This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn(FLOW Redirection and Induction Dynamics)dynamic wake model.First,the i...This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn(FLOW Redirection and Induction Dynamics)dynamic wake model.First,the impact of wakes on turbine effective wind speed is analyzed,leading to a quantitative method for assessing wake interactions.Based on these interactions,a partitioning method divides the wind farm into smaller,computationally manageable zones.Subsequently,a heuristic control algorithm is developed for yaw optimization within each partition,reducing the overall computational burden associated with multi-turbine optimization.The algorithm’s effectiveness is evaluated through case studies on 11-turbine and 28-turbine wind farms,demonstrating power generation increases of 9.78%and 1.78%,respectively,compared to baseline operation.The primary innovation lies in coupling the higher-fidelity dynamic FLORIDyn wake model with a graph-based partitioning strategy and a computationally efficient heuristic optimization,enabling scalable and accurate yaw control for large wind farms,overcoming limitations associated with simplified models or centralized optimization approaches.展开更多
Establishing power systems with a high share of renewable energy sources is a pivotal step toward achieving a globally sustainable transition to green and low-carbon energy.This study focuses on low-output wind power ...Establishing power systems with a high share of renewable energy sources is a pivotal step toward achieving a globally sustainable transition to green and low-carbon energy.This study focuses on low-output wind power that affects the generation capacity of power systems with a high share of renewable energy sources.Utilizing the Coupled Model Intercomparison Project Phase 6 datasets,a predictive model for low-output wind power was employed to investigate regional trends worldwide.The frequency and duration of low-output wind-power events exhibited increasing trends globally,particularly in East Asia and South America,but not in North America.By 2060,the annual total days with low-output wind power in East Asia and South America could rise to 13 and 5 d,and the maximum continuous duration of low-output wind power could reach 5 and 2 d,respectively.As wind power becomes a primary elec-tricity source,such low output could lead to shortages in energy supply within the power system,trig-gering large-scale power outages.This issue calls for critical attention when establishing power systems with a high share of renewable energy sources.The conclusions provide a basis for analyzing power supply risks and configuring flexible power sources for scenarios with a high share of renewable energy.展开更多
A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical dis...A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical distribution of the two variables may show multimodal characteristics.In this work,a finite mixture bivariate statistical model was designed to describe the statistical properties,which is composed of several components,each with a Weibull distribution and a normal distribution for wind speed and wind shear,respectively,with a Gaussian copula to describe the dependency structure between the two variables.To confirm the developed model,reanalysis data from six positions in the coastal sea areas of China were used.Our results disclosed that the developed joint statistical model can accurately capture the different multimodal structures presented in all the bivariate samples under mixed atmospheric conditions,giving acceptable predictions of the joint probability distributions.Proper consideration of wind shear coefficient variation is crucial in estimating height-dependent wind resource characteristics.Importantly,unlike traditional methods that are limited to specific hub heights,the model developed here can estimate wind energy potential across different hub heights,enhancing the economic viability assessment of wind power projects.展开更多
To investigate the wind⁃induced vibration re⁃sponse characteristics of multispan double⁃layer cable photo⁃voltaic(PV)support structures,wind tunnel tests using an aeroelastic model were carried out to obtain the wind⁃...To investigate the wind⁃induced vibration re⁃sponse characteristics of multispan double⁃layer cable photo⁃voltaic(PV)support structures,wind tunnel tests using an aeroelastic model were carried out to obtain the wind⁃induced vibration response data of a three⁃span four⁃row double⁃layer cable PV support system.The wind⁃induced vibration characteristics with different PV module tilt angles,wind speeds,and wind direction angles were analyzed.The results showed that the double⁃layer cable large⁃span flexible PV support can effectively control the wind⁃induced vibration response and prevent the occur⁃rence of flutter under strong wind conditions.The maxi⁃mum value of the wind⁃induced vibration displacement of the flexible PV support system occurs in the windward first row.The upstream module has a significant shading effect on the downstream module,with a maximum effect of 23%.The most unfavorable wind direction angles of the structure are 0°and 180°.The change of the wind direction angle in the range of 0°to 30°has little effect on the wind vi⁃bration response.The change in the tilt angle of the PV modules has a greater impact on the wind vibration in the downwind direction and a smaller impact in the upwind di⁃rection.Special attention should be paid to the structural wind⁃resistant design of such systems in the upwind side span.展开更多
The Michelson Interferometer for Global High-resolution Thermospheric Imaging(MIGHTI)onboard the Ionospheric Connection Explorer(ICON)satellite offers the opportunity to investigate the altitude profile of thermospher...The Michelson Interferometer for Global High-resolution Thermospheric Imaging(MIGHTI)onboard the Ionospheric Connection Explorer(ICON)satellite offers the opportunity to investigate the altitude profile of thermospheric winds.In this study,we used the red-line measurements of MIGHTI to compare with the results estimated by Horizontal Wind Model 14(HWM14).The data selected included both the geomagnetic quiet period(December 2019 to August 2022)and the geomagnetic storm on August 26-28,2021.During the geomagnetic quiet period,the estimations of neutral winds from HWM14 showed relatively good agreement with the observations from ICON.According to the ICON observations,near the equator,zonal winds reverse from westward to eastward at around 06:00 local time(LT)at higher altitudes,and the stronger westward winds appear at later LTs at lower altitudes.At around 16:00 LT,eastward winds at 300 km reverse to westward,and vertical gradients of zonal winds similar to those at sunrise hours can be observed.In the middle latitudes,zonal winds reverse about 2-4 h earlier.Meridional winds vary more significantly than zonal winds with seasonal and latitudinal variations.According to the ICON observations,in the northern low latitudes,vertical reversals of meridional winds are found at 08:00-13:00 LT from 300 to 160 km and at around 18:00 LT from 300 to 200 km during the June solstice.Similar reversals of meridional winds are found at 04:00-07:00 LT from 300 to 160 km and at 22:00-02:00 LT from 270 to 200 km during the December solstice.In the southern low latitudes,meridional wind reversals occur at 08:00-11:00 LT from 200 to 160 km and at 21:00-02:00 LT from 300 to 200 km during the June solstice.During the December solstice,reversals of the meridional wind appear at 20:00-01:00 LT below 200 km and at 06:00-11:00 LT from 300 to 160 km.In the northern middle latitudes,the northward winds are dominant at 08:00-14:00 LT at 230 km during the June solstice.Northward winds persist until 16:00 LT at 160 and 300 km.During the December solstice,the northward winds are dominant from 06:00 to 21:00 LT.The vertical variations in neutral winds during the geomagnetic storm on August 26-28 were analyzed in detail.Both meridional and zonal winds during the active geomagnetic period observed by ICON show distinguishable vertical shear structures at different stages of the storm.On the dayside,during the main phase,the peak velocities of westward winds extend from a higher altitude to a lower altitude,whereas during the recovery phase,the peak velocities of the westward winds extend from lower altitudes to higher altitudes.The velocities of the southward winds are stronger at lower altitudes during the storm.These vertical structures of horizontal winds during the storm could not be reproduced by the HWM14 wind estimations,and the overall response to the storm of the horizontal winds in the low and middle latitudes is underestimated by HWM14.The ICON observations provide a good dataset for improving the HWM wind estimations in the middle and upper atmosphere,especially the vertical variations.展开更多
Wind tunnel experiment and CFD(computational fluid dynamics)simulation with LES(large eddy simulation)have been conducted to investigate the characteristics of peak wind force coefficients of porous panels mounted on ...Wind tunnel experiment and CFD(computational fluid dynamics)simulation with LES(large eddy simulation)have been conducted to investigate the characteristics of peak wind force coefficients of porous panels mounted on the roofs of high-rise buildings.First,aerodynamic modelling of porous panels was discussed.The relation between pressure loss coefficient and porosity was obtained.Then,a wind tunnel experiment was conducted to measure the wind forces(net wind pressures)acting on solid and porous panels mounted on the roof of a high-rise building.Because it was difficult to measure the pressures on both sides of thin,porous panel at the same location simultaneously,we proposed to use the roof edge pressures near the panel for the panel’s inside-surface pressures.This experimental method was validated by a CFD simulation reproducing the wind tunnel experiment.The characteristics of peak wind force coefficients of porous panels mounted on the roofs of high-rise buildings were made clear.Finally,positive and negative peak wind force coefficients for designing the rooftop porous panels were proposed.展开更多
Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particular...Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particularly necessary in offshore wind,currently one of the most critical assets for achieving sustainable energy generation goals,due to the harsh marine environment and the difficulty of maintenance tasks.To address this problem,this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines,using normalized and linearized operational data.The proposed framework transforms heterogeneous wind speed and power measurements into a unified scale,enabling the development of a new wind power index(WPi)that quantifies deviations from expected performance.Additionally,spatial and temporal coherence analyses of turbines within a wind farm ensure the validity of these normalized measurements across different wind turbine models and operating conditions.Furthermore,a Support Vector Machine(SVM)refines the classification process,effectively distinguishing measurement errors from actual power generation failures.Validation of this strategy using real-world data from the Alpha Ventus wind farm demonstrates that the proposed approach not only improves predictive maintenance but also optimizes energy production,highlighting its potential for broad application in offshore wind installations.展开更多
Wind energy has emerged as a potential replacement for fossil fuel-based energy sources.To harness maximum wind energy,a crucial decision in the development of an efficient wind farm is the optimal layout design.This ...Wind energy has emerged as a potential replacement for fossil fuel-based energy sources.To harness maximum wind energy,a crucial decision in the development of an efficient wind farm is the optimal layout design.This layout defines the specific locations of the turbines within the wind farm.The process of finding the optimal locations of turbines,in the presence of various technical and technological constraints,makes the wind farm layout design problem a complex optimization problem.This problem has traditionally been solved with nature-inspired algorithms with promising results.The performance and convergence of nature-inspired algorithms depend on several parameters,among which the algorithm termination criterion plays a crucial role.Timely convergence is an important aspect of efficient algorithm design because an inefficient algorithm results in wasted computational resources,unwarranted electricity consumption,and hardware stress.This study provides an in-depth analysis of several termination criteria while using the genetic algorithm as a test bench,with its application to the wind farm layout design problem while considering various wind scenarios.The performance of six termination criteria is empirically evaluated with respect to the quality of solutions produced and the execution time involved.Due to the conflicting nature of these two attributes,fuzzy logic-based multi-attribute decision-making is employed in the decision process.Results for the fuzzy decision approach indicate that among the various criteria tested,the criterion Phi achieves an improvement in the range of 2.44%to 32.93%for wind scenario 1.For scenario 2,Best-worst termination criterion performed well compared to the other criteria evaluated,with an improvement in the range of 1.2%to 9.64%.For scenario 3,Hitting bound was the best performer with an improvement of 1.16%to 20.93%.展开更多
Previous studies have indicated a global reversal of near-surface wind speeds from a declining trend to an increasing trend around 2010;however,it remains unclear whether upper-air wind speeds exhibit a similar revers...Previous studies have indicated a global reversal of near-surface wind speeds from a declining trend to an increasing trend around 2010;however,it remains unclear whether upper-air wind speeds exhibit a similar reversal.This study evaluates reanalysis products using surface and radiosonde observations to analyze upper-air wind speed variations in the Northern Hemisphere,focusing on their seasonal and latitudinal differences.Results demonstrate that JRA-55 effectively captures wind speed variations in the Northern Hemisphere.Notably,upper-air wind speeds over land experienced a reversal in winter 2010 with significant latitudinal differences.The trend reversal of upper wind speed between the midlatitudes and subtropics presents a dipole pattern.From 1990 to 2010,upper-air wind speeds in the midlatitudes(40°-70°N)significantly declined,while the subtropical zone(20°-40°N)displayed an opposite trend.However,during 2010-2020,wind speeds in the midlatitudes shifted to a significant positive trend,whereas the subtropics experienced a significant negative trend.The variations in Northern Hemisphere winter wind speeds can be attributed to changes in low-level baroclinicity driven by tropical diabatic heating and midlatitude transient eddy feedback.Enhanced diabatic heating and weakened eddy feedback during 1990-2010 contributed to reduced wind speeds in the midlatitudes and increased speeds in the subtropics,while reduced diabatic heating and strengthened eddy feedback during 2010-2020 resulted in increased wind speeds in the midlatitudes and decreased speeds in the subtropics.The reversal of upper-air wind speeds could affect surface wind speeds by downward momentum transfer,which could contribute to the reversal of surface wind speeds.展开更多
This review provides a comprehensive and systematic examination of Computational Fluid Dynamics(CFD)techniques and methodologies applied to the development of Vertical Axis Wind Turbines(VAWTs).Although VAWTs offer si...This review provides a comprehensive and systematic examination of Computational Fluid Dynamics(CFD)techniques and methodologies applied to the development of Vertical Axis Wind Turbines(VAWTs).Although VAWTs offer significant advantages for urban wind applications,such as omnidirectional wind capture and a compact,ground-accessible design,they face substantial aerodynamic challenges,including dynamic stall,blade-wake interactions,and continuously varying angles of attack throughout their rotation.The review critically evaluates how CFD has been leveraged to address these challenges,detailing the modelling frameworks,simulation setups,mesh strategies,turbulence models,and boundary condition treatments adopted in the literature.Special attention is given to the comparative performance of 2-D vs.3-D simulations,static and dynamic meshing techniques(sliding,overset,morphing),and the impact of near-wall resolution on prediction fidelity.Moreover,this review maps the evolution of CFD tools in capturing key performance indicators including power coefficient,torque,flow separation,and wake dynamics,while highlighting both achievements and current limitations.The synthesis of studies reveals best practices,identifies gaps in simulation fidelity and validation strategies,and outlines critical directions for future research,particularly in high-fidelity modelling and cost-effective simulation of urban-scale VAWTs.By synthesizing insights from over a hundred referenced studies,this review serves as a consolidated resource to advance VAWT design and performance optimization through CFD.These include studies on various aspects such as blade geometry refinement,turbulence modeling,wake interaction mitigation,tip-loss reduction,dynamic stall control,and other aerodynamic and structural improvements.This,in turn,supports their broader integration into sustainable energy systems.展开更多
Biomimetics has recently emerged as an interesting approach to enhance renewable energy technologies.In this work,bioinspired Trailing Edge Serrations(TES)were evaluated on a typical Vertical Axis Wind Turbine(VAWT)ai...Biomimetics has recently emerged as an interesting approach to enhance renewable energy technologies.In this work,bioinspired Trailing Edge Serrations(TES)were evaluated on a typical Vertical Axis Wind Turbine(VAWT)airfoil,the DU06-W200.As noise reduction benefits of these mechanisms are already well-established,this study focuses on their impact on airfoil and VAWT performance.A saw-tooth geometry was chosen based on VAWT specifications and existing research,followed by a detailed assessment through wind tunnel tests using a newly developed aerodynamic balance.For a broad spectrum of attack angles and Reynolds numbers,lift,drag,and pitching moments were carefully measured.The results show that TES enhance the lift-to-drag ratio,especially in stalled conditions,and postpone stall at negative angles,expanding the effective performance range.A notable increase in pitching moment also is also observed,relevant for blade-strut joint design.Additionally,the impact on turbine performance was estimated using an analytical model,demonstrating excellent accuracy when compared against previous experimental results.TES offer a modest 2%improve-ment in peak performance,though they slightly narrow the optimal tip-speed ratio zone.Despite this,the potential noise reduction and performance gains make TES a valuable addition to VAWT designs,especially in urban settings.展开更多
To enhance the navigation efficiency of inland new-energy ships and reduce energy consumption and emissions,this study investigates wind load coefficients under 13 conditions,combining a wind speed of 2.0 m/s with win...To enhance the navigation efficiency of inland new-energy ships and reduce energy consumption and emissions,this study investigates wind load coefficients under 13 conditions,combining a wind speed of 2.0 m/s with wind direction angles ranging from 0°to 180°in 15°increments.Using Computational Fluid Dynamics(CFD)simulations,the wind load is decomposed into along-course(Cx)and transverse(Cy)components,and their variation with wind direction is systematically analyzed.Results show that Cx is maximal under headwind(0°),decreases approximately following a cosine trend,and reaches its most negative value under tailwind(180°).Cy peaks at crosswind(90°)and exhibits an overall sinusoidal distribution.Certain wind directions produce a compound effect on the hull,particularly when the crosswind angle approaches 90°.Flow analysis reveals that wind generates a high-pressure zone on the windward side and a low-pressure vortex region on the leeward side,inducing unstable forces and increasing energy consumption.Based on the wind pressure distribution,a targeted structural optimization is proposed to mitigate high-pressure resistance.These findings provide a theoretical basis for hull form optimization and energy-efficient ship design.展开更多
Under the context of global climate change,the frequent occurrence of strong winds in Guyuan has significantly hindered the development of local facility agriculture.Using hourly meteorological data from the Sanying N...Under the context of global climate change,the frequent occurrence of strong winds in Guyuan has significantly hindered the development of local facility agriculture.Using hourly meteorological data from the Sanying National Station and the Guyuan Greenhouse Station between April 2024 and April 2025,this study employed machine learning methods to develop wind speed prediction models based on BP neural network,support vector machine,and random forest(referred to as BP,SVM,and RF models),aiming to provide references for local disaster prevention and mitigation.The results indicate that:1)Wind speed at the Guyuan Greenhouse Station exhibits the strongest correlation with that at the National Station(0.489-0.595),followed by temperature and 24-hour precipitation(0.116-0.336).2)The mean absolute error(MAE)of the BP,RF,and SVM models at all heights is below 1.5 m/s,the root mean square error(RMSE)is under 2.1 m/s,and the forecast accuracy(FA)exceeds 75%,indicating satisfactory model performance.Compared to 3 m,the MAE and RMSE of 0.5 m are larger,while the FA is smaller.This indicates that the wind speed of 0.5 m is close to the ground,and is more affected by surface roughness and turbulence effects,resulting in greater randomness and making the model more difficult.3)Based on case analyses of May 10 and May 1,2024,the overall simulation performance ranks as“RF model>SVM model>BP model”;however,the SVM model demonstrates higher accuracy in simulating strong wind events.展开更多
The present paper investigates the methods for estimating the maximum(positive)and the minimum(negative)peak wind force coefficients on domed free roofs based on the quasi-steady theory and the peak factor method,in w...The present paper investigates the methods for estimating the maximum(positive)and the minimum(negative)peak wind force coefficients on domed free roofs based on the quasi-steady theory and the peak factor method,in which the experimental results obtained from our previous studies(2019,2025)are used.Focus is on the distributions of the peak wind force coefficients along the centerline parallel to the wind direction considering that domed free roof is an axisymmetric body.Empirical formulas are provided to the distributions of mean wind force coefficient,RMS(root mean square)fluctuating wind force coefficient and peak factors as a function of the rise/span ratio of the roof and the turbulence intensity of the approach flow in the along-wind direction at the mean roof height.The proposed methods are validated by the experimental results for the peak wind force coefficients.The methods would provide useful information to structural engineers when estimating the design wind loads on cladding/components of domed free roofs.展开更多
This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain fie...This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain field.The impact of rainfall on aerodynamic performance was initially examined using a stationary turbine model in both wind and wind–rain conditions.Subsequently,the study compared the FOWT’s performance under various single degree-of-freedom(DOF)motions,including surge,pitch,heave,and yaw.Finally,the combined effects of wind–rain fields and platform motions involving two DOFs on the FOWT’s aerodynamics were analyzed and compared.The results demonstrate that rain negatively impacts the aerodynamic performance of both the stationary turbines and FOWTs.Pitch-dominated motions,whether involving single or multiple DOFs,caused significant fluctuations in the FOWT aerodynamics.The combination of surge and pitch motions created the most challenging operational environment for the FOWT in all tested scenarios.These findings highlighted the need for stronger construction materials and greater ultimate bearing capacity for FOWTs,as well as the importance of optimizing designs to mitigate excessive pitch and surge.展开更多
The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward...The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.展开更多
Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.There...Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.Therefore,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution observations.This paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust events.The shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or typhoons.Then,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning observations.Finally,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind gusts.TGNet products have high accuracy,with a critical success index reaching 0.77.Compared with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,respectively.The new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every 10minutes.The results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.展开更多
Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationship...Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.展开更多
Vector winds play a crucial role in weather and climate,as well as the effective utilization of wind energy resources.However,limited research has been conducted on treating the wind field as a vector field in the eva...Vector winds play a crucial role in weather and climate,as well as the effective utilization of wind energy resources.However,limited research has been conducted on treating the wind field as a vector field in the evaluation of numerical weather prediction models.In this study,the authors treat vector winds as a whole by employing a vector field evaluation method,and evaluate the mesoscale model of the China Meteorological Administration(CMA-MESO)and ECMWF forecast,with reference to ERA5 reanalysis,in terms of multiple aspects of vector winds over eastern China in 2022.The results show that the ECMWF forecast is superior to CMA-MESO in predicting the spatial distribution and intensity of 10-m vector winds.Both models overestimate the wind speed in East China,and CMA-MESO overestimates the wind speed to a greater extent.The forecasting skill of the vector wind field in both models decreases with increasing lead time.The forecasting skill of CMA-MESO fluctuates more and decreases faster than that of the ECMWF forecast.There is a significant negative correlation between the model vector wind forecasting skill and terrain height.This study provides a scientific evaluation of the local application of vector wind forecasts of the CMA-MESO model and ECMWF forecast.展开更多
基金supported by the Science and Technology Project of China South Power Grid Co.,Ltd.under Grant No.036000KK52222044(GDKJXM20222430).
文摘This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn(FLOW Redirection and Induction Dynamics)dynamic wake model.First,the impact of wakes on turbine effective wind speed is analyzed,leading to a quantitative method for assessing wake interactions.Based on these interactions,a partitioning method divides the wind farm into smaller,computationally manageable zones.Subsequently,a heuristic control algorithm is developed for yaw optimization within each partition,reducing the overall computational burden associated with multi-turbine optimization.The algorithm’s effectiveness is evaluated through case studies on 11-turbine and 28-turbine wind farms,demonstrating power generation increases of 9.78%and 1.78%,respectively,compared to baseline operation.The primary innovation lies in coupling the higher-fidelity dynamic FLORIDyn wake model with a graph-based partitioning strategy and a computationally efficient heuristic optimization,enabling scalable and accurate yaw control for large wind farms,overcoming limitations associated with simplified models or centralized optimization approaches.
基金supported by the Joint Research Fund in Smart Grid(U1966601)under cooperative agreement between the National Natural Science Foundation of China(NSFC)and the State Grid Cor-poration of China(SGCC).
文摘Establishing power systems with a high share of renewable energy sources is a pivotal step toward achieving a globally sustainable transition to green and low-carbon energy.This study focuses on low-output wind power that affects the generation capacity of power systems with a high share of renewable energy sources.Utilizing the Coupled Model Intercomparison Project Phase 6 datasets,a predictive model for low-output wind power was employed to investigate regional trends worldwide.The frequency and duration of low-output wind-power events exhibited increasing trends globally,particularly in East Asia and South America,but not in North America.By 2060,the annual total days with low-output wind power in East Asia and South America could rise to 13 and 5 d,and the maximum continuous duration of low-output wind power could reach 5 and 2 d,respectively.As wind power becomes a primary elec-tricity source,such low output could lead to shortages in energy supply within the power system,trig-gering large-scale power outages.This issue calls for critical attention when establishing power systems with a high share of renewable energy sources.The conclusions provide a basis for analyzing power supply risks and configuring flexible power sources for scenarios with a high share of renewable energy.
基金supported by the Key R&D Program of Shandong Province,China(No.2021ZLGX04)the National Natural Science Foundation of China(No.52171284)。
文摘A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical distribution of the two variables may show multimodal characteristics.In this work,a finite mixture bivariate statistical model was designed to describe the statistical properties,which is composed of several components,each with a Weibull distribution and a normal distribution for wind speed and wind shear,respectively,with a Gaussian copula to describe the dependency structure between the two variables.To confirm the developed model,reanalysis data from six positions in the coastal sea areas of China were used.Our results disclosed that the developed joint statistical model can accurately capture the different multimodal structures presented in all the bivariate samples under mixed atmospheric conditions,giving acceptable predictions of the joint probability distributions.Proper consideration of wind shear coefficient variation is crucial in estimating height-dependent wind resource characteristics.Importantly,unlike traditional methods that are limited to specific hub heights,the model developed here can estimate wind energy potential across different hub heights,enhancing the economic viability assessment of wind power projects.
基金The National Natural Science Foundation of China(No.52338011).
文摘To investigate the wind⁃induced vibration re⁃sponse characteristics of multispan double⁃layer cable photo⁃voltaic(PV)support structures,wind tunnel tests using an aeroelastic model were carried out to obtain the wind⁃induced vibration response data of a three⁃span four⁃row double⁃layer cable PV support system.The wind⁃induced vibration characteristics with different PV module tilt angles,wind speeds,and wind direction angles were analyzed.The results showed that the double⁃layer cable large⁃span flexible PV support can effectively control the wind⁃induced vibration response and prevent the occur⁃rence of flutter under strong wind conditions.The maxi⁃mum value of the wind⁃induced vibration displacement of the flexible PV support system occurs in the windward first row.The upstream module has a significant shading effect on the downstream module,with a maximum effect of 23%.The most unfavorable wind direction angles of the structure are 0°and 180°.The change of the wind direction angle in the range of 0°to 30°has little effect on the wind vi⁃bration response.The change in the tilt angle of the PV modules has a greater impact on the wind vibration in the downwind direction and a smaller impact in the upwind di⁃rection.Special attention should be paid to the structural wind⁃resistant design of such systems in the upwind side span.
基金supported by the National Key R&D Program of China (Grant No.2022YFF0503700)the special funds of Hubei Luojia Laboratory (Grant No.220100011)+1 种基金supported by the International Space Science Institute–Beijing(ISSI-BJ) project“The Electromagnetic Data Validation and Scientific Application Research based on CSES Satellite”and ISSI/ISSI-BJ project,“Multi-Scale Magnetosphere–Ionosphere–Thermosphere Interaction.”
文摘The Michelson Interferometer for Global High-resolution Thermospheric Imaging(MIGHTI)onboard the Ionospheric Connection Explorer(ICON)satellite offers the opportunity to investigate the altitude profile of thermospheric winds.In this study,we used the red-line measurements of MIGHTI to compare with the results estimated by Horizontal Wind Model 14(HWM14).The data selected included both the geomagnetic quiet period(December 2019 to August 2022)and the geomagnetic storm on August 26-28,2021.During the geomagnetic quiet period,the estimations of neutral winds from HWM14 showed relatively good agreement with the observations from ICON.According to the ICON observations,near the equator,zonal winds reverse from westward to eastward at around 06:00 local time(LT)at higher altitudes,and the stronger westward winds appear at later LTs at lower altitudes.At around 16:00 LT,eastward winds at 300 km reverse to westward,and vertical gradients of zonal winds similar to those at sunrise hours can be observed.In the middle latitudes,zonal winds reverse about 2-4 h earlier.Meridional winds vary more significantly than zonal winds with seasonal and latitudinal variations.According to the ICON observations,in the northern low latitudes,vertical reversals of meridional winds are found at 08:00-13:00 LT from 300 to 160 km and at around 18:00 LT from 300 to 200 km during the June solstice.Similar reversals of meridional winds are found at 04:00-07:00 LT from 300 to 160 km and at 22:00-02:00 LT from 270 to 200 km during the December solstice.In the southern low latitudes,meridional wind reversals occur at 08:00-11:00 LT from 200 to 160 km and at 21:00-02:00 LT from 300 to 200 km during the June solstice.During the December solstice,reversals of the meridional wind appear at 20:00-01:00 LT below 200 km and at 06:00-11:00 LT from 300 to 160 km.In the northern middle latitudes,the northward winds are dominant at 08:00-14:00 LT at 230 km during the June solstice.Northward winds persist until 16:00 LT at 160 and 300 km.During the December solstice,the northward winds are dominant from 06:00 to 21:00 LT.The vertical variations in neutral winds during the geomagnetic storm on August 26-28 were analyzed in detail.Both meridional and zonal winds during the active geomagnetic period observed by ICON show distinguishable vertical shear structures at different stages of the storm.On the dayside,during the main phase,the peak velocities of westward winds extend from a higher altitude to a lower altitude,whereas during the recovery phase,the peak velocities of the westward winds extend from lower altitudes to higher altitudes.The velocities of the southward winds are stronger at lower altitudes during the storm.These vertical structures of horizontal winds during the storm could not be reproduced by the HWM14 wind estimations,and the overall response to the storm of the horizontal winds in the low and middle latitudes is underestimated by HWM14.The ICON observations provide a good dataset for improving the HWM wind estimations in the middle and upper atmosphere,especially the vertical variations.
文摘Wind tunnel experiment and CFD(computational fluid dynamics)simulation with LES(large eddy simulation)have been conducted to investigate the characteristics of peak wind force coefficients of porous panels mounted on the roofs of high-rise buildings.First,aerodynamic modelling of porous panels was discussed.The relation between pressure loss coefficient and porosity was obtained.Then,a wind tunnel experiment was conducted to measure the wind forces(net wind pressures)acting on solid and porous panels mounted on the roof of a high-rise building.Because it was difficult to measure the pressures on both sides of thin,porous panel at the same location simultaneously,we proposed to use the roof edge pressures near the panel for the panel’s inside-surface pressures.This experimental method was validated by a CFD simulation reproducing the wind tunnel experiment.The characteristics of peak wind force coefficients of porous panels mounted on the roofs of high-rise buildings were made clear.Finally,positive and negative peak wind force coefficients for designing the rooftop porous panels were proposed.
基金supported by the Spanish Ministry of Science and Innovation under the MCI/AEI/FEDER project number PID2021-123543OBC21.
文摘Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particularly necessary in offshore wind,currently one of the most critical assets for achieving sustainable energy generation goals,due to the harsh marine environment and the difficulty of maintenance tasks.To address this problem,this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines,using normalized and linearized operational data.The proposed framework transforms heterogeneous wind speed and power measurements into a unified scale,enabling the development of a new wind power index(WPi)that quantifies deviations from expected performance.Additionally,spatial and temporal coherence analyses of turbines within a wind farm ensure the validity of these normalized measurements across different wind turbine models and operating conditions.Furthermore,a Support Vector Machine(SVM)refines the classification process,effectively distinguishing measurement errors from actual power generation failures.Validation of this strategy using real-world data from the Alpha Ventus wind farm demonstrates that the proposed approach not only improves predictive maintenance but also optimizes energy production,highlighting its potential for broad application in offshore wind installations.
基金funded by King Fahd University of Petroleum&Minerals,Saudi Arabia under IRC-SES grant#INRE 2217.
文摘Wind energy has emerged as a potential replacement for fossil fuel-based energy sources.To harness maximum wind energy,a crucial decision in the development of an efficient wind farm is the optimal layout design.This layout defines the specific locations of the turbines within the wind farm.The process of finding the optimal locations of turbines,in the presence of various technical and technological constraints,makes the wind farm layout design problem a complex optimization problem.This problem has traditionally been solved with nature-inspired algorithms with promising results.The performance and convergence of nature-inspired algorithms depend on several parameters,among which the algorithm termination criterion plays a crucial role.Timely convergence is an important aspect of efficient algorithm design because an inefficient algorithm results in wasted computational resources,unwarranted electricity consumption,and hardware stress.This study provides an in-depth analysis of several termination criteria while using the genetic algorithm as a test bench,with its application to the wind farm layout design problem while considering various wind scenarios.The performance of six termination criteria is empirically evaluated with respect to the quality of solutions produced and the execution time involved.Due to the conflicting nature of these two attributes,fuzzy logic-based multi-attribute decision-making is employed in the decision process.Results for the fuzzy decision approach indicate that among the various criteria tested,the criterion Phi achieves an improvement in the range of 2.44%to 32.93%for wind scenario 1.For scenario 2,Best-worst termination criterion performed well compared to the other criteria evaluated,with an improvement in the range of 1.2%to 9.64%.For scenario 3,Hitting bound was the best performer with an improvement of 1.16%to 20.93%.
基金supported by the National Natural Science Foundation of China[grant numbers U2442207,42122034,42075043,and 42330609]the Youth Innovation Promotion Association[grant number 2021427]+2 种基金the West Light Foundation[grant number xbzgzdsys-202409]of the Chinese Academy of Sciencesthe Key Talent Projects in Gansu Provincethe Central Guidance Fund for Local Science and Technology Development Projects in Gansu Province[grant number 24ZYQA031].
文摘Previous studies have indicated a global reversal of near-surface wind speeds from a declining trend to an increasing trend around 2010;however,it remains unclear whether upper-air wind speeds exhibit a similar reversal.This study evaluates reanalysis products using surface and radiosonde observations to analyze upper-air wind speed variations in the Northern Hemisphere,focusing on their seasonal and latitudinal differences.Results demonstrate that JRA-55 effectively captures wind speed variations in the Northern Hemisphere.Notably,upper-air wind speeds over land experienced a reversal in winter 2010 with significant latitudinal differences.The trend reversal of upper wind speed between the midlatitudes and subtropics presents a dipole pattern.From 1990 to 2010,upper-air wind speeds in the midlatitudes(40°-70°N)significantly declined,while the subtropical zone(20°-40°N)displayed an opposite trend.However,during 2010-2020,wind speeds in the midlatitudes shifted to a significant positive trend,whereas the subtropics experienced a significant negative trend.The variations in Northern Hemisphere winter wind speeds can be attributed to changes in low-level baroclinicity driven by tropical diabatic heating and midlatitude transient eddy feedback.Enhanced diabatic heating and weakened eddy feedback during 1990-2010 contributed to reduced wind speeds in the midlatitudes and increased speeds in the subtropics,while reduced diabatic heating and strengthened eddy feedback during 2010-2020 resulted in increased wind speeds in the midlatitudes and decreased speeds in the subtropics.The reversal of upper-air wind speeds could affect surface wind speeds by downward momentum transfer,which could contribute to the reversal of surface wind speeds.
基金funded by Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme(FRGS/1/2024/TK10/UKM/02/7).
文摘This review provides a comprehensive and systematic examination of Computational Fluid Dynamics(CFD)techniques and methodologies applied to the development of Vertical Axis Wind Turbines(VAWTs).Although VAWTs offer significant advantages for urban wind applications,such as omnidirectional wind capture and a compact,ground-accessible design,they face substantial aerodynamic challenges,including dynamic stall,blade-wake interactions,and continuously varying angles of attack throughout their rotation.The review critically evaluates how CFD has been leveraged to address these challenges,detailing the modelling frameworks,simulation setups,mesh strategies,turbulence models,and boundary condition treatments adopted in the literature.Special attention is given to the comparative performance of 2-D vs.3-D simulations,static and dynamic meshing techniques(sliding,overset,morphing),and the impact of near-wall resolution on prediction fidelity.Moreover,this review maps the evolution of CFD tools in capturing key performance indicators including power coefficient,torque,flow separation,and wake dynamics,while highlighting both achievements and current limitations.The synthesis of studies reveals best practices,identifies gaps in simulation fidelity and validation strategies,and outlines critical directions for future research,particularly in high-fidelity modelling and cost-effective simulation of urban-scale VAWTs.By synthesizing insights from over a hundred referenced studies,this review serves as a consolidated resource to advance VAWT design and performance optimization through CFD.These include studies on various aspects such as blade geometry refinement,turbulence modeling,wake interaction mitigation,tip-loss reduction,dynamic stall control,and other aerodynamic and structural improvements.This,in turn,supports their broader integration into sustainable energy systems.
基金The authors wish to thank the financial support of the Spanish Ministry of Science,Innovation and Universities in reference to the Project:Efficiency improvement and noise reduction of a vertical axis wind turbine for urban environments(MERTURB)-Ref.MCINN-22-TED2021-131307B-100.
文摘Biomimetics has recently emerged as an interesting approach to enhance renewable energy technologies.In this work,bioinspired Trailing Edge Serrations(TES)were evaluated on a typical Vertical Axis Wind Turbine(VAWT)airfoil,the DU06-W200.As noise reduction benefits of these mechanisms are already well-established,this study focuses on their impact on airfoil and VAWT performance.A saw-tooth geometry was chosen based on VAWT specifications and existing research,followed by a detailed assessment through wind tunnel tests using a newly developed aerodynamic balance.For a broad spectrum of attack angles and Reynolds numbers,lift,drag,and pitching moments were carefully measured.The results show that TES enhance the lift-to-drag ratio,especially in stalled conditions,and postpone stall at negative angles,expanding the effective performance range.A notable increase in pitching moment also is also observed,relevant for blade-strut joint design.Additionally,the impact on turbine performance was estimated using an analytical model,demonstrating excellent accuracy when compared against previous experimental results.TES offer a modest 2%improve-ment in peak performance,though they slightly narrow the optimal tip-speed ratio zone.Despite this,the potential noise reduction and performance gains make TES a valuable addition to VAWT designs,especially in urban settings.
基金Shandong Province Key R&D Program(Innovation Capacity Improvement Project for Science,Technology Small,Medium-Sized Enterprises)Project No.:2025TSGCCZZB0679Project ZR2024QE394 supported by Shandong Provincial Natural Science Foundation.
文摘To enhance the navigation efficiency of inland new-energy ships and reduce energy consumption and emissions,this study investigates wind load coefficients under 13 conditions,combining a wind speed of 2.0 m/s with wind direction angles ranging from 0°to 180°in 15°increments.Using Computational Fluid Dynamics(CFD)simulations,the wind load is decomposed into along-course(Cx)and transverse(Cy)components,and their variation with wind direction is systematically analyzed.Results show that Cx is maximal under headwind(0°),decreases approximately following a cosine trend,and reaches its most negative value under tailwind(180°).Cy peaks at crosswind(90°)and exhibits an overall sinusoidal distribution.Certain wind directions produce a compound effect on the hull,particularly when the crosswind angle approaches 90°.Flow analysis reveals that wind generates a high-pressure zone on the windward side and a low-pressure vortex region on the leeward side,inducing unstable forces and increasing energy consumption.Based on the wind pressure distribution,a targeted structural optimization is proposed to mitigate high-pressure resistance.These findings provide a theoretical basis for hull form optimization and energy-efficient ship design.
基金supported by Ningxia Natural Science Foundation Project(2023AAC02088)Liangshan Prefecture 2023 Annual Science and Technology Planning Project(23ZDYF0182).
文摘Under the context of global climate change,the frequent occurrence of strong winds in Guyuan has significantly hindered the development of local facility agriculture.Using hourly meteorological data from the Sanying National Station and the Guyuan Greenhouse Station between April 2024 and April 2025,this study employed machine learning methods to develop wind speed prediction models based on BP neural network,support vector machine,and random forest(referred to as BP,SVM,and RF models),aiming to provide references for local disaster prevention and mitigation.The results indicate that:1)Wind speed at the Guyuan Greenhouse Station exhibits the strongest correlation with that at the National Station(0.489-0.595),followed by temperature and 24-hour precipitation(0.116-0.336).2)The mean absolute error(MAE)of the BP,RF,and SVM models at all heights is below 1.5 m/s,the root mean square error(RMSE)is under 2.1 m/s,and the forecast accuracy(FA)exceeds 75%,indicating satisfactory model performance.Compared to 3 m,the MAE and RMSE of 0.5 m are larger,while the FA is smaller.This indicates that the wind speed of 0.5 m is close to the ground,and is more affected by surface roughness and turbulence effects,resulting in greater randomness and making the model more difficult.3)Based on case analyses of May 10 and May 1,2024,the overall simulation performance ranks as“RF model>SVM model>BP model”;however,the SVM model demonstrates higher accuracy in simulating strong wind events.
文摘The present paper investigates the methods for estimating the maximum(positive)and the minimum(negative)peak wind force coefficients on domed free roofs based on the quasi-steady theory and the peak factor method,in which the experimental results obtained from our previous studies(2019,2025)are used.Focus is on the distributions of the peak wind force coefficients along the centerline parallel to the wind direction considering that domed free roof is an axisymmetric body.Empirical formulas are provided to the distributions of mean wind force coefficient,RMS(root mean square)fluctuating wind force coefficient and peak factors as a function of the rise/span ratio of the roof and the turbulence intensity of the approach flow in the along-wind direction at the mean roof height.The proposed methods are validated by the experimental results for the peak wind force coefficients.The methods would provide useful information to structural engineers when estimating the design wind loads on cladding/components of domed free roofs.
基金Supported by the National Natural Science Foundation of China(51679080 and 51379073)the Fundamental Research Funds for the Central Universities(B230205020).
文摘This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain field.The impact of rainfall on aerodynamic performance was initially examined using a stationary turbine model in both wind and wind–rain conditions.Subsequently,the study compared the FOWT’s performance under various single degree-of-freedom(DOF)motions,including surge,pitch,heave,and yaw.Finally,the combined effects of wind–rain fields and platform motions involving two DOFs on the FOWT’s aerodynamics were analyzed and compared.The results demonstrate that rain negatively impacts the aerodynamic performance of both the stationary turbines and FOWTs.Pitch-dominated motions,whether involving single or multiple DOFs,caused significant fluctuations in the FOWT aerodynamics.The combination of surge and pitch motions created the most challenging operational environment for the FOWT in all tested scenarios.These findings highlighted the need for stronger construction materials and greater ultimate bearing capacity for FOWTs,as well as the importance of optimizing designs to mitigate excessive pitch and surge.
基金funded by the State Grid Science and Technology Project“Research on Key Technologies for Prediction and Early Warning of Large-Scale Offshore Wind Power Ramp Events Based on Meteorological Data Enhancement”(4000-202318098A-1-1-ZN).
文摘The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC3004104)the National Natural Science Foundation of China(Grant No.U2342204)+4 种基金the Innovation and Development Program of the China Meteorological Administration(Grant No.CXFZ2024J001)the Open Research Project of the Key Open Laboratory of Hydrology and Meteorology of the China Meteorological Administration(Grant No.23SWQXZ010)the Science and Technology Plan Project of Zhejiang Province(Grant No.2022C03150)the Open Research Fund Project of Anyang National Climate Observatory(Grant No.AYNCOF202401)the Open Bidding for Selecting the Best Candidates Program(Grant No.CMAJBGS202318)。
文摘Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.Therefore,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution observations.This paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust events.The shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or typhoons.Then,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning observations.Finally,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind gusts.TGNet products have high accuracy,with a critical success index reaching 0.77.Compared with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,respectively.The new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every 10minutes.The results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.
基金funded by the Inner Mongolia Nature Foundation Project,Project number:2023JQ04.
文摘Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.
基金primarily supported by the National Key R&D Program of China[grant number 2021YFC3000904]the Jiangsu Provincial Key Technology R&D Program[grant number BE2022851]National Natural Science Foundation of China[grant number 42405035]。
文摘Vector winds play a crucial role in weather and climate,as well as the effective utilization of wind energy resources.However,limited research has been conducted on treating the wind field as a vector field in the evaluation of numerical weather prediction models.In this study,the authors treat vector winds as a whole by employing a vector field evaluation method,and evaluate the mesoscale model of the China Meteorological Administration(CMA-MESO)and ECMWF forecast,with reference to ERA5 reanalysis,in terms of multiple aspects of vector winds over eastern China in 2022.The results show that the ECMWF forecast is superior to CMA-MESO in predicting the spatial distribution and intensity of 10-m vector winds.Both models overestimate the wind speed in East China,and CMA-MESO overestimates the wind speed to a greater extent.The forecasting skill of the vector wind field in both models decreases with increasing lead time.The forecasting skill of CMA-MESO fluctuates more and decreases faster than that of the ECMWF forecast.There is a significant negative correlation between the model vector wind forecasting skill and terrain height.This study provides a scientific evaluation of the local application of vector wind forecasts of the CMA-MESO model and ECMWF forecast.
