20T16:29:45Z
user-wind_energy
user-oswec
openaire
user-wesc2019
user-newa
Santos, Pedro
Borbón, Fernando
Mann, Jakob
Cantero, Elena
Vasiljević, Nikola
Sanz Rodrigo, Javier
Courtney, Michael
Martinez-Villagrasa, Daniel
Martí, Belén
Cuxart, Joan
2019-06-18
<p>In this talk, we present results of multi-lidar measurements from the Alaiz Experiment (ALEX17), carried out in a collaboration between DTU Wind Energy, CENER and UIB. Dual-Doppler synchronized measurements (125 m a.g.l.) are performed by four WindScanner systems on top of a ridge and a mountain range that are 6km apart. Results provide a first step towards resource assessment using scanning lidars, at the same time featuring the challenges faced to obtain a high data availability. The most common flow patterns are also highlighted, being gravity waves from notherly winds and atmospheric hydraulic jumps from southerly winds. These atmospheric phenomena are going to be better analyzed in an upcoming journal paper.</p>
https://doi.org/10.5281/zenodo.3358598
oai:zenodo.org:3358598
Zenodo
https://doi.org/10.11583/DTU.c.4508597.v1
https://doi.org/10.5281/zenodo.3187482
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://zenodo.org/communities/oswec
https://zenodo.org/communities/wesc2019
https://doi.org/10.5281/zenodo.3358597
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
WESC 2019, Wind Energy Science Conference, Cork, Ireland, 17-20 June 2019
multi-lidar
resource assessment
gravity wave
atmospheric hydraulic jump
full-scale experiment
Multi scanning lidar measurements for resource assessment: a case study in complex terrain
info:eu-repo/semantics/lecture
oai:zenodo.org:2685879
2020-01-20T16:46:52Z
user-wind_energy
openaire
user-newa
Charlotte Hasager
Merete Badger
Tobias Ahsbahs
Ioanna Karagali
Andrea Hahmann
Jakob Mann
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. Overview of SAR and Scatterometer satellite wind maps useful for quantification of coastal effects, wind farm effects and for the validation of models for pre-site assessment. </p>
https://doi.org/10.5281/zenodo.2685879
oai:zenodo.org:2685879
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2685878
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource
SAR
Scatterometer
satellite wind
European offshore winds based on satellite data relevant for the wind industry
info:eu-repo/semantics/lecture
oai:zenodo.org:4192667
2021-01-29T08:52:02Z
openaire
user-wakebench
user-newa
Sanz Rodrigo, Javier
2018-03-13
<p>Presentation of the Meso-Micro Challenge organized by the NEWA project to test mesoscale-to-microscale flow models in the prediction of wind conditions and AEP at the NEWA experimental sties. Initial results are provided at Cabauw as a follow-up of the model development and validation activities around the GABLS3 diurnal cycles benchmark. The results were presented at Torque 2018.</p>
https://doi.org/10.5281/zenodo.4192667
oai:zenodo.org:4192667
eng
Zenodo
https://doi.org/10.1088/1742–6596/1037/7/072030
https://zenodo.org/communities/newa
https://zenodo.org/communities/wakebench
https://doi.org/10.5281/zenodo.4192666
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Torque 2018, The Science of Making Torque from Wind, Milano, 20-22 June 2018
meso-micro
AEP
wind resource assessment
wind conditions
NEWA Meso-Micro Challenge
info:eu-repo/semantics/lecture
oai:zenodo.org:1305064
2020-01-20T16:44:49Z
user-wind_energy
user-newa
Roberto Aurelio Chávez Arroyo
Javier Sanz Rodrigo
2018-07-04
<p>This report provides a brief user’s manual for the first release of the NEWA open-source model-chain. The document is associated to a public git repository that will be updated throughout the rest of the project. <br>
The objective of this release is to allow early-adopters of the model-chain to start testing the open-source code and, eventually, provide feedback to the NEWA developers about usability, possible bugs, robustness, etc. <br>
The repositories consist of:</p>
<ul>
<li>CFDWind3 OpenFOAM libraries to run atmospheric-boundary layer microscale simulations driven by mesoscale inputs. Tutorial test case based on the GABLS3 diurnal-cycle benchmark. Repository available at: <a href="https://github.com/iat-cener/CFDWind">https://github.com/iat-cener/CFDWind</a></li>
</ul>
<p>Additional test cases will be added in the future as new benchmarks are produced based on the experiments of the project. <br>
The report provides an overview of the model-chain context and its intended use followed by a description of CFDWind3 libraries. Finally, an outlook on future developments is provided.</p>
https://doi.org/10.5281/zenodo.1305064
oai:zenodo.org:1305064
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.1305063
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy
wind resource assessment
CFD
atmospheric boundary layer
OpenFOAM
GABLS3
NEWA Open-Source Model-Chain v1.0
info:eu-repo/semantics/report
oai:zenodo.org:3250200
2020-01-20T14:45:46Z
user-newa
Steinfeld, Gerald
2019-06-19
<p>This report summarizes in the first three sections the procedure that has been followed within the first twelve months of the NEWA project in order to outline the final product of the project, a New European Wind Atlas data base.</p>
<p>For this, potential future users of the New European Wind Atlas were invited to take part in a questionnaire on stakeholders’ expectations to a new wind atlas data base for Europe. It turned out that the stakeholders were especially interested in long-term time series data from meso-scale simulations (the length of the period covered by the wind atlas expected by the stakeholders is about 25 years, the temporal resolution expected by the stakeholders is about 10 minutes and the spatial resolution expected by the stakeholders is about 1 km) as well as in a well-documented methodology that allows for a further downscaling of the meso-scale time series to a target site with a micro-scale model. Moreover, the participants of the questionnaire were especially interested in information on extreme values and on detailed guidelines how the data provided in the wind atlas data base can actually be used. On the other hand, there was interest but at a slightly lower level also in additional statistical data. The stakeholder expectations were summarized to a preliminary list of NEWA output parameters.</p>
<p>In a second step, the results of the questionnaire were presented for discussion within the consortium in order to adapt the full amount of stakeholders’ expectations to a technically feasible amount taking into account the limited real and computing time that will be available to derive the wind atlas data base and the limited disk space that will be available to host the data base. This step included presentations on several workshops of the project as well as a second, but this time project internal survey.</p>
<p>The resulting, preliminary suggestions for the contents of the New European Wind Atlas are documented in detail in this report. They were presented for a final discussion at the NEWA WP 3 workshop in Barcelona in September 2016, being the basis for the final list of suggested NEWA output parameters and the conclusion of Task 4.1 of the project.</p>
The work of Carl von Ossietzky Universität Oldenburg in the NEWA project was funded by the German Federal Ministry for Economic Affairs and Energy under grant number 0325832B.
https://doi.org/10.5281/zenodo.3250200
oai:zenodo.org:3250200
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.3250199
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Report on the definition of wind atlas output parameters: Catalogue of output parameters to be stored in the data base and output parameters of the model chain
info:eu-repo/semantics/report
oai:zenodo.org:3228082
2020-01-20T17:14:16Z
openaire
user-newa
Chávez Arroyo, Roberto Aurelio
Sanz Rodrigo, Javier
Gancarski, Pawel
Cantero, Elena
Borbón, Fernando
Santos, Pedro
2019-05-24
<p>This work presents the development of a model-chain for the simulation of Atmospheric Boundary Layer flows through an open-science approach. The presentation introduces the different stages of the open-science methodology which starts with the release of the open-source CFD code and the open-access validation data developed throughout the NEWA project. It also contains the open-access publications and description of the scripts employed for the comparison with the measurements so that it can serve as a case example for other model developments, and to the wind energy industry as a platform for validation & verification procedures for current and potentially new tools.</p>
https://doi.org/10.5281/zenodo.3228082
oai:zenodo.org:3228082
eng
Zenodo
https://doi.org/10.5281/zenodo.3187482
https://doi.org/10.5281/zenodo.1305064
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.3228081
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
WindEurope, Bilbao, Spain, 2-4/April/2019
open science
open data
wind energy
atmospheric boundary layer
CFD
wind resource assessment
ALEX17
Meso-to-microscale modelling of the Atmospheric Boundary Layer: an open-science approach
info:eu-repo/semantics/lecture
oai:zenodo.org:3596596
2020-01-20T13:59:10Z
user-newa
Gottschall, Julia
2019-06-30
<p>This report describes the procedures that were proposed to derive extreme wind estimates for the New European Wind Atlas (NEWA). Data basis for the estimations are the NEWA mesoscale simulations comprising the NEWA mesoscale wind atlas. A modified Spectral Correction Method (SCM) is applied to take the smoothing effect of these data in comparison to on-site measurements into account. Initial verifications show that this correction approach works quite well for simple offshore sites without significant miscroscale effects. For more complex sites an additional downscaling approach is required, that is described in this report but could not applied anymore due to missing input data which are required from the processed wind atlas data.</p>
<p> </p>
<p> </p>
https://doi.org/10.5281/zenodo.3596596
oai:zenodo.org:3596596
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.3596595
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Report on models for extreme winds (NEWA Deliverable D4.2)
info:eu-repo/semantics/report
oai:zenodo.org:834356
2020-07-22T10:40:46Z
user-wind_energy
software
user-wakebench
user-newa
user-eu
Javier Sanz Rodrigo
2017-07-24
<p>In this repository you can find the jupyter notebook that was used to post-process CFDWindSCM simulations of the GABLS3 diurnal cycle case. Based on this work a Windbench benchmark for wind energy applications was designed: http://windbench.net/gabls-3</p>
<p>The input data can be fetched from the EUDAT repository:http://doi.org/10.23728/b2share.22e419b663cb4ffca8107391b6716c1b</p>
<p>and the validation data from the original GABLS3 website at KNMI:http://projects.knmi.nl/gabls/gabls3_scm_cabauw_obs_v33.nc</p>
<p>The results were published in the following journal paper: Sanz Rodrigo J, Churchfield M, Kosović B (2017) A methodology for the design and testing of atmospheric boundary layer models for wind energy applications. Wind Energ. Sci. 2: 1-20, https://doi.org/10.5194/wes-2-35-2017</p>
https://doi.org/10.5281/zenodo.834356
oai:zenodo.org:834356
Zenodo
https://github.com/jsrodrigo/GABLS3-CFDWindSCM/tree/v1.0
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://zenodo.org/communities/wakebench
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.834355
info:eu-repo/semantics/openAccess
GNU General Public License v2.0 only
https://www.gnu.org/licenses/old-licenses/gpl-2.0-standalone.html
Wind Energy Science, 2, 1-20, (2017-07-24)
gabls3
meso-micro
wind
windbench
validation
Assessment of meso-micro offline coupling methodology based on driving CFDWind single-column-model with WRF tendencies: the GABLS3 diurnal cycle case
info:eu-repo/semantics/other
oai:zenodo.org:1194752
2020-01-20T16:13:31Z
openaire
user-newa
Sanz Rodrigo, Javier
Mann, Jakob
Gottschall, Julia
2017-11-28
<p>Presentation in the 2017 WindEurope annual conference of an overview of the open-data deliverables from the New European Wind Atlas project, notably:</p>
<ul>
<li>a database of large-scale experiments conducted over a wide range of topographic and wind climate conditions</li>
<li>an open-source model-chain based on WRF and OpenFOAM and means to couple them </li>
<li>a repository of validation benchmarks based on the experimental data</li>
<li>a web interface to access a high resolution wind atlas database</li>
</ul>
<p>These open data repositories will be published through 2019.</p>
https://doi.org/10.5281/zenodo.1194752
oai:zenodo.org:1194752
eng
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.1194751
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, open science, experiments, wind atlas, model-chain, validation, open-access
Open Science in the New European Wind Atlas
info:eu-repo/semantics/lecture
oai:zenodo.org:2685057
2020-01-20T17:37:19Z
user-wind_energy
openaire
user-newa
Jakob Mann
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. It provides a description of the RUNE and Balcony experiments using scanning lidars, among other systems, to measure the the flow field in a coastal transition (RUNE) and above a patchy forest canopy (Balcony). Both experiments are available open-access.</p>
https://doi.org/10.5281/zenodo.2685057
oai:zenodo.org:2685057
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2685056
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource
LIDAR
canopy
turbulence
boundary-layer meteorology
The RUNE and Balcony scanning-lidar experiments
info:eu-repo/semantics/lecture
oai:zenodo.org:2620505
2020-01-20T17:17:40Z
user-wind_energy
user-oswec
openaire
user-newa
Cantero, Elena
Borbón Guillén, Fernando
Sanz Rodrigo, Javier
Mann, Jakob
Courtney, Michael
Vasiljevic, Nikola
Martínez-Villagrasa, Daniel
Martí, Belén
Cuxart, Joan
Santos, Pedro
2019-04-01
<p>The Alaiz Experiment (ALEX17), located in Navarre (Spain), is a full-scale experiment that aims to peer into the microscale flow of a large-scale and complex topography influenced by mesoscale forcing.</p>
<p>The experimental site site consists of a mountain range of 1000m a.s.l with a well-known wind regime. To the North, aligned with the prevailing wind, measurement equipment are located at a valley 500m lower in altitude. The measurement campaign started in November/2017, with an intense observational period (IOP) of six months as well as 1-year of met mast measurements along with long-term means from a reference mast.<br>
<br>
The multi-lidar scanning patterns can provide 2D and 3D wind reconstruction over a 125m a.s.l. Z-shaped transect 10km long, being a unique feature from this experiment. The intersecting scans used for wind speed reconstruction can also be rendered into virtual met masts.<br>
<br>
Results show this multi-lidar layout is capable of capturing main flow patterns as speed-ups on ridge tops and valley flow between ridges, with valid data from 100m to 3500m.</p>
<p>The presentation summarizes the main layout and results of the experiment, pointing the way to access the open-source dataset of all equipment and documentation of ALEX17.</p>
https://doi.org/10.5281/zenodo.2620505
oai:zenodo.org:2620505
eng
Zenodo
https://doi.org/10.11583/DTU.7931444
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://zenodo.org/communities/oswec
https://doi.org/10.5281/zenodo.2620504
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
WindEurope 2019, WindEurope Conference & Exhibition 2019, Bilbao, Spain, 02-April-2019
wind energy
scanning lidar
full-scale experiment
multi-lidars
WindScanner
The Alaiz Experiment (ALEX17): visualizing the flow in complex terrain with multi scanning lidars
info:eu-repo/semantics/lecture
oai:zenodo.org:3240424
2020-01-20T15:16:22Z
user-wind_energy
openaire
user-newa
González-Rouco, J F
Navarro, J
García-Bustamante, E
Lucio-Eceiza, E
Rojas-Labanda, C
Hahmman, A N
Witha, B
Sïle, T
Sastre-Marugan, M
Dörenkämper, M
Mentes, S
Ezber, Y
Barcons, J
Palomares, A
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao.</p>
<p>OUTLINE:</p>
<ul>
<li>Uncertainties in model-data comparison</li>
<li>Evaluation of WRF regional simulations:
<ul>
<li>Various sources of information: observational uncertainty</li>
<li>Realism of WRF in reproducing observed wind variability</li>
</ul>
</li>
<li>Sensitivity of WRF wind climatology to different configurations of the</li>
<li>model:
<ul>
<li>How can we characterize model spread?</li>
</ul>
</li>
</ul>
https://doi.org/10.5281/zenodo.3240424
oai:zenodo.org:3240424
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.3240423
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource assessment
surface stations
WRF
sensitivity analysis
Europe blown by the (observed and simulated) wind
info:eu-repo/semantics/lecture
oai:zenodo.org:3243193
2020-01-20T15:45:35Z
user-newa
Badger, Jake
Sempreviva, Anna Maria
Söderberg, Stefan
Costa, Paula Alexandra
Simoes, Teresa
Estanqueiro, Ana
Gottschall, Julia
Dörenkämper, Martin
Callies, Doron
Navarro Montesinos, Jorge
González Rouco, J. Fidel
Garcia Bustamante, Elena
Bauwens, Ides
2019-06-11
<p>This document provides information for numerous wind atlas, relevant to the New European Wind Atlas. It uses the taxonomy and metadata card format, developed for the wind energy sector and wind resource assessment, in particular, by the European collaborators within the IPRWind project. By using this taxonomy various aspects the wind atlases can be as compared and features in common can be examined. </p>
https://doi.org/10.5281/zenodo.3243193
oai:zenodo.org:3243193
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.3243192
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Report on Link to Global Wind Atlas and National Wind Atlases (Deliverable D4.7)
info:eu-repo/semantics/report
oai:zenodo.org:2669083
2020-01-20T17:04:51Z
openaire
user-newa
Gottschall, Julia
2019-04-02
<p>The presentation gives a summary of what the NEWA final wind Atlas product will provide in terms of extreme winds. 50-year winds defined according to IEC 61400-1 are estimated from the time series data of the mesoscale wind data. In order to counteract the occurring smooting effect, a modified Spectral Correction Method is applied. Details about the procedure and its validation for a few selected sites were already published in Bastine et al. (in: IOP Conf. Series: Journal of Physics: Conf. Series 1102, 2018, doi: 10.1088/1742-6596/1102/1/012006).</p>
<p> </p>
https://doi.org/10.5281/zenodo.2669083
oai:zenodo.org:2669083
eng
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.2669082
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Extreme Winds in the New European Wind Atlas
info:eu-repo/semantics/lecture
oai:zenodo.org:1194733
2020-01-20T17:04:29Z
user-wind_energy
user-newa
Chávez Arroyo, Roberto Aurelio
Sanz Rodrigo, Javier
Bechmann, Andreas
Avila, Matias
Owen, Herbert
Chang, Chi-Yao
Candaele, Arnaud
2016-04-22
<p>This report describes the first tasks towards the downscaling methodologies that will be used to link mesoscale outputs from the New European Wind Atlas with microscale models in connection to wind farm design tools. <br>
This initial report provides a review of existing downscaling methodologies applied in the context of wind energy applications. This is used to frame the development of the NEWA model-chain which will allow microscale models to be used in connection to input data derived from mesoscale models. The mesoscale to microscale methodology will provide means to relate the long-term wind climatology, characterized by a mesoscale model, with the design conditions at site level where wind farm design takes place. <br>
This report deals with microscale models, typically implemented on computational fluid dynamic (CFD) solvers. A list of the participating models in NEWA is provided in the Annex. The initial challenge is to make theses codes intercomparable so we can extract meaningful conclusions when we evaluate simulations in connection with validation cases. Before comparing simulations and observational data, we need to assess the numerical error due to the sensitivity of the result to the model set-up. This is particularly important in complex terrain where grid dependencies can be significant. <br>
The objective of the initial effort of the NEWA microscale team has been focused on using different methods of assessing grid dependencies. This has been done with different microscale models applied to the three complex terrain test cases where dedicated field experiments are planned: Kassel (forested hill), Perdigao (double-hill) and Alaiz (hill and mountain range). In order to make the results more comparable in terms of numerical errors, the reference physical model adopted in the study has been based on neutral, steady-state, surface-layer conditions. This is a Reynolds-independent model that removes the dependency of the results with the wind speed. <br>
The results show significant variability of numerical errors with the grid set-up which includes the inherent sensitivity to the wind direction. These results will be used to define best practices for setting up a microscale model simulation with specific requirements for wind resource assessment applications.</p>
https://doi.org/10.5281/zenodo.1194733
oai:zenodo.org:1194733
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.1194732
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, downscaling, microscale model, complex terrain, CFD
Description of downscaling methodologies
info:eu-repo/semantics/report
oai:zenodo.org:1194705
2020-01-20T14:44:12Z
user-wind_energy
user-newa
Soret, Albert
Torralba, Veónica
Cortesi, Nicola
Lozano Galiana, Sergio
Sanz Rodrigo, Javier
2016-03-29
<p>This report describes the methodology that will be used to produce information about wind predictability in the European wind atlas. A review of the state-of-the-art in predictability assessment is reported at different scales, from day ahead (short-term) to subseasonal (medium-term predictability), seasonal and decadal (long-term predictability). The report provides an overview of the potential applications of wind predictability, the sources of predictability, the available prediction systems and the methods to evaluate them.<br>
Short-term predictability was first studied in the frame of the European project SAFEWIND. A summary of that work is included here in order to show the continuity of this activity in the NEWA project and how it will be integrated with other scales of prediction. Predictability mapping was carried out using forecasts from numerical weather prediction and comparing them with reanalysis data. Downscaling to site level to produce wind power predictability information, based on information from the planning phase, was also done in order to illustrate how a wind farm developer could anticipate costs of lack of predictability during the operational phase.<br>
Medium to long term predictability is studied with global climate models. Preliminary assessment of predictability is also done using reanalysis data as a reference of the real state of the atmosphere. This allows to map predictability skill over Europe. Preliminary results detected at least two windows of opportunity (high forecast skill) over Europe, one at sub-seasonal time scale, for a lead time of 12-18 days, and another at seasonal scale, for a lead time of one month. This skill is found to exist mainly over Central and Northern Europe and to a lesser degree in the Iberian Peninsula during the winter months of December-February.<br>
Having demonstrated that there is statistically significant wind speed skill during winter over some European areas, the end users could gain potential economic value using the forecasts instead of the climatology to base their decisions. Over these areas, novel techniques that employ this probabilistic information effectively to enhance the value of operational business decisions and quantitative risk management in the wind energy sector can be developed.<br>
Further work will try to demonstrate the potential use of predictability with site observations. This will help potential users answer questions like: what can they expect on the use of wind forecast at different time horizons? How predictable the wind resource is at the site of interest? This information will be synthetized in the form of comprehensive maps of predictability skills over Europe so it can be used for spatial planning of wind energy development.</p>
https://doi.org/10.5281/zenodo.1194705
oai:zenodo.org:1194705
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.1194704
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, predictability, probabilistic, forecasting, seasonal, decadal, sub-seasonal
Description of the predictability assessment methodology
info:eu-repo/semantics/report
oai:zenodo.org:3233367
2020-01-20T15:24:56Z
user-wind_energy
user-newa
Sanz Rodrigo, Javier
Chávez Arroyo, Roberto A.
Dörenkämper, Martin
Arnqvist, Johan
2018-07-05
<p>This report summarizes the second round of benchmarks conducted under the NEWA validation strategy. This report is the second of a series of three annual reports on NEWA benchmarks.</p>
<p>The <strong>first round</strong> of microscale benchmarks was directed to developing microscale models that can be driven with mesoscale input forcing, include thermal stratification of the atmospheric boundary layer and high resolution digital models of heterogeneous forest canopy characteristics based on aerial lidar-scan data. These fundamental implementations were developed around the GABLS3 diurnal-cycle and Ryningsnäs forest canopy benchmarks, both in flat terrain conditions. By model intercomparison, NEWA modelers found reasonably good consistency in the simulation of these cases, establishing common understanding of the modeling capabilities of the group before attempting more complex simulation challenges in connection to the NEWA experiments.</p>
<p>The first release of the NEWA model chain is produced based on this first round of benchmarks. CFDWind3 is published open-access to engage with early adopters that can help testing and eventually developing new functionalities alongside the NEWA validation plans. </p>
<p>The <strong>second round</strong> of benchmarks has been focused on the following objectives:</p>
<ul>
<li>Validation of flow models from flat to <strong>hilly forested terrain</strong>: Experimental data from the Rödeser Berg and Hornamossen experiments add terrain complexity to the baseline settings used in GABLS3 and Ryningsnäs. Following the Ryningsnäs approach, a blind test addressing steady-state models was organized around the Rödeser Berg forested hill benchmark. On the other hand, Hornamossen followed the GABLS3 approach to challenge transient models in the simulation of diurnal cycles on an undulated forested landscape.</li>
<li>Assessment of <strong>annual wind conditions</strong> relevant for wind resource assessment and site suitability. The “NEWA Meso-Micro Challenge for Wind Resource Assessment” addresses the evaluation of a hierarchy of methodologies that incorporate mesoscale-to-microscale downscaling to understand the added-value compared to traditional approaches for site assessment that rely only on microscale modeling. This challenge is divided in two phases: the first one in flat terrain and the second one in complex terrain conditions. This report summarizes results for the first phase based on Cabauw and Fino1 sites in onshore and offshore conditions.</li>
<li>Development of an <strong>open-science benchmarking</strong> approach: the benchmarking process established in GABLS3 is rolled out in the next benchmarks to promote a more traceable model evaluation based on sharing of simulation data and evaluation scripts. </li>
</ul>
<p>This report presents benchmark guides for Rödeser Berg, Hornamossen and the NEWA Meso-Micro Challenge and initial results published for the first phase of the Challenge. </p>
<p>The third round of benchmarks will exploit experimental data in complex terrain in terms of flow cases targeting the validation of specific modeling features, as well as case studies that integrate these models in wind resource assessment methodologies to assess the impact of those features in terms of relevant quantities of interest for the wind industry (annual energy prediction, site assessment characteristics, mean profiles, etc).</p>
https://doi.org/10.5281/zenodo.3233367
oai:zenodo.org:3233367
eng
Zenodo
https://doi.org/10.1088/1742-6596/1037/7/072030
https://github.com/windbench/NEWAMesoMicroChallengePhase1
https://b2share.eudat.eu/records/87904b9740cf4defaca8a16070670ead
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.3233366
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy
wind resource assessment
validation
complex terrain
forest canopy
Report on Second Round of Benchmarks
info:eu-repo/semantics/report
oai:zenodo.org:3382572
2020-01-20T17:42:39Z
user-newa
F. Gonzalez Rouco
E. García Bustamante
A. N. Hahmann
I. Karagili
J. Navarro
B. Tobias Olsen
T. Sïle
B. Witha
2019-08-31
<p>This report explores the quantification of uncertainty in the NEWA project. Uncertainty is un- derstood here as the result of the contributions of model sensitivity to different model setups, and of model errors in a model-data comparison framework. The first part (Sec 3 of this report ex- plores the uncertainty derived from model sensitivity subjected to the decisions taken regarding the use of different models setups and how these produce variability in model output. The range of this variability has been regarded as spread in model output and has been quantified in various manners. The second part of this report (Sec. 4 addresses how model performance can be char- acterised with the data at hand and whether decisions regarding selection of a given model setup for a production run can be taken on the basis of model performance in a variety of situations, using different variables and datasets as observational targets: wind farm data from Vestas; tall masts and wind profiles; surface wind data; satellite data and reanalysis outputs.</p>
https://doi.org/10.5281/zenodo.3382572
oai:zenodo.org:3382572
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.3382571
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
NEWA uncertainty evaluation, model error, model spread, model-data comparison
Report on uncertainty quantification (Deliverable D4.4)
info:eu-repo/semantics/report
oai:zenodo.org:2686566
2020-01-20T17:40:27Z
user-wind_energy
openaire
user-newa
Matias Avila
Roberto Chávez
Hugo Olivares
Johan Arnqvist
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. The Ryningsnän experiment in forested terrain is used to define a case study for testing atmospheric boundary layer models in forest canopies during diurnal cycles. A technique is presented based on prescribing net radiative heat flux balance at the top of the canopy, instead of surface temperature, and use geostrophic pressure gradient to drive the simulation. The results are reasonably good showing promise for further implementation in complex terrain sites.</p>
https://doi.org/10.5281/zenodo.2686566
oai:zenodo.org:2686566
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2686565
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource
atmospheric boundary layer
forest canopy
URANS
A coupling strategy to run daily cycle simulations of thermally stratified flows over forests
info:eu-repo/semantics/lecture
oai:zenodo.org:2685951
2020-01-20T15:49:16Z
user-wind_energy
openaire
user-newa
Vladislavs Bezrukovs
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. The use of stationary cellular communication masts for wind speed measurements provides a valid option for significantly reducing the time and material resources required to study the potential of wind energy at the height of up to 100 meters above ground level. This study show how to set up wind assessment campaigns using these masts and the how to account for directional-dependent flow distortion due to the presence of the tower.</p>
https://doi.org/10.5281/zenodo.2685951
oai:zenodo.org:2685951
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2685950
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource
cellular communication mast
flow distortion
Reducing uncertainty of wind speed measurements obtained on lattice cellular communication masts
info:eu-repo/semantics/lecture
oai:zenodo.org:1194686
2020-01-20T16:47:23Z
user-wind_energy
user-newa
Hahmann, Andrea N.
Witha, Björn
Rife, Daran
Frouzakis, Nikolaos
Junk, Constantin
Sile, Tija
Baltscheffsky, Magnus
Dörenkämper, Martin
Ezber, Yasemin
García Bustamante, Elena
González-Rouco, Fidel
Mentes, Sibel
Navarro, Jorge
Söderberg, Stefan
Unal, Yurdanur
2017-07-21
<p>A new ensemble method is explored for estimating the uncertainty of the wind resource within Weather Research and Forecasting (WRF) model simulations. The output of the ensemble simulations is processed to create a "map" showing the uncertainty in the wind resource estimate at each geographic location. This new method is demonstrated by performing a collection of 9 different WRF model simulations using combinations of 3 planetary boundary layer schemes, 2 simulation re-initialization strategies, and 2 methods for initializing the land surface state. The results of the simulations are validated against data from 10 meteorological masts in South Africa, part of the Wind Atlas of South Africa (WASA) project, where a long-term set of high-quality observations exist. The results of the ensemble simulations are encouraging, but further analysis is needed to quantify their utility. A key disadvantage of the ensemble simulation strategy employed herein, is that some members may tend to be highly similar to others, leading to overconfidence in the mean and spread of the simulations. Such overconfidence yields misleading estimates of the accuracy, value, and uncertainty of the wind resource.<br>
The results show that we need to develop a method to determine whether any given set of ensemble simulations are statistically distinct (i.e., each simulation provides unique information). Statistically similar ensemble members provide redundant information, falsely increase confidence, and thus should be removed from the set. The next step is also to identify potential statistical techniques (e.g., machine learning) to optimally combine the results from the various ensemble members into a single wind resource map.<br>
We further describe a set of WRF sensitivity simulations for five domains in Europe. These simulations were carried out to determine a few fundamental settings and strategies that are known to have the largest impact on the wind resource. The results of the simulations show consistent systematic differences among the simulations in the various domains.</p>
<p>This report also introduces and explores the applicability of the Analog Ensemble (AnEn) approach, another method to generate uncertainty information of the wind resource. Test results show that the AnEn is well-suited for estimating the long-term wind resource at target sites based on short-term measurements and historical reanalysis model data. A further benefit is that the AnEn technique adds uncertainty information to the long-term wind resource. Preliminary tests with mesoscale model data instead of observations show that the AnEn method could be applied to extend the high-resolution mesoscale wind atlas data set and to provide uncertainty information for the wind atlas data.</p>
https://doi.org/10.5281/zenodo.1194686
oai:zenodo.org:1194686
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.1194685
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, external conditions, mesoscale, probabilistic
Description of the Probabilistic Wind Atlas Methodology
info:eu-repo/semantics/report
oai:zenodo.org:3332646
2020-01-20T16:03:41Z
user-wind_energy
user-newa
Sanz Rodrigo, Javier
Chávez Arroyo, Roberto Aurelio
Gottschall, Julia
Dörenkämper, Martin
Witha, Björn
2019-05-30
<p>This report summarizes the third round of benchmarks conducted under the NEWA validation strategy <a href="https://doi.org/10.5281/zenodo.1194744">[1]</a>.</p>
<p>The <strong>first round</strong> of microscale benchmarks <a href="https://doi.org/10.5281/zenodo.1194717">[2]</a> was directed to developing microscale models that can be driven with mesoscale input forcing, include thermal stratification of the atmospheric boundary layer and high resolution digital models of heterogeneous forest canopy characteristics based on aerial lidar-scan data. These fundamental implementations were developed around the GABLS3 diurnal-cycle and Ryningsnäs forest canopy benchmarks, both in flat terrain conditions. By model intercomparison, NEWA modelers found reasonably good consistency in the simulation of these cases, establishing common understanding of the modeling capabilities of the group before attempting more complex simulation challenges in connection to the NEWA experiments.</p>
<p>The <strong>second round</strong> of benchmarks <a href="https://doi.org/10.5281/zenodo.3233367">[3]</a> focused on flow modeling over forested terrain based on the Rödeser Berg and Hornamossen experiments to add terrain complexity to the baseline settings used in GABLS3 and Ryningsnäs. A follow-up benchmark from GABLS3, based at the Cabauw tower, served to launch the “NEWA Meso-Micro Challenge for Wind Resource Assessment” to address the evaluation of a hierarchy of methodologies that incorporate mesoscale-to-microscale downscaling and understand the added-value compared to traditional approaches for site assessment that rely only on microscale modeling.</p>
<p>The <strong>third round</strong> continues with the second phase of the challenge in complex terrain, starting with Rödeser Berg. Following the NEWA validation strategy the benchmarks will be directed to flow cases targeting the validation of specific phenomena, as well as case studies that integrate these models in wind resource assessment methodologies to assess the impact on relevant quantities of interest for the wind industry such as annual energy prediction, site assessment characteristics, mean profiles, etc.</p>
<p>Additionally, the Ferry Lidar benchmark was launched to test mesoscale models predicting the wind profile along a ship track in the Southern Baltic Sea. </p>
<p>With the NEWA project concluded, the meso-micro challenge will continue in the frame of the <strong>IEA-Wind Task 31 “Wakebench”</strong> as new benchmarks are generated from the database of experiments <a href="https://community.ieawind.org/task31/home">[4]</a>.</p>
https://doi.org/10.5281/zenodo.3332646
oai:zenodo.org:3332646
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.3332645
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy
wind resource assessment
validation
benchmark
Report on Third Round of Benchmarks
info:eu-repo/semantics/report
oai:zenodo.org:2635548
2020-01-20T16:31:03Z
openaire
user-newa
Witha, Björn
Hahmann, Andrea
Sile, Tija
Barcons, Jordi
Davis, Neil
Dörenkämper, Martin
Ezber, Yasemin
García-Bustamante, Elena
González-Rouco, Fidel
Leroy, Grégoire
Navarro, Jorge
Olsen, Bjarke Tobias
Sastre, Mariano
Söderberg, Stefan
Trei, Wilke
2019-04-10
<p>A central part of the New European Wind Atlas (NEWA) is the generation of a mesoscale wind atlas which is based on 30 years of simulations with the WRF (Weather Research and Forecast) model. The atlas will cover all EU countries (plus Norway, Switzerland, the Balkans and Turkey) and associated offshore areas up to 100 km off the coast including the complete North and Baltic Seas.</p>
<p>The first part of the presentation gives an overview of the work that was done to prepare the mesoscale wind atlas production runs. To arrive at a final model configuration for the production run, a large ensemble of nearly 50 WRF simulations with different model setups was performed. The parameters tested in the ensemble members include, among others: model version, atmospheric and sea surface temperature input, land surface model as well as surface and PBL parameterisations. Information from the ensemble runs will also be used to provide uncertainty information to the wind atlas.</p>
<p>After presenting the final setup of the production runs, some information is given about the management of the production runs, which were performed on the Tier-0 supercomputer MareNostrum. Finally, results from the production runs are shown.</p>
https://doi.org/10.5281/zenodo.2635548
oai:zenodo.org:2635548
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.2635547
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind atlas
mesoscale
WRF
ensemble
The NEWA Mesoscale Wind Atlas: production and ensemble runs
info:eu-repo/semantics/lecture
oai:zenodo.org:3233510
2020-01-20T15:34:28Z
openaire
user-newa
Björn Witha
Tija Sile
Martin Dörenkämper
Jorge Navarro
Elena Garcia Bustamante
Fidel Gonzalez-Rouco
Yasemin Ezber
Andrea N. Hahmann
2019-05-28
<p>Presentation at the EGU 2019, Vienna April 2019.</p>
https://doi.org/10.5281/zenodo.3233510
oai:zenodo.org:3233510
eng
Zenodo
https://zenodo.org/communities/newa
https://doi.org/10.5281/zenodo.3233509
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Mesoscale modeling
WRF
wind resource assessment
The mesoscale production and ensemble simulations for the New European Wind Atlas
info:eu-repo/semantics/lecture
oai:zenodo.org:2643230
2020-01-20T17:42:56Z
user-wind_energy
openaire
user-newa
Javier Sanz Rodrigo
2019-04-02
<p>This presentation was done at the NEWA Final Workshop in April 2019. It presents a summary of the research activities related to the development of the NEWA model chain, which has two branches: one dedicated to the production of the wind atlas, based on the WRF model and statistical downscaling with the WAsP methodology, and another one focused on site assessment tools, based on dynamic downscaling with a variety of computational fluid dynamic (CFD) codes, using both Reynolds-Averaged Navier Stokes (URANS) and Large-Eddy Simulation (LES) turbulence modeling. Alongside model development activities a formal verification and validation (V&V) strategy was implemented, following the IEA Task 31 Wakebench framework, to leverage the experimental database of the project. An open-source model chain based on WRF and OpenFOAM has been released as reference for future model development and validation activities in connection to wind assessment best practices and standards.</p>
https://doi.org/10.5281/zenodo.2643230
oai:zenodo.org:2643230
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2643229
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy
wind resource
validation
mesoscale
microscale
open-source
NEWA Model-Chain and Validation Building-Blocks for Wind Conditions
info:eu-repo/semantics/lecture
oai:zenodo.org:1194765
2020-01-20T17:32:02Z
user-wind_energy
openaire
user-newa
user-eu
Sanz Rodrigo, Javier
Gancarski, Pawel
Chávez Arroyo, Roberto Aurelio
2017-06-27
<p>The Windbench portal for wind energy verification and validation (V&V) repositories is being redesigned, using an Open Science approach, with the objective of improving data openness and reproducibility of research. Windbench manages V&V benchmarking by allowing researchers to meet online and share their data for model intercomparison. The portal follows the IEA Task 31 "Wakebench" model evaluation protocol 2 for wind farm flow modelling based on a building-block validation approach that allows to systematically evaluate the wind farm multi-scale system by decomposing it in a number of sub-system and unitary building blocks of increasing<br>
complexity.<br>
The new portal integrates Jupyter notebooks in the cloud to allow researchers run their scripts for post-processing and model evaluation using their own data or data shared by other benchmark participants. These notebooks allow researchers to create and share documents that contain text, equations and visualization of results together with the code that generates these results. This improves reproducibility and provides better means for the community to adopt model evaluation standards by reusing contributions from previous benchmarks in terms of, for instance, data filtering and post-processing scripts, error metrics, visualization tools,<br>
etc.<br>
The GABLS3 diurnal cycle benchmark 3,4 for mesoscale to microscale atmospheric boundary layer models is used as case study to demonstrate the benefits of the open science approach in the Wakebench V&V framework. The benchmark has been organized within the New European Wind Atlas (NEWA) project to help microscale model developers implement solutions for introducing mesoscale forcings (that could be extracted from a wind atlas). The case is also used to explain how V&V benchmarks contribute to open source community models like CFDWind 3.0, based on OpenFOAM and developed for the NEWA model-chain.</p>
https://doi.org/10.5281/zenodo.1194765
oai:zenodo.org:1194765
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1194764
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy, wind resource assessment, open science, GABLS3, jupyter, validation, windbench, wakebench
An Open Science Approach for Wind Energy V&V: The GABLS3 Case Study
info:eu-repo/semantics/lecture
oai:zenodo.org:2684818
2020-01-20T17:16:54Z
user-wind_energy
openaire
user-newa
Jakob Mann
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao with an overview that summarizes some of the most important highlights of the project.</p>
https://doi.org/10.5281/zenodo.2684818
oai:zenodo.org:2684818
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2684817
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind energy
wind resource
wind atlas
LIDAR
CFD
mesoscale
boundary-layer meteorology
Overview of the New European Wind Atlas Project
info:eu-repo/semantics/lecture
oai:zenodo.org:2686514
2020-01-20T17:14:06Z
user-wind_energy
openaire
user-newa
Johan Arnqvist
Hugo Olivares
Stefan Ivanell
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. The Ryningsnäs atmospheric boundary-layer experiment in a Swedish forested landscape is used to set up a benchmark for wind energy flow models to simulate the flow above a forest canopy that is characterized using aerial laser scans. The footprint characteristics of the canopy are visible in the profiles. The benchmark includes results from RANS and LES models showing good consistency in the mean velocity profiles and less agreement in TKE profiles. </p>
https://doi.org/10.5281/zenodo.2686514
oai:zenodo.org:2686514
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2686513
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource
boundary-layer meteorology
forest canopy
RANS
LES
validation
Measurement and modeling of forested areas – best practice from a NEWA benchmark
info:eu-repo/semantics/lecture
oai:zenodo.org:2686092
2020-01-20T17:42:38Z
user-wind_energy
openaire
user-newa
Martin Dörenkämper
Bernhard Stoevesandt
Tobias Klaas
Paul Kühn
2019-04-02
<p>Presentation at the NEWA Final Workshop in Bilbao. The Rödeser Berg forested hill experiment near Kassel is presented leading to two rounds of blind tests for wind flow models in different stability conditions. A follow up benchmark is underway related to the assessment of annual energy production (AEP). </p>
https://doi.org/10.5281/zenodo.2686092
oai:zenodo.org:2686092
eng
Zenodo
https://zenodo.org/communities/newa
https://zenodo.org/communities/wind_energy
https://doi.org/10.5281/zenodo.2686091
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
wind resource
canopy
LIDAR
AEP
validation
Benchmarking of microscale models: the Kassel blind test
info:eu-repo/semantics/lecture