Changes In Wind Speed Research Articles

Imputation based wind speed forecasting technique during abrupt changes in short term scenario

AbstractIt is tough and complex to forecast wind speed due to its intermittent and stochastic nature as well as sudden and abrupt variations in the wind speed. Further, it is required to handle the variety of scenarios e.g. cyber‐attacks, unexpected power device malfunction, communication/sensor outages etc. that can cause the missing data.This paper proposes and employs a de‐noising autoencoder algorithm for wind speed forecasting to ensure the handling of missing data information. At the next step, the data is processed via variational mode decomposition technique to mitigate the noise and improves the model's prediction accuracy. Furthermore, the bi‐directional long‐short term memory deep learning approach is tied with convolution neural network to increase prediction accuracy and anticipating the sudden/abrupt changes in wind speed accurately. Finally, actual wind speed related data is examined to scrutinize meticulousness of projected forecast methodology particularly during sudden/abrupt changes in the wind speed. The parameter indicators of the wind speed forecasting technique exhibit the capability of improved predictions under the diversified conditions.

Comment on “Anticyclonic Suppression of the North Pacific Transient Eddy Activity in Midwinter” by Okajima et al.

AbstractAtmospheric energetics is frequently used to diagnose how different atmospheric processes contribute to the development of transient storm track activity. Okajima et al. (2024), https://doi.org/10.1029/2023gl106932 developed an ad hoc method to separate the contributions of cyclones and anticyclones to the energetics using the value of the curvature of the instantaneous local wind. Here, using simple examples in which the physics is exactly known, it is shown that cyclones embedded within a constant zonal flow exhibit large regions with anticyclonic curvature despite the absence of any real anticyclones. Using the method of Okajima et al., a large fraction of the eddy kinetic energy is erroneously attributed to being associated with anticyclones. Furthermore, the fraction that is misattributed varies substantially with changes in the background wind speed. It is concluded that using the curvature to separate energetics contributions from cyclones and anticyclones is not likely to be physically meaningful.

A neural network model for predicting the temperature of insulated overhead lines

In this work, we develop a neural network model based on experimental heating and cooling curves of insulated wires of overhead lines under changes in wind speed and its direction relative to the wire axis. Insulated SIP-3 wire used in overhead lines was investigated. A multilayer perceptron neural network was employed to model the process of heating and cooling of insulated wire under changes in wind speed and its direction. The average absolute error was taken as a criterion for evaluating the prediction accuracy of wire core and insulation temperatures. The main parameters of the developed neural network model include the number of hidden layers and neurons in each hidden layer, the degree of regulation, and the regulatory rigidity of the model. The modelled heating and cooling curves of insulated wire were compared with those obtained experimentally. The average absolute error was equal to 1.74 and –4.08°C for the predicted core and insulation temperatures, respectively. The difference between the heating curves at low wind speeds was found to range within 9°C. It was shown that an increase in wind speed leads to a decrease in the difference between the curves. Our analysis showed that neural network models used for predicting variations in the temperature of insulated overhead lines should be trained using a larger number of input parameters. This is the main prerequisite for high prediction accuracy of such models, when the difference between the simulated and experimental data does not exceed 5%.

Maximum power point tracking control of wind turbines based on speed hysteresis loop to reduce drive-train loads

By adding compensation torque based on the optimal torque, the torque compensation control method expands the unbalanced torque at varying wind speeds, thereby improving the maximum power point tracking (MPPT) performance of wind turbines (WT). However, while improving the wind energy capture efficiency, such methods will lead to drastic fluctuations of generator torque, resulting in significantly increased drive-train loads. To solve this problem, based on the amplitude-frequency characteristics analysis of the WT system transfer function, it is found rotor speed information can not only reflect the main trend of wind speed changes, but also has the characteristics of not being easily affected by the high-frequency component of wind speed. Therefore, setting compensation torque according to it can effectively alleviate the above phenomenon. On this basis, the MPPT control of WT based on speed hysteresis loop to reduce drive-train loads is proposed. The speed information is used to replace the torque information to set the compensation torque amplitude term, and the speed hysteresis loop is introduced to improve the design of the compensation torque symbol term, which can significantly decreased drive-train loads without compromising on power capture. Finally, the effectiveness of the proposed method is verified by the experiments.

Study on Multi-Parameter Variation of Smoke Flow in Inclined Roadway Fire

ABSTRACT Based on the fluid similarity theory, a “Mine inclined roadway fire simulation experimental system” with similarity ratio of 1:20 is established. The temperature, velocity, density and dynamic pressure of fire smoke under different inlet wind speed (0.5 m/s, 1.0 m/s, 1.5 m/s) were tested and analyzed, and the distribution of temperature, velocity, density and dynamic pressure of inclined roadway during fire was simulated and analyzed by Ansys numerical simulation software. The research shows that: The higher the inlet wind speed, the faster the heat diffusion and the temperature field tends to be flat and long, the wind speed changes in advance and the change is drastic, the gas density decreases, the dynamic pressure first decreases and then increases and then tends to stabilize, but the change trend of temperature, wind speed, gas density and pressure in the overall combustion process remains unchanged. The numerical analysis results are in good agreement with the experimental results. By studying the change law of smoke temperature, velocity, density and dynamic pressure of coal mine inclined roadway fire, the theory of coal mine roadway fire is further perfected, and the level of coal mine fire prevention and rescue is improved.

Nonlinear unsteady aerodynamic forces prediction and aeroelastic analysis of wind-induced bridge response at multiple wind speeds: A deep learning-based reduced-order model

Machine learning-based aerodynamic reduced-order models (ROMs) combine high accuracy with extremely low computational costs, making them highly effective in predicting nonlinear and unsteady bridge aerodynamic forces. Although several machine learning-based nonlinear aerodynamic models have been developed, the majority are built on a single wind speed parameter. However, in nonlinear aerodynamic prediction and aeroelastic analysis of bridges, the variability in incoming wind speed significantly influences the computed results. A ROM relying solely on a single wind speed lacks the ability to accurately forecast the intricate dynamic behaviors arising from changes in wind speed. When the incoming wind speed changes, the model's prediction accuracy significantly decreases. Usually, it is necessary to establish a new database and train a new model, which not only increases time and cost but also greatly reduces the convenience of the ROM. Addressing this challenge, this study proposes a multiple-wind-speed (MWS) nonlinear unsteady bridge aerodynamic model based on the LSTM deep neural network. Taking the Taohuayu Yellow River Bridge in the Henan Province of China as an example, the modeling process of the proposed MWS-ROM is demonstrated, along with non-linear aerodynamic predictions of the deck under various conditions and aerodynamic-elastic analysis of the deck under different wind speeds. The research results show that the trained LSTM network can accurately predict the nonlinear aerodynamic forces of bridges under single and double degrees of freedom vibration conditions. The MWS-ROM performed well in predicting convergent vibrations at low wind speeds and limits cycle oscillations at high wind speeds, aligning closely with results from the CFD full-order model. Compared to CFD, the aerodynamic ROM based on the LSTM network significantly enhances computational efficiency, consequently boosting the convenience and efficiency of bridge flutter analysis. Additionally, the methodology proposed herein can be extended for wind-induced vibration control and response prediction in other types of deck sections.

Comparative examinations of wind speed and energy extrapolation methods using remotely sensed data – A case study from Hungary

Exact knowledge of wind energy potential is a fundamental issue in wind energy utilization. The vertical changes in wind speeds, that is, the wind profile, have a predominant impact on the wind energy available at a location because the kinetic energy of moving air is proportional to the square of the wind speed. Roughness describes the resistance of a 3D surface to moving air. The exponent α of the power law of Hellmann and the roughness length (z0) are two parameters that describe the effects of the roughness of the surface on the wind profile. They can be used for the vertical extrapolation of wind speeds. The exponent α can be determined using multiple height level wind speed measurement data, whereas a reliable technique for the calculation of the roughness length requires detailed knowledge of the 3D geometry of the measurement site. In the present study, the exponent α was calculated based on SODAR wind speed measurements, while (z0) was determined using a combination of GIS and UAS-based aerial survey methods. Wind speeds measured at 50 m were extrapolated for height levels of 80, 90, 100, 110, and 120 m using dynamic power law exponent values. Wind power was determined using the power law (method V1), roughness length (method V2), frequency distribution (method W-RF), and gamma distribution (method W-G), and Windographer software was compared to the values calculated from the empirical (measured) wind speeds. A comparative statistical analysis of the datasets of the power law and roughness length methods on monthly/diurnal, annual/diurnal, and month/direction contexts showed no significant differences at all height levels. Differences can be detected in the distribution of the signs of the differences at heights of 80 and 120 m for the entire dataset. Underestimation was dominant with a significant frequency (over 70 %) in the case of both methods and heights. There were no significant differences between the wind power estimations provided by the different methods, and all the methods involved in the study underestimated the wind speeds and wind energy potential for each height level. Methods V1 and V2 can be used alternatively, depending on the input data available for analysis. The major advantage of method V2 is that it provides the same accuracy as V1, which requires a UAS-based aerial survey at the beginning, but continuous wind measurements must be performed at a lower height only. This means that there is no need for a high measurement tower, which makes the measurements simpler, more cost-effective, and causes much less disturbance to the environment. Another important advantage of the methods presented here is that they use a dynamic approach of power law exponent values that provide a more realistic estimation of wind speed and energy on a diurnal scale.

Spatiotemporal distribution of global wind erosion over the past four decades

Abstract Wind erosion is a critical environmental issue that degrades land and air quality, affecting global ecosystems, agriculture, and human health. Yet, on the global scale, the long-term spatial variability and controlling factors of wind erosion remain highly uncertain. Here, we develop a high-resolution spatiotemporal dataset of global wind erosion from 1980 to 2020 using the Revised Wind Erosion Equation model, integrated with comprehensive meteorological, terrestrial ecology, and soil datasets. Our analysis indicates that wind erosion annually impacted 359 ± 25 petagrams of soils worldwide during this period. Approximately 70% of this erosion occurred in just ten countries, predominantly in Africa and the Middle East. Due to higher erosion intensities, pasturelands, accounting for 28% of all non-barren land use types, disproportionately contributed to 70% of the erosion in these areas. Furthermore, our analysis highlights an upward trend in global wind erosion over the past four decades, with affected areas expanding worldwide. Although our study reinforces that changing wind speeds and a drier climate are central factors impacting global wind erosion, we find that increasing erosion intensities in pasturelands may also exacerbate erosion in North Africa, South America, and East Asia. This has broad implications for soil erosion issues that impact food productivity, human health, and ecosystem stability. This research provides insights for developing wind erosion warnings and targeted mitigation strategies, supporting global efforts to combat environmental degradation and promote sustainable development.

TRACER Perspectives on Gulf-Breeze and Bay-Breeze Circulations and Coastal Convection

Abstract This study explores gulf-breeze circulations (GBCs) and bay-breeze circulations (BBCs) in Houston–Galveston, investigating their characteristics, large-scale weather influences, and impacts on surface properties, boundary layer updrafts, and convective clouds. The results are derived from a combination of datasets, including satellite observations, ground-based measurements, and reanalysis datasets, using machine learning, changepoint detection method, and Lagrangian cell tracking. We find that anticyclonic synoptic patterns during the summer months (June–September) favor GBC/BBC formation and the associated convective cloud development, representing 74% of cases. The main Tracking Aerosol Convection Interactions Experiment (TRACER) site located close to the Galveston Bay is influenced by both GBC and BBC, with nearly half of the cases showing evident BBC features. The site experiences early frontal passages ranging from 1040 to 1630 local time (LT), with 1300 LT being the most frequent. These fronts are stronger than those observed at the ancillary site which is located further inland from the Galveston Bay, including larger changes in surface temperature, moisture, and wind speed. Furthermore, these fronts trigger boundary layer updrafts, likely promoting isolated convective precipitating cores that are short lived (average convective lifetime of 63 min) and slow moving (average propagation speed of 5 m s−1), primarily within 20–40 km from the coast.

Changes in turbulent processes caused by atmospheric gravity waves from troposphere

We have determined that changes in temperature and wind speed recorded in the Earth‘s upper atmosphere above tropospheric sources (hurricanes) can be explained by the propagation of atmospheric gravity waves (AGW). We carried out modeling of the propagation of AGW with a period of 65 min and kx=10−5 m−1 using multi-layer methods in a non-homogeneous, non-isothermal atmosphere, taking into account viscosity and thermal conductivity. We obtained that disturbances in the horizontal component of the velocity are five times greater than the increase in the vertical component of the velocity, and temperature changes can reach 30 K. We should note that the disturbances of temperature and pressure as a result of AGW spreading are superimposed onto the usual view of changes of pressure and temperature with the altitude and reach the maximum amplitude in the range from 90 to 100 km. The obtained changes in the temperature of the upper atmosphere and the velocity with height as a result of the presence of AGW made it possible to estimate the values of the coefficients of turbulent viscosity and thermal conductivity in the upper atmosphere of the Earth above tropospheric energy sources. Intensification of turbulent processes was recorded in the range of altitudes from 75 to 100 km.

Defining algal bloom phenology in Lake Erie

Elucidating the impact of global climate change on aquatic ecosystems, particularly through phenological shifts in primary producers, is critical for understanding ecological resilience. Here, we focus on the phenological shifts in chlorophyll as a proxy for algae biomass and primary production in aquatic ecosystems, specifically in Lake Erie as well as concentrations of the toxin microcystin. By tracking temporal changes in each, we identified key phenological phases important to estimate duration, magnitude, and intensity of harmful algal blooms (HABs). Determining which influential biotic and abiotic factors such as temperature, wind speed, nutrient availability, and climate change is most important, is a long-term management need for Lake Erie, which can be explored using our methodology. Our novel statistical framework employing Bayesian generalized additive mixed models described seasonal chlorophyll and particulate microcystin concentration from Lake Erie and our simple geometric method identified the start, peak, and end of algal blooms. This research enhances our understanding of the ecological effects of nutrient pollution on aquatic ecosystems and provides a repeatable method for determining phenological events without the need for user defined cutoffs which aids in the management and mitigation of HABs, safeguarding water quality in regions dependent on lakes for drinking water.

Optimization Design of Bionic Leading-edge Protuberances on Horizontal Axis Wind Turbine Blades

Abstract The complex operating environments of horizontal axis wind turbines has made the phenomenon of blade flow separation more obvious. As a passive flow control method, the bionic humpback whale leading-edge protuberances have been shown to effectively enhance the performance of the wind turbine. This study employs a multi-objective genetic algorithm and Computational Fluid Dynamics method to analyse the impact of leading-edge protuberances on the aerodynamic performance and flow characteristics of the blades. The results indicate a significant improvement in blade performance after optimization in the wind turbine’s output power. The streamwise vortices generated by the bionic protuberances not only reduce the suction surface pressure, but also suppress the spanwise flow over the blade surface. The length of the flow separation Region is reduced from 0.410 to 0.368 radius. In the process of wind speed change, the tangential forces on the bionic blade exhibit a wave-like variation. The bionic protuberance alters the pressure coefficient of the position. Compared with the original blade, the pressure coefficient of the trough sections on both sides of the bionic blade protuberance is improved. In this study, the bionic protuberance applied to the leading-edge of horizontal-axis wind turbine blades is proposed for the first time, and holds practical value for guiding practical applications.

Similarity of the low-occurrence wind profiles within urban turbulent boundary layers of uniform and non-uniform height block arrays

Within urban boundary layers, the safety of pedestrians is markedly affected by wind speed, particularly in urban areas. The characteristics of turbulence above the canopy layers can lead to unpredictable changes in wind speed at the pedestrian level. Therefore, this study analyzes low-occurrence wind speed phenomena above canopy heights for uniform and nonuniform block configurations using wind tunnel experiments (WTE) to understand the background turbulence characteristics which the wind profile is generated by the boundary layer above the canopy. The urban canopy arrays were reproduced using solid blocks arranged in 30 rows in a streamwise direction with a packing density of 25 % at three different heights. An x-type hot-wire anemometer was used to measure the streamwise and vertical velocity components. The low-occurrence values were classified based on wind speed percentiles of 0.1 %, 1.0 %, 99.0 %, and 99.9 % wind speeds. The results demonstrated that above the canopy, there were minor influences of block height variations on the low occurrence factor. The peak factor demonstrated a comparable value between the uniform and nonuniform cases, regardless of the block arrangement. Statistical models based on the Weibull distribution and Gram–Charlier series demonstrating good agreement with the WTE data in predicting the low occurrence and peak factors. This study found that variations in block height have a minor influence on the low occurrence and peak factors within the turbulent boundary layers, implying that we can separate the effect of background turbulence from the local turbulent generation within the urban canopy layers.

Enhanced “Wind‐Evaporation Effect” Drove the “Deep‐Tropical Contraction” in the Early Eocene

AbstractThe equatorward contraction of tropical precipitation, commonly referred to as the “deep‐tropical contraction”, is witnessed in the paleoclimate simulations of the early Eocene. However, the mechanism driving this contraction is still unclear. Based on the energetics framework of the Intertropical Convergence Zone (ITCZ) and the decomposition method of the latent heat flux along with the simulations of a climate system model, CESM1.2, we proposed a novel mechanism responsible for the “deep‐tropical contraction” in the early Eocene. The greenhouse gases‐induced sea surface warming amplifies the sensitivity of evaporation to surface wind speed changes through Clausius‐Clapeyron scaling, leading to an interhemispheric asymmetric enhancement of the latent heat flux. To maintain hemispheric energy balance, the cross‐equatorial atmospheric energy transport must be reduced during the solstice seasons. As a result, the solstitial location of the ITCZ shifts equatorward, causing the “deep‐tropical contraction” in the early Eocene.

Implementation Joule Thief Buck-Boost Converter in A Neodymium Wind Power Plant

Wind power generation is gaining popularity as an environmentally friendly renewable energy source. However, the output voltage of a wind generator usually varies according to the wind speed, requiring a power converter to produce a stable DC voltage. The author of this research aims to implement a Joule Thief Buck-Boost Converter on a neodymium wind power generation system. Joule Thief is a DC-DC converter that has the ability to convert a low input voltage into a higher output voltage, and can maintain a relatively stable output voltage despite changes in the input voltage. In this study, a Joule Thief buck-boost converter is used to regulate the output DC voltage of the neodymium wind generator to remain stable despite the changing wind speed. System testing is done by measuring the output voltage of the neodymium wind power plant. The test results show that the Joule Thief Buck-Boost Converter can maintain the output DC voltage at a stable value of 14V at input voltages above 3V, so the implementation of this converter in neodymium wind power plants is proven effective in producing a stable DC voltage. This research is expected to contribute to the development of a more efficient and reliable wind power generation system.

Study on the Design of Series-Type All-DC Wind Farms Based on Half-Bridge Voltage Balancing Circuits

Offshore wind farms connected in series, with each wind turbine connected in series with one another, enhance the coupling between them. Significant differences in wind speeds between neighboring DC wind turbines (DCWTs) might result in a substantial disparity in the output voltage, hence posing a risk of overvoltage. Nevertheless, implementing voltage-limiting configurations for DCWTs might lead to the dissipation of wind energy, thereby diminishing the wind farm’s capacity to deliver electricity. This work introduces a half-bridge voltage balancing circuit (HVBC) topology as a solution to the issue of DCWT output voltage changes affecting the stable operation of wind farms. The proposed HVBC topology is designed specifically for large-capacity series-connected all-DC wind farms where wind speed variations occur. This design achieves power decoupling for series-connected all-DC wind farms by providing current compensation to the series-connected DCWTs. A control strategy is devised by examining the decoupling principle and operational characteristics of the HVBC. A 60 kV/48 MW tandem-type all-DC wind farm model consisting of six DCWTs in series is built in Matlab/Simulink. The model is then simulated to evaluate its performance under conditions of unequal wind speed, rapid changes in wind speed, and wind turbine failure shutdown. This research verifies the feasibility of the HVBC topology and improves the stability of the series-type all-DC wind farm.

Mitigating crosswind response of a high-speed train passing the end of windbreak walls

The sudden change in wind speed at the end of a windbreak wall poses a significant threat to train safety, as it amplifies train’s responses. This study aims to investigate countermeasures to reduce the maximum unsteady crosswind response of high-speed trains at the end of windbreaks. Wind flow around windbreak walls was systematically examined by particle image velocimetry (PIV), considering both constant and varying porosities. Subsequently, a gust model was proposed to evaluate the wind distributions behind windbreak walls, validated by experimental results. Aerodynamic forces on high-speed train, incorporating windbreak walls with diverse porosities, were assessed by integrating the gust model and the quasi-steady theory. Ultimately, the unsteady crosswind responses were computed employing multibody simulations (MBS), accounting for both solid windbreak walls and those with varying porosities. A noteworthy finding was the reduction of approximately 25 % in the maximum unsteady crosswind response when windbreak porosity varied from 0 % to 80 %, thus affirming the efficacy of windbreaks featuring varying porosities in diminishing unsteady crosswind response. Overall, this study provides valuable insights into the design of windbreaks for high-speed trains, which can improve their safety and performance in strong wind regions.

Study and evaluation of wind power density for the use of small wind turbine under Baghdad conditions

The main aim of this research is to analyze the characteristics of the wind speed and wind power density in Baghdad City within micro-scale meteorological conditions at Mustansiriyah University Meteorological Station (MUMS). Temperature, atmospheric pressure and wind speed data were taken for one year (2016) measured at a height of 18 m above the earth's surface. Hourly, monthly, and seasonal changes in wind speed at an altitude of 30 m were estimated using a power law. The mean diurnal and monthly air density was calculated. Different statistical distributions were used, including the Rayleigh, Gamma and Weibull distributions, and the best distribution function was selected to evaluate the wind power density in the study area. The results showed the highest monthly mean of wind speed recorded in June and July. Therefore, these months have the highest wind power density. The lowest monthly mean of wind speed and wind power density was observed in December. The maximum and minimum values of air density were recorded in December, January and July, August, respectively. The monthly variation of the shape parameter (k) ranges between 0.99 - 1.81, while the monthly variation of the scale parameter(c) ranges between 1.07 - 2.3 m s-1. It was also found that the Weibull distribution was more accurate than the Rayleigh and Gamma distributions. The prevailing wind direction is northeast (NE) and east-northeast (ENE) most of the time. The research results showed that the study area is not suitable for using wind energy to generate energy.

Experimental study into the effects of pitch and coning angles on the flight performance of the natural samara.

Using their light wing and through the use of a leading-edge vortex (LEV), autorotating samaras can generate high lift while descending at extremely low speeds. But the flight performance of the samara, with respect to the wide design envelope, is still not well understood. Therefore, this paper aims to experimentally assess how the flight performance of three natural samara wings varies with differing wind speeds and flight conditions. The tests were conducted within a vertical wind tunnel and a novel rig was devised to effectively measure the vertical thrust and rotational rate of the autorotating samara at near frictionless conditions. Furthermore, a bespoke hub was implemented to control the coning and pitch angles of the samara wing. The tests generated a novel and comprehensive set of experimental data of autorotating samaras with changing wind speed, coning and pitch angles. The results also revealed that coning angles between 5 and 15 degrees can increase the vertical thrust produced by the samara by up to a maximum of . Additionally, it was found that samaras operate at extremely low pitch angles between -0.7 and -2.6 degrees to maximise their thrust, even though the conditions are close to the autorotational stability boundary.

Evaluation of future wind climate over the Eastern Mediterranean Sea

The aim of this study is to evaluate wind climate characteristics in the Eastern Mediterranean Sea until the end of the 21st century using the wind fields simulated by the EURO-CORDEX Regional Climate Models (RCM), namely the Rossby Centre regional atmospheric model (version RCA4). Long-term averages, long-term trends, and long-term variability in wind characteristics under two Representative Concentration Pathway (RCP 4.5 and 8.5) scenarios were assessed for two future periods: the near future for the years 2021–2060 and the middle future for the years 2061–2100. Relative to the historical period, the most remarkable changes in the mean wind speeds were projected under the RCP 8.5 scenario in the middle future in the central and southern Aegean Sea (exceeding 5 % increase) and in the eastern and northern Levantine basin (up to 5 % decrease), compatible with the definition of the climate scenarios as the RCP8.5 scenario assumes a rising radiative forcing until 2100. The changes in extreme wind characteristics are more noteworthy in agreement with the indicators of climate change (i.e., an increase in the intensity and the frequency of extreme events). 100-year return period wind speed increases by about 29 % in the western Levantine basin under the RCP 8.5 scenario while the most drastic decrease in 100-year extreme wind speed was found in the central Levantine basin with a reduction of exceeding −29 % for the middle future period under the RCP 8.5 scenario. These decreasing and increasing behaviors in extreme wind speeds are expected in the study area as the Mediterranean is affected by many climate systems.