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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]

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 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]

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]

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]

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]

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]

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]

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]

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]

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]

The wind directionality factor, Kd, is a nondimensional quantity smaller than unity that reflects the fact that the climatologically Kd and aerodynamically or dynamically most unfavorable wind directions typically do not coincide. The ASCE 7-10 standard specifies for buildings a directionality factor d 0.85, although no justification appears to have been adduced for this value in the literature. This Kd paper presents a more informed discussion of this topic by the engineering and codification communities. The results of this work show that the directional factor d varies as a function of type of wind storm, geographical location within an area with a given type of wind Kd climate, type of wind effect (e.g., local pressures, internal forces in members of wind force resisting systems, global shear or torsion), and position of the wind effect being considered in the structure. These results suggest that, in most if not all cases, the dependence of the directionality factor on mean recurrence interval of wind effects is weak, and they confirm a recent finding that d values are larger Kd for hurricane-prone than for nonhurricane regions. For pressures at individual points on building envelopes, the value Kd = 0.85 is typically found to be adequate for hurricane-prone regions and conservative for nonhurricane regions. For internal forces in wind force resisting systems (e.g., frames), the value Kd = 0.85 is typically adequate for nonhurricane regions while Kd = 0.90 is required for hurricane-prone regions, in spite of its conservatism in some situations. Finally, for global effects, such as building base shears and global building torsion, the values Kd = 0.90 and Kd = 0.95 are appropriate for nonhurricane and hurricane-prone regions, respectively. [ABSTRACT FROM AUTHOR]

Tornado research has significantly advanced our understanding of tornadoes and their impacts. However, knowledge of the near-surface (<10 m above ground) wind speeds in tornadoes is still lacking, despite its importance to both the engineering and meteorological communities. Because near-surface wind speeds in tornadoes are typically out of the reach of radar, and in-situ measurements are difficult to obtain, the peak near-surface wind speeds are currently estimated using methods based upon the damage inflicted. In this study, a near-surface wind field model is developed using tree-fall patterns observed following the 22 May, 2011 Joplin, Missouri tornado. This wind field is compared to over 1200 individual wind speed estimates throughout the tornado path, obtained from a ground survey of the building damage using the Enhanced Fujita (EF) scale. The comparison demonstrates for individual structures that the estimated tree-fall wind speeds are consistently higher than wind speeds estimated using the EF scale. Differences between the two methods become more pronounced for individual structures closer to the tornado center. [ABSTRACT FROM AUTHOR]

Weibull distribution has been one of the most widely used distribution to determine potential of wind energy. Many different numerical methods can be used to estimate the parameters of the Weibull distribution. The L-moment method (L-MoM), which has not been used extensively in the previous literature about wind energy for the estimation of wind speed parameters relevant to the Weibull distribution has been presented and this method has been compared to the Moment method (MoM) and Maximum Likelihood (ML) method. Monte Carlo simulation has been used to compare the methods used in the estimation of the shape ( k ) and scale ( c ) parameters for a Weibull distribution. Moreover, MoM, L-MoM and ML parameter estimation methods have been used in analyzing an actual data set. Wind power densities have also been calculated with the help of estimated parameter values. We showed that, distribution is skewed to the right or is symmetrical and n ≥100 the ML method is preferable in comparison to other methods in the estimation of the shape ( k ) parameter. The L-MoM method which we presented in this study may be beneficial for research using small sample sizes. [ABSTRACT FROM AUTHOR]

A bistatic radar at X-band (11 GHz) using opportunity signals (Passive Reflectometry and Interferometry System (PARIS) concept implementing the interferometric technique) has been developed and tested in a coastal-based experimental setup. Digital satellite TV signals broadcast from geostationary orbit have been used as sources of opportunity, and correlation waveforms have been collected at different receiver bandwidths. Calibration algorithms to compensate instrumental errors have improved our observables and allowed us to obtain delay measurements with a precision of about 10 cm for wind speeds in the range of 3 m/s. A statistical analysis of the measurement noise is used to determine the quality of the obtained observables. This paper also discusses the opportunities of the PARIS concept applied at higher frequency band and with stronger signals. [ABSTRACT FROM PUBLISHER]

Abstract: We propose a general method for predicting multiple steps ahead of our target system and estimating simultaneously the prediction errors in a real time. The requirement of the proposed method is that we have a time series of the target system. We demonstrate the method by artificial data, real wind speed data, and real solar irradiation data. [Copyright &y& Elsevier]

The quality of measurements of wind velocities in a wind tunnel depends heavily on the proper use of the instruments used to obtain them, for that reason is very important to know the features of these instruments. The hot-wire anemometer is the most used instrument in wind velocity measurements and their fluctuations on a wind tunnel. The features of wind velocity fluctuations are very important because for the simulation of the atmospheric boundary layer in a wind tunnel is necessary to develop a physical model of atmospheric turbulent flow, so that, the parameters which characterize them are reproduced as closely as possible inside the wind tunnel. The aim of this paper is to describe the characteristics of hot-wire anemometer at constant temperature which produce the characteristics of fluctuating wind speeds and exemplify the application of CTA to obtain speeds in the wind tunnel of the Aerodynamics Laboratory Constructions of UFRGS , Brazil. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to discuss issues associated with ASCE 7-10 standard methods for determining wind loads on buildings and other structures that warrant comment, correction, or improvement. The assessment is intended to serve as a resource in the development of a new version of the ASCE 7 standard and to stimulate a wider participation in that development by the structural engineering community. Issues discussed in the paper include: wind speeds in nonhurricane regions; alternative analytical methods for determining wind loads and wind effects on main wind force resisting systems and components and/or cladding; aerodynamic pressure coefficients; pressures on rooftop equipment; component and cladding pressures on arched roofs; and the wind tunnel procedure. It is noted that the ASCE 49 standard essentially covers wind tunnel testing, rather than the wind tunnel procedure, of which wind tunnel testing is only a part. [ABSTRACT FROM AUTHOR]

Abstract: Climate change and depletion of natural resources are serious issues that have potential impact on the economic and social development of countries. In this perspective, the governments world-wide are mobilizing initiatives to exploit renewable energy sources to mitigate increasing demand of energy, volatile fuel prices, and environmental concerns. Renewable energy (wind/solar) based power system is a nature-friendly option for power production to foster sustainable development challenges. In the present study, the economic feasibility of development of 75MW wind power plants (wind farms) in the coastal locations of the Kingdom of Saudi Arabia (K.S.A.) has been studied/reviewed by analyzing long-term wind speed data. Attention has been focused on four coastal locations (Al-Wajh, Jeddah, Yanbu and Jizan) covering the west coast. In general, long-term data indicates that the yearly average wind speed of K.S.A. varies from 3.0 to 4.5m/s at 10m height. The wind farms simulated consist of different combinations of 600kW commercial wind machines (50m hub-height). NREL''s (HOMER Energy''s) HOMER software has been employed to perform the techno-economic assessment. The study presents monthly variations of wind speed, cumulative frequency distribution (CFD) profiles of wind speed, monthly and yearly amount of energy generated from the 75MW wind farms (50m hub-height) at different coastal locations of K.S.A., cost of generating energy (COE, $/kWh), capacity factor (%), etc. The CFD indicates that the wind speeds are less than 3m/s for 45%, 53%, 41%, and 52% of the time during the year at Al-Wajh, Jeddah, Yanbu and Jizan respectively. This implies that wind electric conversion systems (WECS) will not produce energy for about 41–53% of the time during the year. The annual energy produced by 75MW wind farms (50m hub-height) has been found to be 107,196, 81,648, 135,822, and 80,896MWh at Al-Wajh, Jeddah, Yanbu and Jizan respectively. The cost of wind-based electricity by using 600kW (50m hub-height) commercial WECS has been found to be 0.0536, 0.0704, 0.0423, and 0.0711 US$/kWh for Al-Wajh, Jeddah, Yanbu and Jizan respectively. Also, attempt has been made to determine the capacity factor (CF) of wind-based power plants, the CF has been found to vary from 12% to 21% for different locations of the Kingdom. [Copyright &y& Elsevier]

Abstract: An online multi-step prediction method is constructed based on data streams, for which using all observed data points for prediction is impractical. The proposed method is superior in prediction accuracy and computational time, at various prediction steps, compared to two simple extensions of Kwasniok and Smith [F. Kwasniok, L.A. Smith, Phys. Rev. Let. 92 (2004) 164101]. We apply our proposed prediction method to artificial data sets generated from the Lorenz-63 model and to measured wind speed data streams. [Copyright &y& Elsevier]

Results of microwave radar Doppler spectra from 1-D nonlinear ocean surface at moderate- and low-grazing angles are calculated by the composite surface scattering model. For the large-scale undulating surface description, the narrow-band Lagrange model is used, which takes into account the vertical and horizontal skewnesses. Moreover, the shadow and the curvature effects of large-scale waves on the Doppler spectra are also considered in our calculations. Comparisons of computed curves with experimentally measured Doppler spectra at different incidence angles and at various wind speeds show that the simulated results can fit the measured data well at moderate incident angles. From the simulations, we also find that the hydrodynamic modulation and the horizontal skewness of the large-scale waves can induce remarkable influence on Doppler shift. In addition, when the shadow and the curvature effects of large-scale waves are considered in the calculations, the Doppler shifts grow more quickly and the spectral widths become narrower at low-grazing angles, and this is consistent with the numerical results given by Toporkov in the nonlinear surface case. The conclusions obtained in this work seem promising for better understanding the properties of time-dependent radar echoes from oceanic surfaces. [ABSTRACT FROM AUTHOR]

Wind turbine power converter system (WTPCS) is a crucial device in a wind energy conversion system. This paper presents the new failure rate models and a reliability evaluation technique for the (WTPCS) considering effects of wind speeds, which can be named by the multistate probability analysis method. The case studies on the WTPCS of a 2 MW wind turbine with a permanent magnet synchronous generator are conducted using wind speed data at Lauwersoog and Valkenburg wind sites in Holland. The results indicate that reliability of the WTPCS is affected significantly by variations of wind speed and the rated wind speed of wind turbine. The effectiveness of the proposed method is demonstrated by examples. [ABSTRACT FROM AUTHOR]

Abstract: Lateral correlation analyses are carried out in different scales for two sets of full-scale thunderstorm downburst full wind speed time series. These two sets of data were recorded at the TTU field site, Texas, USA, on June 4 and 15, 2002, respectively. The same data sets were also used in the authors’ previous paper [L. Chen, C.W. Letchford, Proper orthogonal decomposition of two vertical profiles of full-scale nonstationary correlated downburst wind speeds, J. Wind Eng. Ind. Aerodyn., 93(3)(2005) 187–266.], which presents a methodology to model downburst vertical profiles. The statistical procedures utilized in [7], such as the POD technique, the wavelet shrinkage for time-varying mean inference, the two-stage weighted moving-average method for time-varying variance inference and the Priestley''s EPSD estimator, are also employed in this paper and their details are thus omitted. While in [7] the authors employed the proper orthogonal decomposition (POD) to reduce the dimensions, POD in this article is employed to measure the degree of the correlation between two deterministic time series. Conventionally, wind speeds are decomposed to a time-varying mean speed and a nonstationary fluctuating speed by virtue of wavelet shrinkage [7]. Time-varying mean speeds are in the largest scale, which are essentially due to translations of storms and radial velocities of spreading flow. It was observed that the time-varying standard deviations [7] of fluctuating speeds are basically driven by time-varying mean speeds other than small-scale turbulence. Therefore, time-varying standard deviations are considered in the medium scale. Finally, the modulated fluctuating speeds are viewed in the smallest scale and due to small-scale turbulence. It is found that (1) the two lateral profiles are fully correlated and almost evenly spatially distributed in the largest and medium scales with more than 96% of the total energy; (2) they are uncorrelated in the smallest scale since the measurement locations are at least 263m apart. [Copyright &y& Elsevier]

Abstract: The paper proposes a novel analysis framework for nonstationary wind speeds, from which accumulated results can potentially lead to or enhance empirical nonstationary wind speed models such as the hybrid one for downbursts in (Eng. Struct. 26 (2004) 619). This framework is motivated by the proper orthogonal decomposition (POD) technique and consists of four major steps: separation, POD, approximation and property inference. In the first step, the original wind speed time histories are separated into their time-varying mean speeds and fluctuating speeds through wavelet shrinkage, which is a promising new tool for smoothing; fluctuating speeds are further expressed as the product of their time-varying standard deviations and normalized fluctuating speeds with unit variance. In the second step, the POD is applied to the time-varying means, standard deviations and normalized fluctuation. In the third step, by properly selecting the number of retained modes, the original time series can be approximated to a numerical model. Finally, wind properties such as velocity vertical profiles and turbulence vertical profiles can be calculated from the model. The POD employed herein is a specific POD for arbitrary multivariate data representation. The normalized fluctuations are characterized by both their power spectral densities (PSD) and evolutionary power spectral densities (EPSD). The concept of EPSD for nonstationary processes is briefly presented and one EPSD estimator is given. Specifically, the PSD/EPSD of an original process is related to the PSD/EPSD of the principal coordinate process obtained by the POD. This framework is applied to two sets of nonstationary full-scale thunderstorm downburst wind speed time series. Many appealing downburst properties are obtained and the benefit of the POD is demonstrated. [Copyright &y& Elsevier]

To achieve structures that are risk-consistent, structural reliability methods must be used that account for uncertainties with respect to the relevant parameters affecting the estimation of wind effects. In this paper, we obtain measures of uncertainties in the estimation of the wind speeds upwind of structures. These uncertainties are due to incomplete knowledge with respect to the relevant extreme climatological and micrometeorological parameters. Advances in wind engineering and improvements in computational capabilities now make it possible to improve upon earlier estimates available in the literature. The work presented in this paper is a phase of a broader NIST project aimed at developing user-friendly software for the estimation of probabilities of failure of low-rise structures subjected to wind loads. [Copyright &y& Elsevier]

A recent paper updated the methodology for the analysis of extreme wind speeds in mixed climates originally proposed in 1978 by Gomes and Vickery (GV) to take advantage of recent improvements in methodology and available data records. This involved the separation of independent sub-annual maxima by storm mechanism, determining the Weibull shape parameter k, preconditioning for fastest convergence using k, fitting each mechanism to the Fisher–Tippet Type I distribution and synthesising the composite extreme-value distribution. That work did not address the confidence of the composite distribution. In this paper, the “bootstrap” method was used to derive the confidence limits of the composite distribution for the revised methodology, as well as for the original GV methodology, illustrated by data from Onslow and Brisbane in Australia. It is shown that the composite distribution can be directly fitted to the observations, without prior separation by storm mechanism, when each mechanism is adequately represented in the observations. However, separation by causal mechanism prior to analysis should always be the preferred option when suitable data records are available. [Copyright &y& Elsevier]

The Wind Engineering Mobile Instrumented Tower Experiment (WEMITE) successfully gathered high-resolution wind speed data from within Hurricane Bonnie as it made landfall near Wilmington, North Carolina, on 27 August 1998, at 04:00 UTC. This data is used to inspect the variations in turbulent characteristics of the wind during the passage of the storm. Specifically, turbulence intensities, integral scales, gust factors and power spectral densities are evaluated. Results indicate there is general agreement with the Krayer/Marshall gust factor curve, additional low-frequency energy in the longitudinal power spectral density compared to various model spectra, and a wide variation in integral scales even within the same roughness regime. [Copyright &y& Elsevier]

The methodology for the analysis of extreme wind speeds in mixed climates originally proposed in 1978 by Gomes and Vickery is updated to take advantage of recent improvements in methodology and available data records. The revised methodology is demonstrated for two sites in Australia: Onslow and Brisbane. This work shows that the observed curvature in the upper tail is due to incomplete convergence to the Fisher–Tippett Type 1 asymptote and is not an indicator of Type 3 behaviour as sometimes supposed. It is also shown that moving from a reference epoch of 1 year to an epoch of 50 years frees the method from most of the rate-dependent assumptions, and simplifies the problem to a single, dominant wind mechanism. [Copyright &y& Elsevier]

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 σ U around 〈 U 〉 or, more preferably, a dimensionless coefficient of variation I u = σ U / 〈 U 〉 . The proposed correction outperforms previous methodologies that adjusted k when using 〈 U 〉 only. An unexpected outcome was that upon setting I u 2 = 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 I u 2 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. [ABSTRACT FROM AUTHOR]

This study aims to determine long-term spatial variability of wind and wave characteristics over the Sea of Marmara. For this purpose, we produced four different wind and wave datasets for a period of 40 years (1979–2018) using the calibrated and default-setting SWAN models forced with both CFSR and ERA-Interim winds and inter-compared. The performance of these datasets is examined against the wave height measurements of 2015 at the Silivri buoy station and 27-year (1991–2018) satellites data (ENVISAT, ERS-1, ERS-2, JASON-1, JASON-2, JASON-3, SENTINEL-3A, SENTINEL-3B, TOPEX). Then, for wind and wave climate analysis, the spatial distributions of the wind and wave characteristics over the study area are determined in terms of seasonal and annual averages. 40-year averages of 95th and 99th percentile significant wave heights, probabilities of being larger than significant wave heights exceeding a critical value, and 40-year maximum significant wave heights are spatially analyzed. Finally, the calibrated SWAN model using CFSR winds presents the most accurate results. Therefore, the effects of different model inputs and settings on the model results are examined by creating spatial distributions of the biases of the other three model results and comparing them to those of the calibrated model results using CFSR winds. The CFSR forced and calibrated model predicts the largest average wind speed and average wave height in the central regions of the Sea of Marmara in comparison with the other three models. The shores of Kapidag Peninsula and Marmara Island are exposed to be with the highest wave conditions. • The most accurate results were obtained for the calibrated SWAN model using CFSR winds (CC model). • Calibration has a large effect on the estimated maximum wave conditions showing about 2 m difference. • Calibration does not show a significant effect in terms of average wave conditions. • The CC model predicts the largest average wind speed in the central regions of Sea of Marmara. • The shores of Kapidag Peninsula and Marmara Island are exposed to the highest wave conditions. [ABSTRACT FROM AUTHOR]

Electricity from renewable energy (RE) sources gained in significance due to green-friendly governmental initiatives in the form of either direct subsidizes, tax incentives or tradable certificates. Thereby, RE generators are incentivized to maximize energy feed-in or the remuneration from governmental subsidizes, meanwhile neglecting any market interaction. Consequently, wind farms are clustered in windy regions. Along with the governmentally initiated integration of RE generation into power markets, the siting of RE generators will change. In wind power dominated power systems that fully integrate RE generators into power markets, wind farms will compete against each other and try to maximize their market value. Hence, wind speed correlations with other wind farms will become increasingly important when choosing a site in a uniform or zonal pricing system. To quantify the impact of market integration on future wind farm siting, an approach is developed that takes into account the local wind potential of a certain site, wind speed correlations to other sites and their installed capacities. An optimization that minimizes the normalized sum of wind power correlations to all other sites and their respective normalized installed wind power capacity is performed. To achieve a predefined minimum energy output, the average wind yield is considered as an additional constraint. The outcome is an optimal wind farm site in a wind energy dominated system. Running this for a given wind power expansion scenario enables decision makers to foresee the spatial development of wind farm installations. To demonstrate the model’s applicability, a case study is performed for Germany. Thereby, wind speed data for four years from the European reanalysis model COSMO-REA6 is used. The results indicate that a full market integration of RE generators will space out more evenly new wind farms. Thereby, wind farms can economically benefit from the non-simultaneity of wind speed. [ABSTRACT FROM AUTHOR]

A procedure is presented for estimating parametric probabilistic models of hurricane wind speeds from existing information on state-of-the-art estimates of wind speeds with various mean recurrence intervals (MRIs). Such models may be needed, for example, for the estimation of hurricane wind speeds with long MRIs required for the performance-based design of structures susceptible of experiencing nonlinear behavior. First, the procedure is applied to the case where that information is obtained from ASCE 7-10 wind maps, and examples are provided of its application to a number of coastal mileposts on the Gulf and Atlantic coasts. Next, the procedure is applied by using, in addition to the ASCE 7-10 information, hurricane wind speeds with 1,000,000- and 10,000,000-year MRIs estimated in a 2011 Nuclear Regulatory Commission (NRC) report. It is then argued that ASCE 7-10 Standard basic wind speeds for New York City are not conservative with respect to their counterparts specified in the standard for other U.S. hurricane-prone locations. Finally, it is shown that, for the randomly selected cases examined here, best-fitting extreme value distributions of hurricane wind speeds typically have finite upper tails of the reverse Weibull type, rather than infinite upper tails of the Gumbel type. This result, if confirmed by additional studies, may help to change the still widely held belief that extreme wind speeds are modeled appropriately only by the Gumbel distribution. [ABSTRACT FROM AUTHOR]