Climate Change Characteristics of Coastal Wind Energy Resources in Zhejiang Province Based on ERA-Interim Data

The reanalysis of sea surface wind speed is compared with the measured wind speed of five offshore wind towers in Zhejiang, China. The applicability of reanalysis data in the Zhejiang coastal sea surface and the climatic characteristics of sea surface wind power density is analyzed. Results show that the reanalysis of wind field data at the height of 10 m can well capture the wind field characteristics of the actual sea surface wind field. The sea surface wind power density effective hours increases from west to east and north to south. Then Empirical orthogonal function (EOF) is used to analyze the sea surface wind power density anomaly field, and the first mode is a consistent pattern, the second mode is a North-South dipole pattern, the third mode is an East-West dipole pattern respectively. The stability of wind energy resources grows more stable with increasing distance from the coast, and the northern sea area which is far away from the coastal sea is more stable than that of the southern sea area. The yearly linear trend of sea surface wind power density is in an East-West dipole pattern respectively. The wind energy resources are more stable farther from the coast, and the wind energy resources in the northern sea are more stable than that of the southern sea. The yearly linear trend of sea surface wind power density is the East-West dipole type, the seasonal linear trend is a significant downward trend from West to East in spring, and on the contrary in summer, a non-significant trend in autumn and winter. The monthly change index shows that the linear trend near the entrance of Hangzhou Bay in Northern Zhejiang is of weak increase or decrease, which is good for wind energy development. When the wind power density is between 0 and 150 W·m−2, its frequency mainly shows the distribution trend of high in the West and low in the East, but the wind power density is between 150 and 600 W·m−2, its distribution is the opposite.

Assessment of wind energy potential and characteristics in Qatar for clean electricity generation

The present study analyzes the wind energy potential of Qatar, by generating a wind atlas and a Wind Power Density map for the entire country based on ERA-5 data with over 41 years of measurements. Moreover, the wind speeds’ frequency and direction are analyzed using wind recurrence, Weibull, and wind rose plots. Furthermore, the best location to install a wind farm is selected. The results indicate that, at 100 m height, the mean wind speed fluctuates between 5.6054 and 6.5257 m/s. Similarly, the Wind Power Density results reflect values between 149.46 and 335.06 W/m2. Furthermore, a wind farm located in the selected location can generate about 59.7437, 90.4414, and 113.5075 GWh/y electricity by employing Gamesa G97/2000, GE Energy 2.75-120, and Senvion 3.4M140 wind turbines, respectively. Also, these wind farms can save approximately 22,110.80, 17,617.63, and 11,637.84 tons of CO2 emissions annually.

Comparison of numerical methods in estimating Weibull parameters to install a sustainable wind farm in mount Bamboutos, Cameroon

Purpose The purpose of this paper is to evaluate the wind energy potential of Mount Bamboutos in Cameroon by comparing nine numerical methods in determining Weibull parameters for the installation of a sustainable wind farm. Design/methodology/approach By using statistical analysis, the analysis of shape and scale parameters, the estimation of the available wind power density and wind direction frequency distributions, the objective of this paper is to compare nine numerical methods in estimating Weibull parameters for the installation of a sustainable wind farm in Mount Bamboutos, Cameroon. Findings The results suggested that the minimum and maximum values of the standard deviation occurred in the months of May and November 2016, respectively. The graphical method appeared to be the most effective method with the maximum value of variance and minimum values of chi-square and RMSE. The scale factor parameter values indicated that Mount Bamboutos hills were a potential site for electricity generation. The analysis of wind power density showed that it reached the maximum and minimum values in February and September, respectively. The wind direction frequency distributions showed that the prevailing wind directions were North-East. Originality/value The wind energy potential of Mount Bamboutos in Cameroon was performed by using nine numerical methods. Therefore, it could be effective to have a prediction model for the wind speed profile. The analysis of wind power density showed that it reached the maximum and minimum values in February and September, respectively. The wind direction frequency distributions showed that the prevailing wind directions were North-East.

Evaluation of the Technical Wind Energy Potential of Kisii Region Based on the Weibull and Rayleigh Distribution Models

Background. Global warming is a growing threat in the world today mainly due to the emission of CO2 caused by the burning of fossil fuel. Consequently, countries are being forced to seek potential alternative sources of energy such as wind, solar, and photovoltaic among many others. However, the realization of their benefits is faced with challenges. Though wind stands a chance to solve this problem, the lack of adequate site profiles, long-term behavioural information, and specific data information that enables informed choice on site selection, turbine selection, and expected power output has remained a challenge to its exploitation. In this research, Weibull and Rayleigh models are adopted. Wind speeds were analyzed and characterized in the short term and then simulated for a long-term measured hourly series data of daily wind speeds at a height of 10 m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent the mean wind speed, diurnal variations, daily variations, and monthly variations. To verify the models, statistical tools of Chi square, RMSE, MBE, and correlational coefficient were applied. Also, the method of measure, correlate, and predict was adopted to check for the reliability of the data used. The wind speed frequency distribution at the height of 10 m was found to be 2.9 ms-1 with a standard deviation of 1.5. From the six months’ experiments, averages of wind speeds at hub heights of 10 m were calculated and found to be 1.7 m/s, 2.4 m/s, and 1.3 m/s, for Ikobe, Kisii University, and Nyamecheo stations, respectively. The wind power density of the region was found to be 29 W/m2. By a narrow margin, Rayleigh proves to be a better method over Weibull in predicting wind power density in the region. Wind speeds at the site are noted to be decreasing over the years. The region is shown as marginal on extrapolation to 30 m for wind energy generation hence adequate for nongrid connected electrical and mechanical applications. The strong correlation between the site wind profiles proves data reliability. The gradual decrease of wind power over the years calls for attention.

Wind Intensity and Power Density in the Brazilian Dry Tropical Forests (Caatinga)

Wind speed has been widely used for energy purposes. Therefore, studies focused on its knowledge are extremely relevant to better benefit from this resource. The aim of this study is to analyze wind behavior and estimate wind power density (WPD) in the interior of northeastern Brazil, a region with predominance of the semi-arid climate, based on the data made available by the automatic station installed at the Experimental Farm in the municipality of São João do Cariri-PB, which come from the SONDA project and refer to the year 2007. Descriptive analysis techniques were used to identify the periods in which the wind behavior is more favorable to wind harnessing. From the results obtained, there was a predominance of southeast in the wind direction component. However, the values of both the observed wind speed (2, 25 and 50 m) and the wind speed estimated for the levels of 100 and 150 m, as well as the estimates of power density (50, 100 and 150 m) showed that the lowest records are present mainly in the first hours of the day, as well as in the first half of the year, while the highest values occur from 10 a.m. extending to the beginning of the night and prevail in the last six months of the year. These determinations denoted higher values of wind power density available for the second half of the year (mainly from August to December).

Observation and Simulation of Wind Speed and Wind Power Density over Bac Lieu Region

In this study, the WRF (Weather Research and Forecasting) model was used to simulate and investigate diurnal and annual variations of wind speed and wind power density over Southern Vietnam at 2‐km horizontal resolution for two years (2016 and 2017). The model initial and boundary conditions are from the National Centers for Environmental Prediction (NCEP) Final Analyses (FNL). Observation data for two years at 20 m height at Bac Lieu station were used for model bias correction and investigating diurnal and annual variation of wind speeds. The results show that the WRF model overestimates wind speeds. After bias correction, the model reasonably well simulates wind speeds over the research area. Wind speed and wind power density show much higher values at levels of 50–200 m above ground levels than near ground (20 m) level and significantly higher near the coastal regions than inland. Wind speed has significant annual and diurnal cycles. Both annual and diurnal cycles of wind speeds were well simulated by the model. Wind speed is much stronger during daytime than at nighttime. Low-level wind speed reaches the maximum at about 14 LT to 15 LT when the vertical momentum mixing is highly active. Wind speeds over the eastern coastal region of Southern Vietnam are much stronger in winter than in summer due to two main reasons, including (1) stronger large-scale wind speed in winter than in summer and (2) funnel effect creating a local maximum wind speed over the nearshore ocean which then transports high-momentum air inland in winter.

Assessment of Wind Energy Potential In Zwara, Libya

To assess the wind energy potential at any site, the wind power density should be estimated; it evaluates the wind resource and indicates the amount of available wind energy. The purpose of this study is to estimate the monthly and annual wind power density based on the Weibull distribution using wind speed data collected in Zwara, Libya during 2007. The wind date are measured at the three hub heights of 10m, 30m, and 50m above ground level, and recorded every 10 minutes. The analysis showed that the annual average wind speed are 4.51, 5.86, 6.26 m/s for the respective mentioned heights. The average annual wind power densities at the mentioned heights were 113.71, 204.19, 243.48 , respectively.