Wind resource assessment using numerical weather prediction models and multi-criteria decision making technique: case study (Masirah Island, Oman)

2013 ◽  
Vol 4 (1) ◽  
pp. 17 ◽  
Author(s):  
Sultan Al Yahyai ◽  
Yassine Charabi ◽  
Abdullah Al Badi ◽  
Adel Gastli
2015 ◽  
Vol 156 ◽  
pp. 528-541 ◽  
Author(s):  
Jie Zhang ◽  
Caroline Draxl ◽  
Thomas Hopson ◽  
Luca Delle Monache ◽  
Emilie Vanvyve ◽  
...  

Author(s):  
S. Jafari ◽  
T. Sommer ◽  
N. Chokani ◽  
R. S. Abhari

Prospecting for wind farm sites and pre-development studies of wind energy projects require knowledge of the wind energy resource over large areas (that is, areas of the order of 10’000 km2 and greater). One approach to detail this wind resource is the use of mesoscale numerical weather prediction models. In this paper, the mesoscale Weather Research and Forecasting (WRF) model is used to examine the effect of horizontal grid resolution on the fidelity of the predictions of the wind resource. The simulations are made for three test cases, Switzerland (land area 39’770 km2), Iowa (land area 145,743 km2) and Oregon (land area 248’647 km2), representing a range of terrain types, from complex terrain to flat terrain, over the period from 2006–2010. On the basis of comparisons to the data from meteorological masts and tall communication towers, guidelines are given for the horizontal grid required in the use of mesoscale models of large area wind resource assessment, especially over complex terrain.


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4169
Author(s):  
Giovanni Gualtieri

The reliability of ERA5 reanalyses for directly predicting wind resources and energy production has been assessed against observations from six tall towers installed over very heterogeneous sites around the world. Scores were acceptable at the FINO3 (Germany) offshore platform for both wind speed (bias within 1%, r = 0.95−0.96) and capacity factor (CF, at worst biased by 6.70%) and at the flat and sea-level site of Cabauw (Netherlands) for both wind speed (bias within 7%, r = 0.93−0.94) and CF (bias within 6.82%). Conversely, due to the ERA5 limited resolution (~31 km), large under-predictions were found at the Boulder (US) and Ghoroghchi (Iran) mountain sites, and large over-predictions were found at the Wallaby Creek (Australia) forested site. Therefore, using ERA5 in place of higher-resolution regional reanalysis products or numerical weather prediction models should be avoided when addressing sites with high variation of topography and, in particular, land use. ERA5 scores at the Humansdorp (South Africa) coastal location were generally acceptable, at least for wind speed (bias of 14%, r = 0.84) if not for CF (biased by 20.84%). However, due to the inherent sea–land discontinuity resulting in large differences in both surface roughness and solar irradiation (and thus stability conditions), a particular caution should be paid when applying ERA5 over coastal locations.


Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 89
Author(s):  
Harel. B. Muskatel ◽  
Ulrich Blahak ◽  
Pavel Khain ◽  
Yoav Levi ◽  
Qiang Fu

Parametrization of radiation transfer through clouds is an important factor in the ability of Numerical Weather Prediction models to correctly describe the weather evolution. Here we present a practical parameterization of both liquid droplets and ice optical properties in the longwave and shortwave radiation. An advanced spectral averaging method is used to calculate the extinction coefficient, single scattering albedo, forward scattered fraction and asymmetry factor (bext, v, f, g), taking into account the nonlinear effects of light attenuation in the spectral averaging. An ensemble of particle size distributions was used for the ice optical properties calculations, which enables the effective size range to be extended up to 570 μm and thus be applicable for larger hydrometeor categories such as snow, graupel, and rain. The new parameterization was applied both in the COSMO limited-area model and in ICON global model and was evaluated by using the COSMO model to simulate stratiform ice and water clouds. Numerical weather prediction models usually determine the asymmetry factor as a function of effective size. For the first time in an operational numerical weather prediction (NWP) model, the asymmetry factor is parametrized as a function of aspect ratio. The method is generalized and is available on-line to be readily applied to any optical properties dataset and spectral intervals of a wide range of radiation transfer models and applications.


Sign in / Sign up

Export Citation Format

Share Document