Offshore wind resource assessment using reanalysis data

2022 ◽  
pp. 0309524X2110693
Author(s):  
Sajeer Ahmad ◽  
Muhammad Abdullah ◽  
Ammara Kanwal ◽  
Zia ul Rehman Tahir ◽  
Usama Bin Saeed ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Resource Assessment ◽  
Reanalysis Data ◽  
Measured Data ◽  
Offshore Wind ◽  
Technological Advancement ◽  
Wind Rose ◽  
Wind Resource Assessment ◽  
Wind Resource

The growth rate of offshore wind is increasing due to technological advancement and reduction in cost. An approach using mast measured data at coastline and reanalysis data is proposed for offshore wind resource assessment, especially for developing countries. The evaluation of fifth generation European Reanalysis (ERA5) data was performed against measured data using statistical analysis. ERA5 data slightly underestimates wind speed and wind direction with percentage bias of less than 1%. Wind resource assessment of region in Exclusive Economic Zone (EEZ) of Pakistan was performed in terms of wind speed and Wind Power Density (WPD). The range of monthly mean wind speed and WPD in the region was 4.03–8.67 m/second and 73–515 W/m2 respectively. Most-probable wind speed and dominating wind direction on corners and center of the region were found using probability distributions and wind rose diagrams respectively. Most-probable wind speed ranges 4.41–7.64 m/second and dominating wind direction is southwest.

Wind Resource Assessment for the Kingdom of Bahrain

2008 ◽  
Vol 32 (5) ◽  
pp. 439-448 ◽  
Author(s):  
Hanan Al Buflasa ◽  
David Infield ◽  
Simon Watson ◽  
Murray Thomson
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Resource Assessment ◽  
Measured Data ◽  
Shape Parameters ◽  
Main Island ◽  
Wind Resource Assessment ◽  
Mean Wind Speed ◽  
Wind Resource ◽  
Hourly Basis

The geographical distribution of wind speed (the wind atlas) for the kingdom of Bahrain is presented, based on measured data and on calculations undertaken using WAsP,. The data used were recorded by the Meteorological Directorate at a weather station situated at Bahrain International Airport, taken on an hourly basis for a period of time extended for ten years. These data indicate an annual mean wind speed of 4.6 m/s at 10 m height and mean Weibull scale and shape parameters C and k of 5.2 m/s and 1.9 respectively. At a typical wind turbine hub height of sixty metres, these values are extrapolated to 6.9 m/s, 7.8 m/s and 1.8 respectively, which suggests that the area has a good wind resource. The wind atlas shows that several locations in the less populated central and southern regions of the main island of the archipelago of Bahrain are potentially suitable for wind energy production.

scholarly journals Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison against Tall Towers

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4169
Author(s):  
Giovanni Gualtieri
Keyword(s):  
Wind Speed ◽  
Prediction Models ◽  
Weather Prediction ◽  
Resource Assessment ◽  
Reanalysis Data ◽  
Solar Irradiation ◽  
Wind Resource Assessment ◽  
Regional Reanalysis ◽  
Wind Resource ◽  
Wind Resources

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.

Assessment of Offshore Wind Resource in China Using CFSR Data

2014 ◽  
Vol 1070-1072 ◽  
pp. 303-308
Author(s):  
Shuang Long Jin ◽  
Shuang Lei Feng ◽  
Bo Wang ◽  
Ju Hu ◽  
Zhen Qiang Ma ◽  
...  
Keyword(s):  
Wind Power ◽  
Large Scale ◽  
Wind Farms ◽  
Resource Assessment ◽  
Reanalysis Data ◽  
Offshore Wind ◽  
Ground Vegetation ◽  
Observation Data ◽  
Wind Resource Assessment ◽  
Wind Resource

The offshore wind farms have many advantages over the onshore ones: they are not affected by the terrain, ground vegetation, buildings and other landscape features, so they have stronger and steadier wind, higher wind power density, smaller turbulence intensity and other advantages. Therefore, offshore wind power becomes the developing trends of wind power industry nowadays. However, its development faces the challenge of how to assess offshore wind resources accurately. It is difficult to get accurate, long-term, large-scale measured data on sea, and the nearshore observations cannot be substitute for the offshore wind conditions directly. This paper applies the NCEP CFSR reanalysis data (combines with the WMO marine observation data) to research the offshore wind resource assessment of China. We find that CFSR reanalysis data is consistent with the observation data, and it can provide a reference for China offshore wind resource assessment. The result of China offshore wind resource distribution is obtained finally.

A hybrid solution for offshore wind resource assessment from limited onshore measurements

2021 ◽  
Vol 298 ◽  
pp. 117245
Author(s):  
Basem Elshafei ◽  
Alfredo Peña ◽  
Dong Xu ◽  
Jie Ren ◽  
Jake Badger ◽  
...  
Keyword(s):  
Resource Assessment ◽  
Offshore Wind ◽  
Wind Resource Assessment ◽  
Hybrid Solution ◽  
Wind Resource

Offshore Wind Power Assessment on the East Coast of Saudi Arabia

2005 ◽  
Vol 29 (5) ◽  
pp. 409-419 ◽  
Author(s):  
Shafiqur Rehman
Keyword(s):  
Saudi Arabia ◽  
Wind Speed ◽  
Ghg Emissions ◽  
Resource Assessment ◽  
Offshore Wind ◽  
Energy Yield ◽  
North West ◽  
North East ◽  
Prevailing Wind Direction ◽  
Wind Resource

This paper, to the best of author's knowledge, presents the first wind resource assessment for offshore-wind energy off the mainland coasts of Saudi Arabia, despite the onshore wind resource being known. The study utilized wind speed data from, in effect, an offshore meteorological station to study the annual and seasonal variation of wind speed, wind speed frequency distribution, energy yield and consequent opportunity for reduction in green house gases (GHG) emissions. These results were compared with contemporaneous data from a mainland location ∼ 10 km inland at the same longitude Energy yields were calculated using HOMER and RetScreen models. The annual mean wind measured at Abu Ali Island, the offshore location, was 5.43 m/s. This is larger than the 4.9 m/s measured over the same period at Abu Kharuf, the nearby inland location. Larger wind speeds were found in winter months than in summer months at both locations. At Abu Ali Island, the power of the wind could be extracted for 75% of the time at hub-height of 60 meters using modern wind machines of cut-in-speed 4 m/s, in comparison with 60% of time at Abu Kharuf. The prevailing wind direction was found to be North (N), North West (NNW) and North East (NNE).

scholarly journals Inter-calibration of SAR data series for offshore wind resource assessment

2019 ◽  
Vol 232 ◽  
pp. 111316 ◽  
Author(s):  
Merete Badger ◽  
Tobias Ahsbahs ◽  
Petr Maule ◽  
Ioanna Karagali
Keyword(s):  
Resource Assessment ◽  
Offshore Wind ◽  
Data Series ◽  
Wind Resource Assessment ◽  
Sar Data ◽  
Wind Resource

On the wind resource in Algeria: Probability distributions evaluation

2020 ◽  
pp. 095765092097588
Author(s):  
Houdayfa Ounis ◽  
Nawel Aries
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Probability Distributions ◽  
Resource Assessment ◽  
Descriptive Statistics ◽  
The Other ◽  
Wind Speeds ◽  
Wind Resource Assessment ◽  
The Mean ◽  
Wind Resource

The present study aims to present a contribution to the wind resource assessment in Algeria using ERA-Interim reanalysis. Firstly, the ERA-Interim reanalysis 10 m wind speed data are considered for the elaboration of the mean annual 10 m wind speed map for a period starting from 01-01-2000 to 31-12-2017. Moreover, the present study intends to highlight the importance of the descriptive statistics other than the mean in wind resource assessment. On the other hand, this study aims also to select the proper probability distribution for the wind resource assessment in Algeria. Therefore, nine probability distributions were considered, namely: Weibull, Gamma, Inverse Gaussian, Log Normal, Gumbel, Generalized Extreme Value (GEV), Nakagami, Generalized Logistic and Pearson III. Furthermore, in combination with the distribution, three parameter estimation methods were considered, namely, Method of Moment, Maximum Likelihood Method and L-Moment Method. The study showed that Algeria has several wind behaviours due to the diversified topographic, geographic and climatic properties. Moreover, the annual mean 10 m wind speed map showed that the wind speed varies from 2.3 to 5.3 m/s, where 73% of the wind speeds are above 3 m/s. The map also showed that the Algerian Sahara is windiest region, while, the northern fringe envelopes the lowest wind speeds. In addition, it has been shown that the study of the mean wind speeds for the evaluation of the wind potential alone is not enough, and other descriptive statistics must be considered. On the other hand, among the nine considered distribution, it appears that the GEV is the most appropriate probability distribution. Whereas, the Weibull distribution showed its performance only in regions with high wind speeds, which, implies that this probability distribution should not be generalized in the study of the wind speed in Algeria.

scholarly journals Wind Speed using Improved Mixture Weibull Distribution

2019 ◽  
Vol 8 (6) ◽  
pp. 1871-1874
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Weibull Distribution ◽  
Wind Farms ◽  
Resource Assessment ◽  
Estimation Of Parameters ◽  
Basic Properties ◽  
Wind Resource Assessment ◽  
Proposed Model ◽  
Wind Resource

Wind is random in nature both in space and in time. Several technologies are used in wind resource assessment (WRA).The appropriate probability distribution used to calculate the available wind speed at that particular location and the estimation of parameters is the essential part in installing wind farms. The improved mixture Weibull distribution is proposed model which is the mixture of two and three parameter Weibull distribution with parameters including scale, shape, location and weight component. The basic properties of the proposed model and estimation of parameters using various methods are discussed.

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