scholarly journals Assessment of Offshore Wind Characteristics and Wind Energy Potential in Bohai Bay, China

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2879 ◽  
Author(s):  
Jianxing Yu ◽  
Yiqin Fu ◽  
Yang Yu ◽  
Shibo Wu ◽  
Yuanda Wu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Direction ◽  
Resource Assessment ◽  
Offshore Wind ◽  
Bohai Bay ◽  
Energy Potential ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
Wind Characteristics

Wind energy, one of the most sustainable renewable energy sources, has been extensively developed worldwide. However, owing to the strong regional and seasonal differences, it is necessary to first evaluate wind energy resources in detail. In this study, the offshore wind characteristics and wind energy potential of Bohai Bay (38.7° N, 118.7° E), China, were statistically analyzed using two-year offshore wind data with a time interval of one second. Furthermore, Nakagami and Rician distributions were used for wind energy resource assessment. The results show that the main wind direction in Bohai Bay is from the east (−15°–45°), with a speed below 12 m/s, mainly ranging from 4 to 8 m/s. The main wind speed ranges in April and October are higher than those in August and December. The night wind speed is generally higher than that in the daytime. The Nakagami and Rician distributions performed reasonably in calculating the wind speed distributions and potential assessments. However, Nakagami distribution provided better wind resource assessment in this region. The wind potential assessment results suggest that Bohai Bay could be considered as a wind class I region, with east as the dominant wind direction.

Investigation on offshore wind energy potential in Benin Republic

2019 ◽  
pp. 0309524X1987276 ◽  
Author(s):  
Maurel R Aza-Gnandji ◽  
François-Xavier Fifatin ◽  
Frédéric Dubas ◽  
Télesphore C Nounangnonhou ◽  
Christophe Espanet ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Wind Energy ◽  
Exclusive Economic Zone ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Energy Potential ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
Economic Zone ◽  
Benin Republic

This article presents a study on offshore wind energy viability in Benin Republic. Weibull law has been used to model the spatial distribution of daily wind speed data in Benin Republic’s Exclusive Economic Zone. The spatial distribution of wind energy potential in Benin’s exclusive economic zone has been obtained at several heights by extrapolating Weibull parameters. Wind resource has then been categorized using National Renewable Energy Laboratory standards. Bathymetric data in the exclusive economic zone are used to determine areas showing good compromise between exploitable wind potential and turbine’s foundation. We have shown that Benin’s offshore resources can reach Class 7 at 100 m height, Class 6, respectively, at 100 and 80 m heights and finally Class 5 at 50 m height. We have also shown that locations close to the shore are the most suitable to offshore wind power generation in Benin’s exclusive economic zone.

Spatiotemporal wind energy potential estimation and analysis in Japan

2021 ◽  
Author(s):  
Taichi Matsuoka ◽  
Tetsushi Amano ◽  
Remi Delage ◽  
Toshihiko Nakata
Keyword(s):  
Wind Energy ◽  
Power Output ◽  
Weather Forecast ◽  
Offshore Wind ◽  
Energy Potential ◽  
Temporal Smoothing ◽  
Wind Potential ◽  
Efficient Integration ◽  
Sustainable Energy Systems ◽  
Wind Energy Potential

<p>For an efficient integration of wind and solar resources toward sustainable energy systems, it is crucial to consider their fluctuations in space and time. Current spatial wind potential estimations in Japan are limited to the annual average of wind speed. In this study, we evaluate the spatial and temporal evolution of both onshore and offshore wind energy potential in Japan based on 5 km mesh and 1-hour sampling weather forecast data. We then demonstrate the benefits of cross-border sharing on the power output stability and identify important sites having high average potential and low average correlation with other sites for the temporal smoothing of power output.</p>

Assessment of Wind Energy Potential in Three Different Locations of Malaysia

2015 ◽  
Vol 785 ◽  
pp. 621-626
Author(s):  
R. Shamsipour ◽  
M. Fadaeenejad ◽  
M.A.M. Radzi
Keyword(s):  
Wind Speed ◽  
Energy Density ◽  
Wind Energy ◽  
Wind Power ◽  
Weibull Model ◽  
Energy Potential ◽  
Wind Speeds ◽  
Wind Potential ◽  
Mean Wind Speed ◽  
Wind Energy Potential

In this study, wind energy potential in three different stations in Malaysia in period of 5 years is analyzed. Base on Weibull distribution parameters, the mean wind speed, wind power density and wind energy density is estimated for each defined location. Although there are many works about wind potential in Malaysia, however a few of them have been provided a comprehensive study about wind power in different places in Malaysia. According to the findings, the annual mean wind speeds indicates that the highest wind speed variation is about 2 m/s and is belonged to the Subang station and the highest wind speed is 3.5 m/s in in Kudat. It is also found that the maximum wind power densities among these three sites are 22 W/m2, 24 W/m2 and 22 W/m2 in Kudat station in January, February and September respectively. The results of the study show that as the second parameter for Weibull model, the highest wind energy density has been 190 kWh/m2 per year in Kudat and the lowest one has been about 60 kWh/m2 in Kuching.

scholarly journals Assessment of the Wind Energy Potential along the Romanian Coastal Zone

Inventions ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 41
Author(s):  
Alina Girleanu ◽  
Florin Onea ◽  
Eugen Rusu
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Coastal Zone ◽  
In Situ Measurements ◽  
Reference Points ◽  
Offshore Wind ◽  
Time Interval ◽  
Energy Potential ◽  
Wind Energy Potential

The present work aims to provide a comprehensive picture of the wind energy potential that characterizes the Romanian coastal environment using in situ measurements and reanalysis of wind data (ERA5) that cover a 42–year time interval (1979–2020). A total of 16 reference points (both land and offshore) equally distributed along the Romanian sector are used to evaluate the local wind energy potential, targeting in this way several sites where a renewable wind project could be established. Compared to the in situ measurements (land points), the ERA5 dataset underestimates the wind speed by at least 11.57%, this value increasing as we approach the coastline. From the analysis of the spatial maps, it is likely that the wind speed steadily increases from onshore to offshore, with a sharp variation near the coastline being reported. Furthermore, the assessment of some state-of-the-art offshore wind turbines was conducted using 12 systems defined by rated capacity ranging from 2 to 10 MW. Some scenarios were proposed to identify sustainable offshore wind projects to be implemented in the Romanian coastal zone based on these results.

scholarly journals Application of GIS and Remote Sensing in Determining Trends in Wind Energy Potential and Its Uses for Designing Development Strategies in Ghana

2020 ◽  
Vol 3 (3) ◽  
pp. 1-10
Author(s):  
Nurideen Abdulai ◽  
Leslie Donkor ◽  
Dennis Asare
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Northern Ghana ◽  
Energy Potential ◽  
Weighted Interpolation ◽  
East Region ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
Upper East Region ◽  
Mechanized Agriculture

This paper is purported to determine the wind energy potential of Ghana for 2010 and 2018 using GIS and RS technologies and how the result could be used to develop a country strategy that benefits the ordinary Ghanaian. In doing this, two different wind potential maps of Ghana were generated for 2010 and 2018 using data from Ghana meteorological Unit and Windfinder respectively. Moreover, the Inverse Distance Weighted interpolation of winds peed was used to generate the maps at different hub heights for 2010 and 2018. The results indicate that, the 2010 wind map showed wind speed is highest (8m/s) in the southernmost part of Ghana (i.e. Coastal part of Greater Accra and Volta Regions) at 10m high while the wind map of 2018 showed that wind speed is highest (9m/s) in the Upper East Region of Ghana at 10m high. As wind energy is untapped in Ghana, we advised that Government should further explore the results for the Upper East Region in ascertaining that it was not influenced by Trade winds and apply to different sectors of the economy through appropriate institutional regulations. The wind energy in Northern Ghana should be dedicated to mechanized agriculture, augmenting electricity tariffs for the poor in those areas and extending electricity to rural communities that do not have access to the national grid under the rural electrification project. Meanwhile, the wind energy generated from the southern part of Ghana should be dedicated mostly to commercial and industrial activities. Keywords: Wind Energy Potential, mechanized agriculture, industrial application, GIS, RS

scholarly journals Wind energy potential assessment based on wind speed, its direction and power data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhiming Wang ◽  
Weimin Liu
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Direction ◽  
Mean Squared Error ◽  
Mixture Distribution ◽  
Information Criterion ◽  
Energy Potential ◽  
Root Mean Squared Error ◽  
Squared Error ◽  
Wind Energy Potential

AbstractBased on wind speed, direction and power data, an assessment method of wind energy potential using finite mixture statistical distributions is proposed. Considering the correlation existing and the effect between wind speed and direction, the angular-linear modeling approach is adopted to construct the joint probability density function of wind speed and direction. For modeling the distribution of wind power density and estimating model parameters of null or low wind speed and multimodal wind speed data, based on expectation–maximization algorithm, a two-component three-parameter Weibull mixture distribution is chosen as wind speed model, and a von Mises mixture distribution with nine components and six components are selected as the models of wind direction and the correlation circular variable between wind speed and direction, respectively. A comprehensive technique of model selection, which includes Akaike information criterion, Bayesian information criterion, the coefficient of determination R2 and root mean squared error, is used to select the optimal model in all candidate models. The proposed method is applied to averaged 10-min field monitoring wind data and compared with the other estimation methods and judged by the values of R2 and root mean squared error, histogram plot and wind rose diagram. The results show that the proposed method is effective and the area under study is not suitable for wide wind turbine applications, and the estimated wind energy potential would be inaccuracy without considering the influence of wind direction.

scholarly journals Potential for wind energy generation in Piracicaba, SP, Brazil

2014 ◽  
Vol 18 (5) ◽  
pp. 559-564 ◽  
Author(s):  
Vanessa de F. Grah ◽  
Isaac de M. Ponciano ◽  
Tarlei A. Botrel
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Potential ◽  
College Of Agriculture ◽  
Average Wind Speed ◽  
Wind Energy Generation ◽  
Average Wind ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
Two Parameters

Wind power has gained space in Brazil's energy matrix, being a clean source and inexhaustible. Therefore, it becomes important to characterize the wind potential of a given location, for future applications. The main objective of the present study was to estimate the wind energy potential in Piracicaba, SP, Brazil. The wind speed data were collected by an anemometer installed at the Meteorological Station Luiz de Queiroz College of Agriculture, Piracicaba-SP. The wind speed variability was represented by the Weibull frequency distribution, a probability density function of two parameters (k and c). The parameters k and c were used to correlate the Gamma function with the annual average wind speed, the variance and power mean density. A wind profile was made to evaluate the behavior of historical average speeds at higher altitudes measured by anemometer, to estimate the gain in power density. The values of k for all heights were close to 1 which corresponds to a wind regime highly variable, and c values were also low representing a low average speed of the location. The location was characterized as being unfavorable for the application of wind turbines for power generation.

scholarly journals Wind energy resources in Bosnia & Herzegovina

2010 ◽  
Vol 14 (1) ◽  
pp. 255-260 ◽  
Author(s):  
Elvir Zlomusica
Keyword(s):  
Wind Energy ◽  
Complex Terrain ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
Energy Resources ◽  
Energy Potential ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
Wind Characteristics ◽  
Wind Energy Resources

Bosnia & Herzegovina state has good potentials for generation of electric power. It applies, first of all, to its water and coal potentials. In addition to this, Bosnia & Herzegovina has good potentials of certain renewable energy sources, namely: wind, sun, water flows, and biomass. Observation and measurement of wind characteristics in Bosnia & Herzegovina have been performed for over 120 years now. However, the first measurements with adequate equipment and technology aimed at determining of the wind energy potential, started in 2002. Research is still incomplete and limited by complex terrain, the wind type 'Bora', as well as by non-existence of necessary strategic documents and regulations on renewables. Based on this research, several wind farms have been already planned, with an installed power of about 200 MW, and with a high coefficient of energy efficiency. This paper provides a review of localities from the wind characteristics research performed in the area of Bosnia & Herzegovina in the period 2002-2008. Additionally, it gives a brief reference to the complexity of wind potential research under complex conditions of terrain and wind type in Bosnia & Herzegovina, giving in this way a contribution to a more realistic estimate of economically feasible potential of Bosnia and Herzegovina, which will consequently help creation of needed strategic documents.

scholarly journals Wind energy potential assessment based on wind speed, its direction and power data

2021 ◽  
Author(s):  
Zhiming Wang ◽  
Weimin Liu
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Direction ◽  
Mean Squared Error ◽  
Mixture Distribution ◽  
Information Criterion ◽  
Energy Potential ◽  
Root Mean Squared Error ◽  
Squared Error ◽  
Wind Energy Potential

Abstract Based on wind speed, direction and power data, an assessment method of wind energy potential using finite mixture statistical distributions is proposed. Considering the correlation existing and the effect between wind speed and direction, the angular-linear modeling approach is adopted to construct the joint probability density function of wind speed and direction. For modeling the distribution of wind power density and estimating model parameters, based on expectation-maximization algorithm, a two-component three-parameter Weibull mixture distribution is chosen as wind speed model, and a von Mises mixture distribution with nine components and six components are selected as wind direction and relation circular variable models, respectively. A comprehensive technique of model selection, which includes Akaike information criterion, Bayesian information criterion, the coefficient of determination R2 and root mean squared error, is used to select the optimal model in all candidate models. The proposed method is applied to averaged 10-minute field monitoring wind data and compared with the other estimation methods and judged by the values of R2 and root mean squared error, histogram plot and wind rose diagram. The results show that the proposed method is effective and the area under study is not suitable for wide wind turbine applications, and the estimated wind energy potential would be inaccuracy without considering the influence of wind direction.

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