scholarly journals Editorial for the Special Issue “Remote Sensing of Atmospheric Conditions for Wind Energy Applications”

2019 ◽  
Vol 11 (7) ◽  
pp. 781 ◽  
Author(s):  
Charlotte Hasager ◽  
Mikael Sjöholm
Keyword(s):  
Remote Sensing ◽  
Wind Energy ◽  
Wind Farm ◽  
Doppler Radar ◽  
Doppler Lidar ◽  
Atmospheric Conditions ◽  
Special Issue ◽  
Energy Applications ◽  
Wind Turbine Control ◽  
Wind Lidar

This Special Issue hosts papers on aspects of remote sensing for atmospheric conditions for wind energy applications. The wind lidar technology is presented from a theoretical view on the coherent focused Doppler lidar principles. Furthermore, wind lidar for applied use for wind turbine control, wind farm wake, and gust characterizations are presented, as well as methods to reduce uncertainty when using lidar in complex terrain. Wind lidar observations are used to validate numerical model results. Wind Doppler lidar mounted on aircraft used for observing winds in hurricane conditions and Doppler radar on the ground used for very short-term wind forecasting are presented. For the offshore environment, floating lidar data processing is presented as well as an experiment with wind-profiling lidar on a ferry for model validation. Assessments of wind resources in the coastal zone using wind-profiling lidar and global wind maps using satellite data are presented.

scholarly journals Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 712 ◽  
Author(s):  
Ines Würth ◽  
Laura Valldecabres ◽  
Elliot Simon ◽  
Corinna Möhrlen ◽  
Bahri Uzunoğlu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Wind Energy ◽  
Wind Power ◽  
Wind Farm ◽  
Power Grid ◽  
Measurement Data ◽  
Physical Models ◽  
Energy Applications ◽  
Short Term Forecasting ◽  
Grid Operators

The demand for minute-scale forecasts of wind power is continuously increasing with the growing penetration of renewable energy into the power grid, as grid operators need to ensure grid stability in the presence of variable power generation. For this reason, IEA Wind Tasks 32 and 36 together organized a workshop on “Very Short-Term Forecasting of Wind Power” in 2018 to discuss different approaches for the implementation of minute-scale forecasts into the power industry. IEA Wind is an international platform for the research community and industry. Task 32 tries to identify and mitigate barriers to the use of lidars in wind energy applications, while IEA Wind Task 36 focuses on improving the value of wind energy forecasts to the wind energy industry. The workshop identified three applications that need minute-scale forecasts: (1) wind turbine and wind farm control, (2) power grid balancing, (3) energy trading and ancillary services. The forecasting horizons for these applications range from around 1 s for turbine control to 60 min for energy market and grid control applications. The methods that can be applied to generate minute-scale forecasts rely on upstream data from remote sensing devices such as scanning lidars or radars, or are based on point measurements from met masts, turbines or profiling remote sensing devices. Upstream data needs to be propagated with advection models and point measurements can either be used in statistical time series models or assimilated into physical models. All methods have advantages but also shortcomings. The workshop’s main conclusions were that there is a need for further investigations into the minute-scale forecasting methods for different use cases, and a cross-disciplinary exchange of different method experts should be established. Additionally, more efforts should be directed towards enhancing quality and reliability of the input measurement data.

scholarly journals Turbulent kinetic energy estimates from profiling wind LiDAR measurements and their potential for wind energy applications

2016 ◽  
Vol 99 ◽  
pp. 898-910 ◽  
Author(s):  
Valerie-M. Kumer ◽  
Joachim Reuder ◽  
Manfred Dorninger ◽  
Rudolf Zauner ◽  
Vanda Grubišić
Keyword(s):  
Kinetic Energy ◽  
Wind Energy ◽  
Turbulent Kinetic Energy ◽  
Energy Estimates ◽  
Energy Applications ◽  
Lidar Measurements ◽  
Wind Lidar

Remote sensing of the nocturnal boundary layer for wind energy applications.

2008 ◽  
Vol 1 ◽  
pp. 012048
Author(s):  
Y L Pichugina ◽  
R M Banta ◽  
N D Kelley ◽  
W A Brewer ◽  
S P Sandberg ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Wind Energy ◽  
Nocturnal Boundary Layer ◽  
Energy Applications

Wind Shear Assessment Using Wind LiDAR Profiler and Sonic 3D Anemometer for Wind Energy Applications—Preliminary Results

2015 ◽  
pp. 893-902 ◽  
Author(s):  
Yoshiaki Sakagami ◽  
Pedro A. A. Santos ◽  
Reinaldo Haas ◽  
Júlio C. Passos ◽  
Frederico F. Taves
Keyword(s):  
Wind Energy ◽  
Wind Shear ◽  
Preliminary Results ◽  
Energy Applications ◽  
Wind Lidar

Multi-site testing and evaluation of remote sensing instruments for wind energy applications

2013 ◽  
Vol 53 ◽  
pp. 200-210 ◽  
Author(s):  
J. Sanz Rodrigo ◽  
F. Borbón Guillén ◽  
P. Gómez Arranz ◽  
M.S. Courtney ◽  
R. Wagner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Wind Energy ◽  
Site Testing ◽  
Energy Applications ◽  
Testing And Evaluation

Design and evaluation of a short coherence length laser-based Doppler wind Lidar system for wind energy applications

2014 ◽  
Author(s):  
Leilei Shinohara ◽  
Julian Asche-Tauscher ◽  
Maik Fox ◽  
Thorsten Beuth ◽  
Wilhelm Stork
Keyword(s):  
Wind Energy ◽  
Coherence Length ◽  
Lidar System ◽  
Energy Applications ◽  
Wind Lidar ◽  
Doppler Wind Lidar

scholarly journals An intercomparison of mesoscale models at simple sites for wind energy applications

2017 ◽  
Vol 2 (1) ◽  
pp. 211-228 ◽  
Author(s):  
Bjarke T. Olsen ◽  
Andrea N. Hahmann ◽  
Anna Maria Sempreviva ◽  
Jake Badger ◽  
Hans E. Jørgensen
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Weather Prediction ◽  
Atmospheric Stability ◽  
Resource Assessment ◽  
Offshore Wind ◽  
Grid Spacing ◽  
Energy Applications ◽  
Wind Resource

Abstract. Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated using a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft (< 4 %) and larger biases closer to the surface over land (> 7 %). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction.

scholarly journals A new reference wind year approach to estimate long term wind characteristics

2021 ◽  
Vol 13 (5) ◽  
pp. 168781402110212
Author(s):  
Saban Pusat ◽  
Yasin Karagöz
Keyword(s):  
Wind Energy ◽  
Wind Farm ◽  
Building Energy ◽  
Energy Performance ◽  
Reference Station ◽  
Energy Applications ◽  
Wind Characteristics ◽  
Term Data

The typical meteorological year (TMY) method has common applications in building energy performance and solar energy studies. However, there is not any well accepted method for the wind energy applications such as the TMY. In the present study, a new reference year approach is proposed for wind energy applications. By using the proposed method, the reference wind year (RWY) datasets may be generated as in the TMY methodology for any measurement station which has the possibility to be used as a reference station in the measure-correlate-predict (MCP) analyses. The MCP calculations are so significant to estimate the long term wind conditions for a candidate wind farm site. In this study, a case study is performed for Turkey after giving the details of the proposed method. The results for the RWY approach has a good agreement with the long term data as in the TMY method. Therefore, the RWY concept has the possibility to make the MCP studies easier and faster.

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