scholarly journals Estimation of Weibull parameters in wind speed mixture using nonlinear optimization for wind energy applications

2020 ◽  
Vol 18 ◽  
pp. 351-355
Author(s):  
Francisco M. Arrabal-Campos ◽  
◽  
Francisco G. Montoya ◽  
Alfredo Alcayde ◽  
Raúl Baños ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Nonlinear Optimization ◽  
Weibull Parameters ◽  
Energy Applications

scholarly journals Large-eddy simulation sensitivities to variations of configuration and forcing parameters in canonical boundary-layer flows for wind energy applications

2018 ◽  
Vol 3 (2) ◽  
pp. 589-613 ◽  
Author(s):  
Jeffrey D. Mirocha ◽  
Matthew J. Churchfield ◽  
Domingo Muñoz-Esparza ◽  
Raj K. Rai ◽  
Yan Feng ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Energy ◽  
Physical Factors ◽  
Convective Conditions ◽  
Measurement Variability ◽  
Energy Applications ◽  
Model Configuration ◽  
Large Eddy ◽  
Quantities Of Interest

Abstract. The sensitivities of idealized large-eddy simulations (LESs) to variations of model configuration and forcing parameters on quantities of interest to wind power applications are examined. Simulated wind speed, turbulent fluxes, spectra and cospectra are assessed in relation to variations in two physical factors, geostrophic wind speed and surface roughness length, and several model configuration choices, including mesh size and grid aspect ratio, turbulence model, and numerical discretization schemes, in three different code bases. Two case studies representing nearly steady neutral and convective atmospheric boundary layer (ABL) flow conditions over nearly flat and homogeneous terrain were used to force and assess idealized LESs, using periodic lateral boundary conditions. Comparison with fast-response velocity measurements at 10 heights within the lowest 100 m indicates that most model configurations performed similarly overall, with differences between observed and predicted wind speed generally smaller than measurement variability. Simulations of convective conditions produced turbulence quantities and spectra that matched the observations well, while those of neutral simulations produced good predictions of stress, but smaller than observed magnitudes of turbulence kinetic energy, likely due to tower wakes influencing the measurements. While sensitivities to model configuration choices and variability in forcing can be considerable, idealized LESs are shown to reliably reproduce quantities of interest to wind energy applications within the lower ABL during quasi-ideal, nearly steady neutral and convective conditions over nearly flat and homogeneous terrain.

scholarly journals Evaluation of wind speed estimates in reanalyses for wind energy applications

2021 ◽  
Vol 18 ◽  
pp. 115-126
Author(s):  
Sebastian Brune ◽  
Jan D. Keller ◽  
Sabrina Wahl
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Surface Characteristics ◽  
Horizontal Resolution ◽  
Hilly Terrain ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Energy Applications ◽  
Spatio Temporal ◽  
Regional Reanalysis

Abstract. A correct spatio-temporal representation of retrospective wind speed estimates is of large interest for the wind energy sector. In this respect, reanalyses provide an invaluable source of information. However, the quality of the various reanalysis estimates for wind speed are difficult to assess. Therefore, this study compares wind measurements at hub heights from 14 locations in Central Europe with two global (ERA5, MERRA-2) and one regional reanalysis (COSMO-REA6). Employing metrics such as bias, RMSE and correlation, we evaluate the performance of the reanalyses with respect to (a) the local surface characteristics (offshore, flat onshore, hilly onshore), (b) various height levels (60 to 200 m) and (c) the diurnal cycle. As expected, we find that the reanalyses show the smallest errors to observations at offshore sites. Over land, MERRA-2 generally overestimates wind speeds, while COSMO-REA6 and ERA5 represent the average wind speed more realistically. At sites with flat terrain, ERA5 correlates better with observations than COSMO-REA6. In contrast, COSMO-REA6 performs slightly better over hilly terrain, which can be explained by the higher horizontal resolution. In terms of diurnal variation, ERA5 outperforms both other reanalyses. While the overestimation of MERRA-2 is consistent throughout the day, COSMO-REA6 significantly underestimates wind speed at night over flat and hilly terrain due to a misrepresentation of nightly low level jets and mountain and valley breezes. Regarding the representation of downtime of wind turbines due to low/high wind speeds, we find that MERRA-2 is consistently underperforming with respect to the other reanalyses. Here COSMO-REA6 performs better over the ocean, while ERA5 shows the best results over land.

scholarly journals A methodology for the design and testing of atmospheric boundary layer models for wind energy applications

2017 ◽  
Vol 2 (1) ◽  
pp. 35-54 ◽  
Author(s):  
Javier Sanz Rodrigo ◽  
Matthew Churchfield ◽  
Branko Kosovic
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Energy ◽  
Atmospheric Boundary Layer ◽  
Wind Direction ◽  
Added Value ◽  
Mean Flow ◽  
Energy Applications ◽  
Single Column ◽  
Design And Testing

Abstract. The GEWEX Atmospheric Boundary Layer Studies (GABLS) 1, 2 and 3 are used to develop a methodology for the design and testing of Reynolds-averaged Navier–Stokes (RANS) atmospheric boundary layer (ABL) models for wind energy applications. The first two GABLS cases are based on idealized boundary conditions and are suitable for verification purposes by comparing with results from higher-fidelity models based on large-eddy simulation. Results from three single-column RANS models, of 1st, 1.5th and 2nd turbulence closure order, show high consistency in predicting the mean flow. The third GABLS case is suitable for the study of these ABL models under realistic forcing such that validation versus observations from the Cabauw meteorological tower are possible. The case consists on a diurnal cycle that leads to a nocturnal low-level jet and addresses fundamental questions related to the definition of the large-scale forcing, the interaction of the ABL with the surface and the evaluation of model results with observations. The simulations are evaluated in terms of surface-layer fluxes and wind energy quantities of interest: rotor equivalent wind speed, hub-height wind direction, wind speed shear and wind direction veer. The characterization of mesoscale forcing is based on spatially and temporally averaged momentum budget terms from Weather Research and Forecasting (WRF) simulations. These mesoscale tendencies are used to drive single-column models, which were verified previously in the first two GABLS cases, to first demonstrate that they can produce similar wind profile characteristics to the WRF simulations even though the physics are more simplified. The added value of incorporating different forcing mechanisms into microscale models is quantified by systematically removing forcing terms in the momentum and heat equations. This mesoscale-to-microscale modeling approach is affected, to a large extent, by the input uncertainties of the mesoscale tendencies. Deviations from the profile observations are reduced by introducing observational nudging based on measurements that are typically available from wind energy campaigns. This allows the discussion of the added value of using remote sensing instruments versus tower measurements in the assessment of wind profiles for tall wind turbines reaching heights of 200 m.

scholarly journals Estimate wind speed in Ninewa province using Weppel parameters: تخمين سرع الرياح في محافظة نينوى باستخدام معلمات ويبل

2017 ◽  
Vol 1 (4) ◽  
Author(s):  
Waleed Asmair Al Rajbo, Faten Mohammed Hamam
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Coefficient Of Determination ◽  
Weibull Parameter ◽  
Energy Investment ◽  
Weibull Parameters ◽  
The Mean ◽  
Very High

The study and forecasting of wind speed is of great importance in weather phenomena, climate and wind energy investment for electricity and other uses. The aim of this paper is to estimate the mean monthly values of wind speed in five  Meteorological stations in Ninava Governorate (Mosul, Rabea ,Sin jar ,Talafar ,Baag) using weibull parameter . The estimated mean monthly values of wind speed using weibull parameters in all stations are nearly equal to the measured values. The coefficient of determination (R2 ) between the measured and estimated values in all stations are (0.997, 0.956, 0.995, 0.997, 0.994) . R2 between the measured and estimated values of wind speed in the whole Ninava Governorate is gives a very high value equal to ( 0.998) . This mean that the model is very accurate.

scholarly journals Large-Eddy Simulation Sensitivities to Variations of Configuration and Forcing Parameters in Canonical Boundary-Layer Flows for Wind Energy Applications

2017 ◽  
Author(s):  
Jeffrey D. Mirocha ◽  
Matthew J. Churchfield ◽  
Domingo Muñoz-Esparza ◽  
Raj K. Rai ◽  
Yan Feng ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Energy ◽  
Physical Factors ◽  
Convective Conditions ◽  
Measurement Variability ◽  
Energy Applications ◽  
Model Configuration ◽  
Large Eddy ◽  
Quantities Of Interest

Abstract. The sensitivities of idealized Large-Eddy Simulations (LES) to variations of model configuration and forcing parameters on quantities of interest to wind power applications are examined. Simulated wind speed, turbulent fluxes, spectra and cospectra are assessed in relation to variations of two physical factors, geostrophic wind speed and surface roughness length, and several model configuration choices, including mesh size and grid aspect ratio, turbulence model, and numerical discretization schemes, in three different code bases. Two case studies representing nearly steady neutral and convective atmospheric boundary layer (ABL) flow conditions over nearly flat and homogeneous terrain were used to force and assess idealized LES, using periodic lateral boundary conditions. Comparison with fast-response velocity measurements at five heights within the lowest 50 m indicates that most model configurations performed similarly overall, with differences between observed and predicted wind speed generally smaller than measurement variability. Simulations of convective conditions produced turbulence quantities and spectra that matched the observations well, while those of neutral simulations produced good predictions of stress, but smaller than observed magnitudes of turbulence kinetic energy, likely due to tower wakes influencing the measurements. While sensitivities to model configuration choices and variability in forcing can be considerable, idealized LES are shown to reliably reproduce quantities of interest to wind energy applications within the lower ABL during quasi-ideal, nearly steady neutral and convective conditions over nearly flat and homogeneous terrain.

scholarly journals A deep CNN model for medium-range spatio-temporal wind speed prediction for wind energy applications

2021 ◽  
Author(s):  
Daan Scheepens ◽  
Katerina Hlavackova-Schindler ◽  
Claudia Plant ◽  
Irene Schicker
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Velocity ◽  
Wind Farms ◽  
Relative Vorticity ◽  
Horizontal Wind ◽  
Energy Applications ◽  
Wind Speed Prediction ◽  
Speed Prediction ◽  
Deep Cnn

<p>The amount of wind farms and wind power production in Europe, on-shore and off-shore, increased rapidly in the past years. To ensure grid stability, omit fees in energy trading, and on-time (re)scheduling of maintenance tasks accurate predictions of wind speed and wind energy is needed. Especially for the prediction range of +48 hours up to 2 weeks ahead at least hourly predictions are envisioned by the users. However, these are either not covered by the high-resolution models or are on a spatial and temporal course scale. </p><p>To address this as a first step we therefore propose a deep CNN based model for wind speed prediction  using the ECMWF ERA5 to train our model using at least seven wind-related temporal variables, i.e. divergence, geopotential, potential vorticity, temperature, relative vorticity, vertical wind velocity and horizontal wind velocity.</p><p>The input of the CNN is represented by  the 3-dim tensor (size of the 2-dim figures x time shots), one for each variable. The CNN  outputs the most probable of the six categories in which the wind speed will be during the following 96 hours, in 6h intervals. Different combinations of input data are investigated in terms of temporal input.</p><p>We analyse the influence of prediction range on the predicted category as well as the relevance of each of the wind-related variables in the prediction of this category.  The model will be tested and applied to the ECMWF IFS forecasts over Austria. The ensure a higher spatial and temporal resolution an additional step will be used for downscaling the CNN directly to a 1 km grid.</p><p>This work is performed as part of the MEDEA project, which is funded by the Austrian Climate Research Program.</p>

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.

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