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Dimensional analysis shows that the relation between wind speed and maximum or mean water wave height takes the form H = c U 0 2 g , where H is the maximum or mean water wave height caused by wind of speed U 0 , g is the gravitational acceleration, and c is a dimensionless constant. This relation is important in predicting the maximum or mean water wave height caused by a tropical cyclone. Firstly, the mathematical and theoretical justification for determining c is presented. Verification is conducted using four tropical cyclones as case studies for determining c using significant wave heights rather than the overall maximum and mean. The observed values of c are analyzed statistically. On the days when the fixed buoy captured the highest wind speeds, the frequency distributions of the data for c are close to a bell shape with very small standard deviations in comparison with the mean values; thus, the mean values provide good predictions for c. In view of the fact that tropical cyclone waves are turbulent and the background waves caused by many other factors such as lunar tidal effect cannot be ignored, the obtained results for c are quite satisfactory. This method provides a direct approach in the prediction of the wave height or the wind speeds given the c value and can serve an interpolation methodology to increase the temporal resolution of the data. [ABSTRACT FROM AUTHOR]

Once a fire breaks out in an electric bus, it can easily lead to mass casualties and severe injuries, resulting in significant property damage and social impact. The high-temperature smoke and toxic gases in an electric bus fire are key factors that cause a large number of casualties, both of which are closely related to ventilation conditions. In view of this, this study utilized the Fire Dynamics Simulator (FDS 6) software to establish a three-dimensional experimental model of an electric bus. Numerical simulations of the fire combustion process in the electric bus under different ventilation conditions were conducted. Multiple fire scenes were established based on varying ventilation areas, different wind speeds, and diverse window opening positions. This study specifically analyzed the temperature and CO concentration variations under different fire scenes. By comparing the simulation results under different ventilation conditions, it can be concluded that when an electric bus catches fire, opening 100% of the windows, the wind speed is 8 m/s, and opening the rear window of the electric bus first can minimize the fire risk. Through the numerical simulation of electric bus fires under various conditions, this study analyzed the impact of different ventilation conditions on electric bus fires, providing a theoretical basis for firefighting and rescue efforts as well as personnel evacuation in electric bus fire incidents, with the ultimate goal of maximizing public safety. [ABSTRACT FROM AUTHOR]

Wind energy has gained tremendous attention recently due to its abundance potential and to obviate the adverse impacts of fossil fuel consumption. However, the efficient development and operation of wind energy systems require precise and accurate wind speed prediction. To fulfill this aim, machine learning algorithms have shown its prowess in accurately predicting the wind speed and this study proposes an interpretable stacked ensemble with ridge regressor utilizing ML algorithms such as catboost (CB), gradient boost (GB), multilayer perceptron (MLP), and random forest (RF) as a base model. The base models' estimations are integrated by applying a ridge regressor to enhance the accuracy of wind speed estimation. The dataset consists of 87 600 samples from which 80% samples are used for training. The proposed approach provides interpretability of the prediction results through Shapley additive explanations and feature importance analysis. The result of the proposed method is calculated by comparing the estimation outcomes with each model such as CB, GB, MLP, and RF in terms of error metrics such as root mean squared error (RMSE) and mean absolute error (MAE). The proposed model outperforms the others due to a reduction of error in RMSE by 19.89% and MAE by 24% respectively. [ABSTRACT FROM AUTHOR]

Urban morphology impacts micro-climates, solar energy absorption, air flow, wind patterns, energy consumption, and air pollution concentration. Temperature control in public spaces reduces heat island formation, while ventilation corridors potentially improve air quality. However, despite the literature on airflow and urban tall buildings providing valuable insights, further research is needed to understand the complex relationship between airflow patterns and urban high-rise buildings. This research should consider factors such as landscape types, building height, density, and orientation. This research aims to examine airflow patterns in high-rise buildings that are influenced by nearby land use, which can impact ventilation and climate comfort. To investigate these objectives, we utilized the Universal Thermal Climate Index (UTCI) and Predicted Mean Vote Index (PMV) by conducting simulations using ENVI-met software. The results revealed that buildings with narrower widths have better wind warded front conditions, while those with an unfavorable wind angle or a narrow facade are less comfortable. Public spaces that face the wind benefit from improved ventilation. It is essential to consider the optimal arrangement, ventilation, and height of buildings to ensure the favorable airflow. Factors such as the placement of trees, the use of porous walls, water features such as fountains and sprinklers, and the local climate all contribute to creating better wind conditions. Investigating the reciprocal interaction between the landscape, high-rise buildings, and climate comfort could be considered in future research. [ABSTRACT FROM AUTHOR]

Dimensional analysis shows that the relation between wind speed and maximum or mean water wave height takes the form H=cU02g, where H is the maximum or mean water wave height caused by wind of speed U0, g is the gravitational acceleration, and c is a dimensionless constant. This relation is important in predicting the maximum or mean water wave height caused by a tropical cyclone. Firstly, the mathematical and theoretical justification for determining c is presented. Verification is conducted using four tropical cyclones as case studies for determining c using significant wave heights rather than the overall maximum and mean. The observed values of c are analyzed statistically. On the days when the fixed buoy captured the highest wind speeds, the frequency distributions of the data for c are close to a bell shape with very small standard deviations in comparison with the mean values; thus, the mean values provide good predictions for c. In view of the fact that tropical cyclone waves are turbulent and the background waves caused by many other factors such as lunar tidal effect cannot be ignored, the obtained results for c are quite satisfactory. This method provides a direct approach in the prediction of the wave height or the wind speeds given the c value and can serve an interpolation methodology to increase the temporal resolution of the data.

Once a fire breaks out in an electric bus, it can easily lead to mass casualties and severe injuries, resulting in significant property damage and social impact. The high-temperature smoke and toxic gases in an electric bus fire are key factors that cause a large number of casualties, both of which are closely related to ventilation conditions. In view of this, this study utilized the Fire Dynamics Simulator (FDS 6) software to establish a three-dimensional experimental model of an electric bus. Numerical simulations of the fire combustion process in the electric bus under different ventilation conditions were conducted. Multiple fire scenes were established based on varying ventilation areas, different wind speeds, and diverse window opening positions. This study specifically analyzed the temperature and CO concentration variations under different fire scenes. By comparing the simulation results under different ventilation conditions, it can be concluded that when an electric bus catches fire, opening 100% of the windows, the wind speed is 8 m/s, and opening the rear window of the electric bus first can minimize the fire risk. Through the numerical simulation of electric bus fires under various conditions, this study analyzed the impact of different ventilation conditions on electric bus fires, providing a theoretical basis for firefighting and rescue efforts as well as personnel evacuation in electric bus fire incidents, with the ultimate goal of maximizing public safety.

Windstorms resulting from intense synoptic-scale cyclones are an important natural hazard in the current climate of the northeastern United States, but their likely response to global climate non-stationarity is poorly understood. This study investigates the ability of the Weather Research and Forecasting model applied at 3.3 km resolution to simulate historically important cold-season windstorms associated with Alberta Clippers (AC) and Colorado Lows (CL) and then examines how such events may evolve in the future using pseudo-global-warming (PGW) simulations. The simulations encompass approximately 14-day periods that include passage of both a primary-strong extratropical cyclone during which multiple stations exhibited 10-m wind speed observations > 20 ms−1, and a secondary-weak mid-latitude cyclone. The thermodynamics changes projected in the pseudo-global-warming (PGW) experiments lead to a modest decline in maximum wind speeds. The marginal probability of 10-m wind speeds > 14.3 ms−1 drops from 6.6 to 5.3% during the intense AC and from 9 to 6.5% for the intense CL. Similarly, the probability of nonzero precipitation in any grid cell/3-h time interval declines from 2.44% in the control simulation of the intense AC to 1.59% in the PGW simulation, and from 3.39 to 2.67% for the intense CL. Virtually all snow during the CL that occurred during March 2018 is simulated as other hydrometeor types in the PGW experiment, and the spatial extent and location of very heavy precipitation are also greatly modified. [ABSTRACT FROM AUTHOR]

With the objective of comparing the potential values of evaporative and wind drag losses in different techniques of sprinkler irrigation in Camagüey Municipality, a study was carried out for the predominant conditions in UBPC Victoria II, belonging to Empresa Agropecuaria Camagüey. The techniques studied were the central pivot machines, the winder irrigation machine, the sprinkler irrigation system and the micro sprinkler. Drop size, wind speed in the maximum height of irrigation water, drop time of flight and steam pressure deficit were valued. The results indicate that the potential evaporative and drag losses under the predominant conditions in Camagüey Municipality, reach values among 7,5 % in the irrigation with micro sprinkler, 7,7 % in the irrigation with central pivot machines, 8,6 % with sprinkler irrigation systems and 9,2% in the winder irrigation machine. Nevertheless, in this technique, under conditions of wind speeds bigger than 3,1 m/s, they could overcome the value of 15 %, considered as permissible maximum limit for the execution of satisfactory air irrigation. [ABSTRACT FROM AUTHOR]

Wind speed reconciliation across different wind sources is critically needed for extending available satellite wind records in Tropical Cyclones. The deviations between wind references of extremes, such as the moored buoy data and dropsonde wind estimates for guidance on geophysical model function development, are one of the main causes of wind speed differences for wind products, for instance, the overestimation of Synthetic Aperture Radars (SARs) relative to ASCAT winds. The study proposes a new wind speed adjustment to achieve mutual adjustment between ASCAT CMOD7 winds and simultaneous SAR wind speeds. The so-called CMOD7D-v2 adjustment is constructed based on the statistical analysis of SAR and ASCAT Tropical Cyclone acquisitions between 2016 and 2021, showing a satisfactory performance in wind speed reconciliation for winds with speeds higher than 14 m/s. Furthermore, the error characteristics of the CMOD7D-v2 adjustment for Tropical Cyclone winds are analyzed using the Triple Collocation analysis technique. The analysis results show that the proposed wind adjustment can reduce ASCAT wind errors by around 16.0% when adjusting ASCAT winds to SAR wind speeds. In particular, when downscaling SAR winds, the improvement in ASCAT wind errors can be up to 42.3%, effectively alleviating wind speed differences across wind sources. Furthermore, to avoid the impacts of large footprints by ASCAT sensors, wind speeds retrieved from SAR VV signals (acting as a substitute for ASCAT winds) are adjusted accordingly and compared against SAR dual-polarized winds and collocated Stepped Frequency Microwave Radiometer (SFMR) observations. We find that the bias values of adjusted winds are lower than products from other adjustment schemes by around 5 m/s at the most extreme values. These promising results verify the plausibility of the CMOD7D-v2 adjustment, which is conducive to SAR and ASCAT wind speed comparisons and extreme wind analysis in Tropical Cyclone cases. [ABSTRACT FROM AUTHOR]

The paper describes a novel structural reliability method, particularly suitable for multi-dimensional environmental systems, either measured or numerically simulated over a sufficient period, resulting in sufficiently long ergodic time series. This study illustrates the efficiency of the proposed methodology by applying it to predict extreme wind speeds of a group of selected measured sites in Southern Norway in the region near the Landvik wind station. It is well known that wind speeds at different locations are highly non-linear, multi-dimensional and cross-correlated dynamic environmental responses, which can be challenging to analyse accurately. Unlike other environmental reliability methods, the new method does not require restarting the simulation each time the system fails, e.g., in the case of numerical simulation. In the case of measured environmental system response, an accurate prediction of system failure probability is also possible, as illustrated in this study. Moreover, in contrast to classical reliability methods, the proposed method can handle systems with high dimensionality and cross-correlation between the different dimensions.

The dynamic evaporation of single droplets was investigated under controlled conditions. In the evaporation process, a droplet was placed on a peach leaf surface. In this research, the relative humidity and temperature were kept constant, and the wind speeds and thiophanate-methyl concentrations varied. Based on these conditions, this study aimed to determine the droplets' dynamic transforming characteristics, including the contact angle, the height of the droplets, and the evaporation rate. Five concentrations and five wind speeds were chosen, and pure water droplets at different wind speeds were used as a control group. All single droplets were generated by a syringe. The results showed that the pure water and thiophanate-methyl droplets' evaporation mode was CCR (constant contact radius) mode. An increase in the wind speed accelerated the evaporation process, when the wind speed was 0 m/s, the evaporation was the longest, and the shortest evaporation was achieved with 2.0 m/s wind speed. An increase in wind speed enhanced the pure water droplets' dynamic evaporation process with a maximum enhancement ratio of 3.44 times in the present work. Under the same conditions, the thiophanate-methyl droplets' evaporation time was shorter than that of the pure water droplets. For thiophanate-methyl droplets, the higher the concentration, the shorter the dynamic evaporation process. A 1250 ppm thiophanate-methyl solution with 2.0 m/s wind speed, had an evaporation ratio that was 2.83 times greater than that measured with 0 m/s wind speed. These results could benefit farmers by suggesting that they should adjust the concentration of thiophanate-methyl depending on the wind speed in order to reduce pollution. [ABSTRACT FROM AUTHOR]

Energy consumption in Bangladesh increased for economic, industrial, and digitalization growth. Reductions in conventional sources such as natural gas (54%) and coal (5.6%) are calls to enhance renewable resources. This paper aims to investigate the atmospheric variables for potential wind zones and develop a statistical power-forecasting model. The study-site is Bangladesh, focusing on eight divisions across two regions. First, the southern zone includes Dhaka (Capital), Chittagong, Barishal, and Khulna. The northern regions are Rajshahi, Rangpur, Mymensingh, and Sylhet. This investigation illustrates wind (m/s) speeds at various heights (m) and analyzes the boundary layer height (BLH) from the European Center for Medium Range Weather Forecast reanalysis 5th generation (ERA5). The data is from a period of 40 years from 1979 to 2018, assessing with a climatic base of 20 years (1979 to 2000). The climatological analysis comprises trends, time series, anomalies, and linear correlations. The results for the wind speed (BLH) indicate that the weakest (lower) and strongest (higher) regions are Sylhet and Barishal, respectively. Based on power-curve relationships, a simple power predictive model (SPPM) is developed using global wind atlas (GWA) data (sample: 1100) to estimate the power density (W/m2) and found an accuracy of 0.918 and 0.892 for Exponential (EXP) and Polynomial (PN) with mean absolute percentage errors (MAPE) of 22.92 and 21.8%, respectively. For validation, SPPM also forecasts power incorporating historical observations for Chittagong and obtains correlations of 0.970 and 0.974 for EXP and PN with a MAPE of 10.26 and 7.69% individually. Furthermore, calculations for annual energy production reveal an average megawattage of 1748 and 1070 in the southern and northern regions, with an MAPE of 15.71 and 5.85% for EXP and PN models, except Sylhet. The SPPM's predictability can be improved with observed wind speeds and turbine types. The research wishes to apply SPPM for estimating energy in operational power plants. [ABSTRACT FROM AUTHOR]

Wind speed reconciliation across different wind sources is critically needed for extending available satellite wind records in Tropical Cyclones. The deviations between wind references of extremes, such as the moored buoy data and dropsonde wind estimates for guidance on geophysical model function development, are one of the main causes of wind speed differences for wind products, for instance, the overestimation of Synthetic Aperture Radars (SARs) relative to ASCAT winds. The study proposes a new wind speed adjustment to achieve mutual adjustment between ASCAT CMOD7 winds and simultaneous SAR wind speeds. The so-called CMOD7D-v2 adjustment is constructed based on the statistical analysis of SAR and ASCAT Tropical Cyclone acquisitions between 2016 and 2021, showing a satisfactory performance in wind speed reconciliation for winds with speeds higher than 14 m/s. Furthermore, the error characteristics of the CMOD7D-v2 adjustment for Tropical Cyclone winds are analyzed using the Triple Collocation analysis technique. The analysis results show that the proposed wind adjustment can reduce ASCAT wind errors by around 16.0% when adjusting ASCAT winds to SAR wind speeds. In particular, when downscaling SAR winds, the improvement in ASCAT wind errors can be up to 42.3%, effectively alleviating wind speed differences across wind sources. Furthermore, to avoid the impacts of large footprints by ASCAT sensors, wind speeds retrieved from SAR VV signals (acting as a substitute for ASCAT winds) are adjusted accordingly and compared against SAR dual-polarized winds and collocated Stepped Frequency Microwave Radiometer (SFMR) observations. We find that the bias values of adjusted winds are lower than products from other adjustment schemes by around 5 m/s at the most extreme values. These promising results verify the plausibility of the CMOD7D-v2 adjustment, which is conducive to SAR and ASCAT wind speed comparisons and extreme wind analysis in Tropical Cyclone cases.

The dynamic evaporation of single droplets was investigated under controlled conditions. In the evaporation process, a droplet was placed on a peach leaf surface. In this research, the relative humidity and temperature were kept constant, and the wind speeds and thiophanate-methyl concentrations varied. Based on these conditions, this study aimed to determine the droplets’ dynamic transforming characteristics, including the contact angle, the height of the droplets, and the evaporation rate. Five concentrations and five wind speeds were chosen, and pure water droplets at different wind speeds were used as a control group. All single droplets were generated by a syringe. The results showed that the pure water and thiophanate-methyl droplets’ evaporation mode was CCR (constant contact radius) mode. An increase in the wind speed accelerated the evaporation process, when the wind speed was 0 m/s, the evaporation was the longest, and the shortest evaporation was achieved with 2.0 m/s wind speed. An increase in wind speed enhanced the pure water droplets’ dynamic evaporation process with a maximum enhancement ratio of 3.44 times in the present work. Under the same conditions, the thiophanate-methyl droplets’ evaporation time was shorter than that of the pure water droplets. For thiophanate-methyl droplets, the higher the concentration, the shorter the dynamic evaporation process. A 1250 ppm thiophanate-methyl solution with 2.0 m/s wind speed, had an evaporation ratio that was 2.83 times greater than that measured with 0 m/s wind speed. These results could benefit farmers by suggesting that they should adjust the concentration of thiophanate-methyl depending on the wind speed in order to reduce pollution.

For large offshore wind turbines, pitch control is usually used for regulating generated power to the rated value and for mitigating the dynamic loads that at the wind speeds above the rated speeds. However, tracking the pitch angle accurately and quickly can hardly be realised due to complex operating environments, uncertain system parameters, various disturbances, and coupled effects between wind, wave, and turbine structure. In this study, an individual pitch control system based on a neural adaptive strategy is proposed to address the problems related to uncertain system parameters and various disturbances. The proposed control method can achieve zero error tracking for the pitch angle in a predefined finite time. The design and stability analysis for the proposed method is elaborated. A simulation model is established in Matlab/Simulink, and by comparing it with the traditional proportional–integral–derivative control method, the merit of the proposed control scheme is verified. [ABSTRACT FROM AUTHOR]

We propose an improved semi-empirical scattering model for X-band radar backscattering from rough sea surfaces. This new model has a wider validity range of wind speeds than does the existing semi-empirical sea spectrum (SESS) model. First, we retrieved the small-roughness parameters from the sea surfaces, which were numerically generated using the Pierson-Moskowitz spectrum and measurement datasets for various wind speeds. Then, we computed the backscattering coefficients of the small-roughness surfaces for various wind speeds using the integral equation method model. Finally, the large-roughness characteristics were taken into account by integrating the small-roughness backscattering coefficients multiplying them with the surface slope probability density function for all possible surface slopes. The new model includes a wind speed range below 3.46 m/s, which was not covered by the existing SESS model. The accuracy of the new model was verified with two measurement datasets for various wind speeds from 0.5 m/s to 14 m/s.

A multilayer frequency adaptive fundamental signal extractor‐based filter is used for the improvement of power quality of a single phase utility grid interfaced to a wind–photovoltaic (PV) system. This filter is used for the grid synchronisation, serving multiple objectives such as mitigating the lower‐order harmonics, DC offset elimination, load reactive power compensation, and power flow management. As this filtering technique is based on frequency adaptation, it adapts the changes in the grid fundamental frequency. The effectiveness of this filter is studied with simulations using MATLAB Simulink under varying solar irradiance, wind speeds, and loads also validated on the test setup developed in the laboratory. [ABSTRACT FROM AUTHOR]

This study proposes a robust sub‐synchronous damping controller based on fractional‐order sliding mode control (FOSMC) method to mitigate sub‐synchronous control interaction (SSCI) induced by DFIG‐based wind park connected to series‐compensated transmissions. Firstly, the nonlinearity of DFIG is cancelled through feedback linearisation. Secondly, FOSMC is designed and applied to the control loop of the DFIG rotor‐side converter. During the design process, the extra degree of freedom, provided by the fractional operator, is employed to achieve fast SSCI‐damping. Thirdly, a genetic algorithm is used for parameter optimisation with the aim of making system eigenvalues approach the left plane. The effectiveness of the proposed damping controller is evaluated based on the adapted IEEE first benchmark model, non‐aggregated wind system model with a realistic configuration, and experimental platform. Simulation and experiment results demonstrate the superior damping performance of FOSMC under different wind speeds, compensation levels, and the number of online wind turbines. Moreover, FOSMC also shows the robustness under parameter uncertainty, control parameter perturbation, and symmetric (three‐phase short circuit) fault. [ABSTRACT FROM AUTHOR]

This paper provides an analytical assessment of the feasibility of wind energy for Saudi Arabia's envisioned NEOM city, which plans to use only renewable energy. A probability density function was fit to winds simulated for the NEOM region during 2014‐2018. Using this distribution, the optimal wind turbine was selected as the one with the largest capacity factor and smallest levelized cost of energy (LCOE). Financial, environmental, and risk analysis of a wind farm consisting of 100 of these units was also performed. A Weibull distribution determined by changing the shape and scale parameters to minimize the mean squared error offered the best fit to the measured wind speeds at this location. The estimated power density showed that the NEOM site warrants a Class 3 classification, which means wind energy systems would be suitable for commercial operation. A 3.2‐MW wind turbine, which is optimal for this location, has a capacity factor varying from 31.9% to 41.4% and LCOE that ranges from 6.99¢ to 8.32¢ per kWh. The 320‐MW wind farm has a positive net present value, a simple payback period of 13.8 years, and a LCOE of 6.6¢ per kWh. By installing this farm, potential annual savings of CO2 are around 106 metric tons. [ABSTRACT FROM AUTHOR]

This study modifies the IEEE first benchmark model (FBM) by connecting nearby doubly‐fed induction generator (DFIG) wind farms to utilize the inbuilt convertor controller for damping the sub‐synchronous resonance (SSR) oscillations. The overall model was evaluated to determine the induction generator effect (IGE) and torsional interaction (TI) of sub‐synchronous resonance (SSR) at various compensation levels, wind speeds, and system parameter settings both with and without a DFIG wind farm. The results of this detailed analysis demonstrated that augmenting an IEEE FBM with a DFIG wind farm suppresses SSR‐induced IGE in the power system. An optimal orientation was investigated from rotor‐side converter (RSC) and grid‐side converter (GSC) of DFIG wind farm using residue configuration to design a SSR supplementary damping controller (SSDC). To suppress the TI effect of SSR, the SSDC implements damping control using three different feedback signals: line current, line power, and voltage across a series capacitor. A robust signal for achieving smooth damping under various operating conditions was defined in terms of several key characteristics, namely, high average residue magnitude, average phase angle of residue and avoidance of destabilisation of other dominant modes. The proposed model was validated using eigenvalue analysis, participation factor calculation and time‐domain simulation. [ABSTRACT FROM AUTHOR]

The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) measures infrared transmittance spectra of the atmosphere from low Earth orbit using the Sun as a light source (solar occultation). Doppler shifts of gas-phase lines in the measured spectra can be used to determine line-of-sight winds. These line-of-sight winds are a new data product for version 5.2 of ACE-FTS processing. The winds are validated through comparison with independent horizontal wind observations from meteor radars and from the ICON-MIGHTI satellite instrument. ACE-FTS winds show a ∼15 m/s offset, opposite in sign for the two different ACE-FTS observation geometries (sunrise and sunset). • ACE-FTS version 5.2 data product is now available and includes line-of-sight winds. • ACE solar occultation measurements can be used to derive line-of-sight winds by observing the Doppler shift on various molecular transitions. • ACE line-of-sight winds were compared against MIGHTI and meteor radar wind data. • Average wind speeds as a function of altitude show that there is a small shift in calculated winds between ACE and MIGHTI/Meteor radar. [ABSTRACT FROM AUTHOR]

Energy consumption in Bangladesh increased for economic, industrial, and digitalization growth. Reductions in conventional sources such as natural gas (54%) and coal (5.6%) are calls to enhance renewable resources. This paper aims to investigate the atmospheric variables for potential wind zones and develop a statistical power-forecasting model. The study-site is Bangladesh, focusing on eight divisions across two regions. First, the southern zone includes Dhaka (Capital), Chittagong, Barishal, and Khulna. The northern regions are Rajshahi, Rangpur, Mymensingh, and Sylhet. This investigation illustrates wind (m/s) speeds at various heights (m) and analyzes the boundary layer height (BLH) from the European Center for Medium Range Weather Forecast reanalysis 5th generation (ERA5). The data is from a period of 40 years from 1979 to 2018, assessing with a climatic base of 20 years (1979 to 2000). The climatological analysis comprises trends, time series, anomalies, and linear correlations. The results for the wind speed (BLH) indicate that the weakest (lower) and strongest (higher) regions are Sylhet and Barishal, respectively. Based on power-curve relationships, a simple power predictive model (SPPM) is developed using global wind atlas (GWA) data (sample: 1100) to estimate the power density (W/m2) and found an accuracy of 0.918 and 0.892 for Exponential (EXP) and Polynomial (PN) with mean absolute percentage errors (MAPE) of 22.92 and 21.8%, respectively. For validation, SPPM also forecasts power incorporating historical observations for Chittagong and obtains correlations of 0.970 and 0.974 for EXP and PN with a MAPE of 10.26 and 7.69% individually. Furthermore, calculations for annual energy production reveal an average megawattage of 1748 and 1070 in the southern and northern regions, with an MAPE of 15.71 and 5.85% for EXP and PN models, except Sylhet. The SPPM’s predictability can be improved with observed wind speeds and turbine types. The research wishes to apply SPPM for estimating energy in operational power plants.

The significance of the water-side gas transfer velocity for air–sea CO2 gas exchange (k) and its non-linear dependence on wind speed (U) is well accepted. What remains a subject of inquiry are biases associated with the form of the non-linear relation linking k to U (hereafter labeled as f(U), where f(.) stands for an arbitrary function of U), the distributional properties of U (treated as a random variable) along with other external factors influencing k, and the time-averaging period used to determine k from U. To address the latter issue, a Taylor series expansion is applied to separate f(U) into a term derived from time-averaging wind speed (labeled as ⟨U⟩, where ⟨.⟩ indicates averaging over a monthly time scale) as currently employed in climate models and additive bias corrections that vary with the statistics of U. The method was explored for nine widely used f(U) parameterizations based on remotely-sensed 6-hourly global wind products at 10 m above the sea-surface. The bias in k of monthly estimates compared to the reference 6-hourly product was shown to be mainly associated with wind variability captured by the standard deviation σσU around ⟨U⟩ or, more preferably, a dimensionless coefficient of variation Iu= σσU/⟨U⟩. The proposed correction outperforms previous methodologies that adjusted k when using ⟨U⟩ only. An unexpected outcome was that upon setting Iu2 = 0.15 to correct biases when using monthly wind speed averages, the new model produced superior results at the global and regional scale compared to prior correction methodologies. Finally, an equation relating Iu2 to the time-averaging interval (spanning from 6 h to a month) is presented to enable other sub-monthly averaging periods to be used. While the focus here is on CO2, the theoretical tactic employed can be applied to other slightly soluble gases. As monthly and climatological wind data are often used in climate models for gas transfer estimates, the proposed approach provides a robust scheme that can be readily implemented in current climate models.

A data‐based estimation of the wind–power curve in wind turbines may be a challenging task due to the presence of anomalous data, possibly due to wrong sensor reads, operation halts, malfunctions or other. In this study, the authors describe a data‐based procedure to build a robust and accurate estimate of the wind–power curve. In particular, they combine a joint clustering procedure, where both the wind speeds and the power data are clustered, with an Earth Mover Distance‐based Extreme Learning Machine algorithm to filter out data that poorly contribute to explain the unknown curve. After estimating the cut‐in and the rated speed, they use a radial basis function neural network to fit the filtered data and obtain the curve estimate. They extensively compared the proposed procedure against other conventional methodologies over measured data of nine turbines, to assess and discuss its performance. [ABSTRACT FROM AUTHOR]

In the present study, the techno-economic feasibility of development of 15 MW wind power plants (wind farms) in the Kingdom of Saudi Arabia has been investigated by analyzing long-term wind speed data. To achieve this aim, two geographically distinct sites covering different non-coastal locations of the Kingdom of Saudi Arabia have been selected. Long-term data indicates that the yearly average wind speed of Kingdom of Saudi Arabia varies from 3.0-4.5 m/s at 10 m height. The wind farms simulated consist of different combinations of 600 kW commercial wind machines (50 m hub-height). The NREL's (HOMER Energy's) HOMER software has been employed to perform the analysis. The study presents the monthly variations of wind speed, cumulative frequency distribution profiles of wind speed, monthly and yearly amount of energy generated from the proposed 15 MW wind farms (50 m hub-height) at different non-coastal locations of Kingdom of Saudi Arabia, cost of generating energy ($/kWh), capacity factor (%), etc. The cumulative frequency distribution indicates that the wind speeds are less than 3 m/s for 48% and 59% of the time during the year at Badanah (Northern province) and Khamis-Mashayt (Southern province), respectively. This implies that wind electric conversion systems or wind farms will not produce energy for 48% of the time during the year at Badanah and for 59% at Khamis-Mashayt. The annual energy produced by 15 MW wind farms (50 m hub-height) has been found to be 18778 and 11314 MWh at Northern and Southern provinces, respectively. The cost of wind-based electricity by using 600 kW (50 m hub-height) commercial wind electric conversion systems has been found to be 0.0612 and 0.1016 US$/kWh for Badanah and Khamis-Mushayt, respectively. Also, the capacity factor of the wind-based power plant has been found to vary from 9 to 15% for the considered locations. [ABSTRACT FROM AUTHOR]

Series capacitor compensation technology has been widely used in long‐distance wind power transmission, which can improve the power transmission capacity and enhance the static stability of the power system. However, adding a series capacitor in the line may present a potential risk of subsynchronous resonance (SSR) to the system. This study focuses on the SSR caused by induction generator effect of the doubly‐fed induction generator‐based wind farms. The SSR phenomenon of wind power system is researched by the impedance analysis method. A mitigation strategy of adding a virtual inductance based on integral control is proposed for enhancing the system stability and alleviating the SSR. It has clear and intuitive physical concept, which is beneficial to system integration and provides a simpler and more economic method for mitigating SSR. Moreover, the principle and process of controller design are elaborated. Moreover, the time‐domain simulation is carried out to prove the effectiveness of the proposed control strategy under different operating conditions considering various compensation levels and wind speeds. Finally, the suppression effects of the virtual inductance in rotor‐side converter and grid‐side converter are compared. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A dish concentrator model is developed by two coupling software. • Finite element model is used to predict the amplitude and frequency of the vibration. • Fluid-structure coupling model is used to analyze harmonic response. • The maximum deformation of reflector is analyzed. • The modal analysis is performed by the fluid-structure coupling model. Abstract The dish solar thermal power generation system is widely used due to the high efficiency. The mechanism of the whole system must meet stringent structural deformation requirements. In this work, the dish concentrator model is developed by the CFD software STAR-CCM+ and the finite element software of ABAQUS, respectively. The pressure fields obtained in the STAR-CCM+ environment are mapped to the ABAQUS model. The validated finite element (FE) model is employed to predict the amplitude and frequency of the vibration. The effects of different pitch angle, azimuth angle and wind velocity on the amplitude and frequency of the vibration are also considered in the process of calculation. The simulated calculation of fluid-structure coupling model is used for the analysis of harmonic response of four hinge nodes vibration. The vibration period of sinusoidal wind excited is 2 s. The results show that the vibration of the dish concentrator will occur with the sinusoidal wind load and reaches the maximum in a short time, then gradually becomes flatter. Moreover, the change of the height angle has a little influence on the modal frequencies of the system and the modal natural frequency is only changed a little when the wind load increases. Thus, the information obtained from the FE model can serve as a reference for subsequent analyses mechanism design such as wind-induced response dynamics analysis. [ABSTRACT FROM AUTHOR]

Research Highlights: Simulations of treefall patterns during tornado events have been conducted, enabling the coupled effects of tornado characteristics, tree properties and soil conditions to be assessed for the first time. Background and Objectives: Treefall patterns and forest damage assessed in post-storm surveys are dependent on the interaction between topography, biology and meteorology, which makes identification of characteristic behavior challenging. Much of our knowledge of tree damage during extreme winds is based on synoptic storms. Better characterization of tree damage will provide more knowledge of tornado impacts on forests, as well as their ecological significance. Materials and Methods: a numerical method based on a Rankine vortex model coupled with two mechanistic tree models for critical wind velocity for stem break and windthrow was used to simulate tornadic tree damage. To calibrate the models, a treefall analysis of the Alonsa tornado was used. Parametric study was conducted to assess induced tornadic tree failure patterns for uprooting on saturated and unsaturated soils and stem break with different knot factors. Results: A power law relationship between failure bending moments and diameter at breast height (DBH) for the hardwood species provided the best correlation. Observed failure distributions of stem break and windthrow along the tornado track were fitted to lognormal distributions and the mean of the critical wind speeds for windthrow were found to be higher than that for stem break. Relationships between critical wind speed and tree size were negatively correlated for windthrow and positively correlated for stem break. Higher soil moisture contents and lower knot factors reduced the critical wind speeds. The simulations show varying tree fall patterns displaying forward and backward convergence, different tornado damage widths and asymmetry of the tracks. These variations were controlled by the relative magnitudes of radial and tangential tornado velocities, the ratio between translational speed and maximum rotational wind speed and the mode of failure of the trees. Conclusions: The results show the complexity of predicting tornadic damage in forests, and it is anticipated that this type of simulation will aid risk assessments for insurance companies, emergency managers and forest authorities.

The rational estimation of extreme wind speeds is crucial. As reported, in the Chinese area, the measured wind speed variation from different meteorological observatories shows a general non-stationary trend in the past 40 years due to urbanization factors or temperature variation. Thus, the non-stationary extreme value analysis (TNGEV) of the measured wind speed is required. However, TNGEV is relatively complicated. Under such a background, in this paper, a novel simplified wavelet transform-based stationary transformation method (PNGEV) is proposed for the extreme value analysis of the non-stationary wind speeds. This paper firstly derives the proposed time-varying extreme value distribution parameter form, combining the wavelet transform and moving average. Secondly, a case study is provided to illustrate and verify this proposed method (PNGEV), using the 40-year daily maximum wind speeds recorded from 1981 to 2020 in Baoshan District Shanghai, China. The effectiveness of the proposed method (PNGEV) is verified by comparing it with TNGEV in the return period and the risk of failure. By comparison, it can be figured out that the proposed PNGEV is practicable and outperforms TNGEV in the stability of the return period calculation, as well as the time-varying extreme value distribution establishment. [ABSTRACT FROM AUTHOR]

Abstract Tornadoes have caused significant damage and casualties in the past decades. These losses have spurred efforts toward tornado-based design, which requires an accurate estimate of the near-surface tornadic wind speeds. Due to the difficulty of obtaining in-situ measurements and various issues regarding Enhance Fujita (EF) scale, a promising method of estimating near-surface wind speed based on damage inflicted is developed. The method utilizes fall directions of trees and other objects with distinct fall patterns to describe the characteristics of the tornado and other wind storms. The observed fall patterns are used to estimate Rankine vortex parameters and reproduce near-surface wind field. The wind field then can be compared to structural damage as an independent method. The near-surface wind speeds of different tornado cases were estimated using this method, one of which (Sidney, IL) exhibited ‘crop-fall’ patterns and yet another (Naplate, IL) caused damage to trees and other infrastructures such as street signs. Based on the damage to structures and estimated wind speeds from tree-fall analysis, empirical fragility curves are also developed, which allows to interpret the vulnerability to tornadoes. The entire process of wind speed, wind load, structural resistance and ultimately how to mitigate damage then can be better understood. [ABSTRACT FROM AUTHOR]

A key aim of most extreme value analyses is the estimation of the r-year return level; the wind speed, or sea-surge, or rainfall level (for example), we might expect to see once (on average) every r years. There are compelling arguments for working within the Bayesian setting here, not least the natural extension to prediction via the posterior predictive distribution. Indeed, for practitioners the posterior predictive return level has been cited as perhaps the most useful point summary from a Bayesian analysis of extremes, and yet little is known of the properties of this statistic. In this paper, we attempt to assess the performance of predictive return levels relative to their estimative counterparts obtained directly from the return level posterior distribution; in particular, we make comparisons with the return level posterior mean, mode and 95% credible upper bound. Differences between the predictive return level and standard summaries from the return level posterior distribution, for wind speed extremes observed in the UK, motivates this work. A large scale simulation study then reveals the superiority of the predictive return level over the other posterior summaries in many cases of practical interest. [ABSTRACT FROM AUTHOR]

In semi-arid developing countries, most poor people depend on contaminated surface or groundwater resources since they do not have access to safe and centrally supplied water. These water resources are threatened by several factors that include high evapotranspiration rates. In the Okavango Delta region in the north-western Botswana, communities facing insufficient centrally supplied water rely mainly on the surface water resources of the Delta. The Delta loses about 98% of its water through evapotranspiration. However, the 2% remaining water rescues the communities facing insufficient water from the main stream water supply. To understand the effects of climate change on evapotranspiration over the Okavango Delta water resources, this study analysed trends in the main climatic parameters needed as input variables in evapotranspiration models. The Mann Kendall test was used in the analysis. Trend analysis is crucial since it reveals the direction of trends in the climatic parameters, which is helpful in determining the effects of climate change on evapotranspiration. The main climatic parameters required as input variables in evapotranspiration models that were of interest in this study were wind speeds, solar radiation and relative humidity. Very little research has been conducted on these climatic parameters in the Okavango Delta region. The conducted trend analysis was more on wind speeds, which had relatively longer data records than the other two climatic parameters of interest. Generally, statistically significant increasing trends have been found, which suggests that climate change is likely to further increase evapotranspiration over the Okavango Delta water resources. [ABSTRACT FROM AUTHOR]

Abstract: We present wind speeds at the ~ 1 bar level at both Jovian polar regions inferred from the 5‐μm infrared images acquired by the Jupiter InfraRed Auroral Mapper (JIRAM) instrument on the National Aeronautics and Space Administration Juno spacecraft during its fourth periapsis (2 February 2017). We adopted the criterion of minimum mean absolute distortion (Gonzalez & Woods, 2008) to quantify the motion of cloud features between pairs of images. The associated random error on speed estimates is 12 m/s in the northern polar region and 9.8 m/s at the south. Assuming that polar cyclones described by Adriani et al. (2018, https://doi.org/10.1038/nature25491) are in rigid motion with respect to System III, tangential speeds in the interior of the vortices increase linearly with distance from the center. The annulus of maximum speed for the main circumpolar cyclones is located at approximatively 1,000 km from their centers, with peak cyclonic speeds typically between 80 and 110 m/s and ~50 m/s in at least two cases. Beyond the annulus of maximum speed, tangential speed decreases inversely with the distance from the center within the Southern Polar Cyclone and somewhat faster within the Northern Polar Cyclone. A few small areas of anticyclonic motions are also identified within both polar regions. [ABSTRACT FROM AUTHOR]

Downburst winds cause significant threats for many structural systems. Most failure reports of transmission line systems point to downburst events rather than other types of wind events. These events produce the highest wind speeds at low elevations and the shape of terrain topology is one of the main parameters that significantly changes the distribution of the surface wind speeds. The main objective of this study is to investigate the profiles of downburst wind speeds as they pass over real topography, and then to provide guidance for the design of transmission line systems in similar terrains. Numerical simulations of downburst wind flow over two samples of real topography were conducted and the consequent changes in horizontal and vertical downburst wind speeds were investigated. [ABSTRACT FROM AUTHOR]

Failures of roofing systems occur due to high local suctions on tiles or shingles, or because of a different failure mechanism triggered by high local wind velocities near the roof surface. In the latter case, the local velocity can induce positive pressures on the lip of a windward facing shingle or tile, which are transmitted underneath, adding to the external surface negative pressure and causing an increase of the net uplift force. Building codes provide estimates of the peak pressure coefficients (peak C p ) based on 3-s gust in the oncoming wind at the roof height. As an approximation, these coefficients are generally taken to be independent of roof height and exposure. This implies that wind tests of roofing system behaviour carried out at one roof height can be used to infer the system behaviour for other roof heights. One of the main objectives of the present study was to examine the validity of this approximation. Regarding the second failure mechanism discussed above, knowledge of surface wind speed is a key element to assess the uplift forces on shingles. Building codes do not address the wind velocities close to the roof surface and estimate it based on the approach wind speed in terms of a wind speed ratio. So the second objective of the present research was to examine the ratio of local wind velocity close to the roof surface to the velocity at roof height in the approach flow and investigate the effect of height on the velocity ratios. Wind tunnel tests were performed on four different gable-hip roof buildings, at various wind directions. Both surface pressures and near-surface velocities were measured and normalized with respect to upwind flow conditions at mean roof height. The results confirm that the velocity ratios and peak C p values on the gable roof do not vary markedly with building height with no more than 10% change found at most locations. For the velocity ratios a similar conclusion was reached on the hip roof. However, for the C p values in the corner zones of the hip roofs increases with height were identified and further investigation is recommended. [ABSTRACT FROM AUTHOR]

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In this study, the probabilistic collocation method (PCM) is proposed to construct a stochastic correlation model of wind speeds at neighbouring wind farms and solve probabilistic power flow (PPF) of South Australia (SA) grid. Based on the historical sampled wind source data, the model is developed to reduce the number of uncertain parameters of the power system model by considering the spatial correlation of wind speeds between neighbouring wind farms. Furthermore, this model aims to increase the computational efficiency of PCM when dealing with PPF simulation. Finally, the computation efficiency and accuracy of the PCM, compared with traditional Monte Carlo simulation method, are validated by the simulation results of aggregated power flow model of SA case studies. [ABSTRACT FROM AUTHOR]

This study presents the impact on power system frequency control in small power systems based on different generator topologies with a large penetration (50%) of variable speed wind turbines. The impact of a proposed controller is investigated versus various wind speeds. In particular, wind speeds with an average wind speed just below rated wind speed proves to cause the worst frequency fluctuations regardless of the type of backup generation topology investigated during 50% wind‐penetration ratio. For this wind‐speed session and a hydro‐based system, the proposed control system improves the frequency duration outside of the specified range [49.9, 50.1]Hz from 81 to 53% while reducing its delivered energy by only 6%. Furthermore, the proposed control reduces the absolute value of requested reserve by 49% from the hydro unit responsible for primary frequency control. [ABSTRACT FROM AUTHOR]

Wind energy systems with permanent magnet generators, especially axial flux permanent magnet generators (AFPMG), have been quite popularly studied and employed recently. However, a known shortcoming of such systems is that they can operate efficiently only in a very limited range of wind speeds, which corresponds to about 70 to 110% of the rated speed of the generator employed and the energy available outside of this wind speed bracket is not accessed at all, and in fact, wasted. Moreover, the absence of any means of excitation control to maintain a regulated output voltage under varying speed conditions calls for expensive power converters. This study presents a novel methodology to obtain a constant output voltage from an AFPMG under varying wind conditions, through the integration of field poles and their control, along with modifications in stator winding. This significantly enhances the power extraction capability of the system over a much wider operational range (corresponding to 25–125% of the rated speed) while eliminating the requirement of a DC–DC converter to maintain constant output voltage. The details of the design of the constant voltage AFPMG and the results establishing the effectiveness of the methodology have also been presented. [ABSTRACT FROM AUTHOR]

In order to evaluate potential benefits of new green shipping concepts that utilize wind power as auxiliary propulsion in ships or of offshore wind energy harvest, it is essential to have reliable wind speed statistics. A new method to find parameters in the Weibull distribution is given. It can be used either at a fixed offshore position or along arbitrary ship routes. The method employs a spatio-temporal transformed Gaussian model for wind speed variability. The model was fitted to 10 years’ ERA-Interim reanalysis data of wind speed. The proposed method to derive Weibull distribution is validated using wind speeds measured on-board by vessels sailing in the North Atlantic and the west region of the Mediterranean Sea. For the westbound voyages in the North Atlantic, the proposed method gives a good approximation of the observed wind distribution along those ship routes. For the eastbound voyages, significant difference is found between the observed wind distribution and that approximated by the proposed method. The suspected reason is attributed to the ship routing decisions of masters and software. Hence, models that consider only the wind climate description need to be supplemented with a method to take into account the effect of wind-aware routing plan. [ABSTRACT FROM AUTHOR]

This article shows how undisturbed wind streams undergo complex transformations in speed and direction as they interact with different features in various areas of Krasnoyarsk City. Fifteen years of data from urban monitoring stations were collected, averaged and analyzed, and these data show how buildings' layout determines the number of possible wind speeds and directions at specific monitoring points. Wind speeds at some monitoring stations can increase up to 40% as compared to the undisturbed wind flow speed at the meteorological station. But some urban points have 300% more calm periods than at the station outside the city. This paper shows the complete transformation of the undisturbed wind flow caused by non-uniform relief and building arrangements. These results can be used to verify numerical simulation models of air pollution dispersion and to use this information to better parametrize a wide range of problems of wind flows in urban areas. [ABSTRACT FROM AUTHOR]

In 2013, the National Oceanic and Atmospheric Administration (NOAA) brought to operations a synthetic aperture radar (SAR)-derived subkilometer resolution wind speed product. This transition from research to operations comes 35 years after the 1978 launch of the US Seasat satellite, which demonstrated that radar backscatter from active microwave instruments in orbit can provide detailed information about ocean surface waves, winds, and sea surface height. NOAA's initial source of data for operational SAR winds is Radarsat-2, which was launched in 2007 by the Canadian Space Agency. In this paper, we discuss the history of our understanding of the relationship between microwave measurements, particularly SAR measurements, and wind speed, and how a spaceborne instrument first designed to measure ocean waves is now routinely used to derive wind speeds.

Wind and wave characteristics and their long-term variability in the Black Sea over a period of 31 years are investigated in this study. The state-of-the art spectral wave model SWAN is implemented to perform a 31- year wave hindcast in the area of interest. The simulation results are used to assess the inter-annual variability and long-term changes in wind and wave climate in the Black Sea for the period 1979–2009. The SWAN model is forced with the Climate Forecast System Reanalysis (CFSR) winds. The model is calibrated and validated against available wave measurements at six offshore and near-shore locations spread over a large region in the Black Sea. The calibration was performed by tuning parameters in the white-capping and wind input formulations against available measurements for 1996 at three offshore locations (Gelendzhik, Hopa, and Sinop). The validation was carried out using measured data, at Gelendzhik, Hopa, and Sinop offshore locations, Gloria drilling platform and Karaburun and Filyos near-shore locations. From the 31-year simulation results, the long-term spatial distributions and changes of the mean wind and mean and maximum wave characteristics and their inter-annual variabilities were determined. The calibration improved SWAN model performance by 11.6% for H m0 and 3.3% for T m02 on average at three locations. The mean annual significant wave height (H m0 ) and mean wind speed (WS) indicate the occurrence of higher wave heights and wind speeds in the western Black Sea compared to the south eastern coasts of the Black Sea. The coefficient of variation over the Black Sea for H m0 and WS shows that the variability for H m0 is higher than that of WS. It is also observed that the variability for H m0 is higher in areas (such as offshore Gelendzhik, Russia) where the variability of WS is high. Besides, the storms mentioned in the previous studies (such as Galabov and Kortcheva, 2013 ; Tarakcioglu et al., 2015 ) are observed in four interesting characteristic areas with maximum H m0 determined in this study over the Black Sea. [ABSTRACT FROM AUTHOR]

It is a challenging task to simulate the turbulent and separated flow around a rotating twisted wind turbine blade. In this study, the open source CFD package OpenFOAM was used in order to investigate the aerodynamics of the NREL phase VI rotor by solving the three-dimensional Reynolds averaged Navier-Stokes (RANS) equations. During this study, steady-state simulations for multiple upwind configurations of the wind tunnel experiment were conducted. The results are then shown in comparison with those obtained by other researchers and also measurements. For the purpose of verification and validation, aerodynamic key parameters such as power, thrust and pressure distributions at different spanwise sections along the blade are used. Furthermore, the quality of the mesh was verified by using a grid independence test based on the grid convergence index and grid resolution test. The results for a constant pitch at varying wind speeds showed that the present simulations consistently and accurately predicted the experimental data. [ABSTRACT FROM AUTHOR]

Information about wind characteristic together with the analysis of its potential are a key step when it comes to planning and performance estimation of wind energy projects. In the current study, hence, a statistical analysis on wind energy potential and wind characteristics over the coasts of the South Western Black sea is carried out. The aim is to determine fields where wind force is strong and consistent for energy production along south western coasts of the Black Sea. For this purpose, seven meteorological stations (Kumköy, Şile, Akçakoca, Zonguldak, Amasra, Cide, İnebolu) from west to east are selected, and 10 year wind data acquired from TSMS (Turkish Meteorological Service) measured hourly at a height of 10 m were used. Annual, seasonal, monthly and diurnal average wind speed and power density variations are evaluated at all stations, after which conclusions on dominant wind directions and frequency distributions at all sites are made. Based on overall results, Amasra and İnebolu indicated the highest potential of wind power among the other sites with Amasra having about 159 W/m2 maximum yearly average wind power density and about 1392 kWh/m2/year maximum yearly average energy density. [ABSTRACT FROM AUTHOR]