Wind Characteristics Research Articles

Sail Wind Power Stations: Evaluating the Efficiency of Converting Mechanical Energy into Electrical Energy

This study aimed to improve the design of an automatically controlled sail wind power station (SWPS). The peculiarity of the considered SWPS design is that its working body (WB) is rigidly connected to the upper platform of a Sholkor parallel manipulator that has six degrees of freedom. Six actuators connect the manipulator’s upper platform to the fixed lower platform. Each actuator is multifunctional and converts mechanical energy from wind action into electrical energy while controlling the WB’s movements. This wind energy conversion, by which the SWPS’s structural efficiency is evaluated, largely depends on the actuator’s coefficient of performance (CP). To meet the study objective, a prototype actuator was experimentally investigated to establish its efficiency. For this, a new experimental methodology was proposed, which involved sequentially experimenting on wind characteristics to obtain data, establishing a database, processing and preparing the initial data, and conducting a force analysis of the SWPS. Based thereon, the predicted power of the input load on the actuators was determined using Mathcad software. In the experimental setup, this predicted power was used as the actuator’s input, and the experimental value of the generated electrical energy (the output power) gave the actuator prototype’s efficiency. The actuator’s average experimental CP was = 0.56−0.58, which demonstrates that this geometry’s dimensions and parameters are acceptable. The results of the study will be used to improve the design. The article emphasizes the potential of SWPSs for producing wind energy.

Diurnal Patterns of Surface Wind at Palabuhanratu, using ERA5 Global Reanalysis Data

Surface wind characteristics are one of the factors in the formation of weather in a place, such as coastal areas that are directly adjacent to the ocean. One of the areas located on the Southern coast of the Java island, is Palabuhanratu, Sukabumi. This study will provide an overview of the characteristics of the diurnal pattern of surface wind in the Palabuhanratu area in the form of bay. The data that will be used in this research is ERA5 global analysis data produced by The European Center for Medium-Range Weather Forecasts (ECMWF) and Observation data. Observational data and ERA5, show different diurnal patterns in each season. This can be seen especially during the day, from 10 to 16 local time. The diurnal pattern of ERA5 also shows different things at the summer (JJA) and during the rainy season (DJF) in Palabuhanratu.

Study on the influence of cross-section shape on the characteristics of wind flow field in heavy-daty railway tunnel

In order to reduce the coal dust pollution when the heavy train enters the tunnel and to ensure the safety of railroad operation, this paper adopts numerical simulation to study the characteristics of the wind flow field of the heavy train passing through different shapes of tunnels. The results show that the shape of the tunnel section has a significant effect on the piston wind characteristics of the train entering the tunnel. When the train passes through the tunnel, the value of the wind pressure and the gradient of the pressure on the surface of the carriages increase from horseshoe shape, high wall shape and high arch shape. The vortex structure generated at the entrance of the horseshoe tunnel is the smallest and the flow field is more stable, and the wind turbulence shows significant weakening effect; when the rear end of the car enters the tunnel, the range of the influence of the piston winds outside the tunnel is in order of smallest to largest for the horseshoe, high wall, and high arch tunnels; in the wake region, the central region of the strong vorticity zone in the horseshoe tunnel is more continuous, reducing the instability of the airflow in the tunnel. The results of this study are of great significance in understanding the characteristics of the wind flow field and the effect on dust generation when heavy trains pass through the tunnel.

Analysis of Strong Wind Characteristics and Impact Systems at Xiangjiaba Hydropower Station

Analysis of Strong Wind Characteristics and Impact Systems at Xiangjiaba Hydropower Station

On the performance of SRANS, URANS and SAS in the prediction of the wind characteristics around a high-rise building

On the performance of SRANS, URANS and SAS in the prediction of the wind characteristics around a high-rise building

Analysis of Typhoon-Induced Wind Fields in Ports of the Central and Northern Taiwan Strait

The winds of a typhoon are a significant meteorological hazard with substantial implications for maritime transportation and are of paramount importance. Studying wind field characteristics and establishing effective algorithms for wind correction are of significant practical and societal importance within the realm of cargo transport operations at ports and terminals, thereby guaranteeing the sustainable development of port shipping. This study investigates the influence of typhoon winds on ports in the central to northern areas of the Taiwan Strait, considering different typhoon paths, by utilizing ground automatic station observations and numerical model forecasts. Furthermore, this research examines deviations in wind field forecasts generated by the ECMWF numerical model and the subsequent correction of surface wind patterns. The results indicate that: (1) maximum wind speeds during typhoons following various paths are most notable in the proximity of coastal islands near Putian, Fujian province, predominantly due to the topographical effects of the strait. (2) Wind speeds at individual stations are contingent on the typhoon’s trajectory, while the pressure difference could serve as a reliable indicator of typhoon intensity and onset timing. (3) Following polynomial fitting correction, the forecast deviations are reduced by 37% for the u component and 40% for the v component. The score for the u component increases notably from 41.60 to 63.17 after correction, representing an improvement of 51.85%, while the v component score rises significantly from 29.33 to 48.89, showing an enhancement of 66.70%. This research has implications for future forecasts of typhoon winds that impact ports in the central and northern sections of the Taiwan Strait, meeting the meteorological service needs of cargo ships entering the port and better serving the sustainable development of the local economy and society.

Geometry effects on wind fields and consequent wave generation in the Strait of Hormuz: A case study

This study investigates the impact of surface wind forcing on wave conditions in the Strait of Hormuz, a region with complex wave interactions. The WRF model is used to simulate the wind field with higher accuracy, enabling the generation of waves for both normal and storm conditions in 2011. A sensitivity analysis examines the WRF model's simulated wind field with variations in initial and boundary conditions, spatial resolutions, and adopting two static topographic datasets. Comparisons between simulated wave parameters and observed data from ADCPs at two stations flanking the strait reveal the importance of accurate wind forcing for obtaining a realistic estimation of wave conditions. Wave errors are found to be influenced by fetch length, with larger errors observed for shorter fetches (∼100 km). However, these errors gradually decrease as the distance from the coast increases. The study emphasizes the importance of incorporating accurate wind data and considering fetch characteristics when simulating wave conditions, which can enhance maritime safety, coastal engineering, and offshore operations in the Strait of Hormuz and other similar regions worldwide. In conclusion, small-scale wind and waves features over the Strait of Hormuz can be better captured with a combination of higher-resolution wind modeling and wave simulation grids with higher spatial resolution.

The Value of Energy Storage in Facilitating Renewables: A Northeast Area Analysis

The cross-regional and large-scale transmission of new energy power is an inevitable requirement to address the counter-distributed characteristics of wind and solar resources and load centers, as well as to achieve carbon neutrality. However, the inherent stochastic, intermittent, and fluctuating nature of wind and solar power poses challenges for the stable bundled dispatch of new energy. Leveraging the regulation flexibility of energy storage offers a potential solution to mitigate new energy fluctuations, enhance the flexibility of the hybrid energy systems, and promote bundled dispatch of new energy for external transmission. This paper takes energy storage as an example and proposes a capacity configuration optimization method for a hybrid energy system. The system is composed of wind power, solar power, and energy storage, denoted by the wind–solar–energy storage hybrid energy systems. The objective is to quantify the support provided by energy storage to bundled dispatch of new energy, namely determining the new energy transmission capacity that can be sustained per unit of energy storage. The results demonstrate that the proposed method effectively improves the bundled dispatch capacity of new energy. Moreover, the obtained configuration results can be tailored based on different wind–solar ratios, allowable fluctuation rates, and transmission channel capacities, rendering the approach highly valuable for engineering practicality.

Temporal collaborative attention for wind power forecasting

Wind power serves as a clean and sustainable form of energy. However, its generation is fraught with variability and uncertainty, owing to the stochastic and dynamic characteristics of wind. Accurate forecasting of wind power is indispensable for the efficient planning, operation, and grid integration of wind energy systems. In this paper, we introduce a novel forecasting method termed Temporal Collaborative Attention (TCOAT). This data-driven approach is designed to capture both temporal and spatial dependencies in wind power generation data, as well as discern long-term and short-term patterns. Utilizing attention mechanisms, TCOAT dynamically adjusts the weights of each input variable and time step based on their contextual relevance for forecasting. Furthermore, the method employs collaborative attention units to assimilate directional and global information from the input data. It also explicitly models the interactions and correlations among different variables or time steps through the use of self-attention and cross-attention mechanisms. To integrate long-term and short-term information effectively, TCOAT incorporates a temporal fusion layer that employs concatenation and mapping operations, along with hierarchical feature extraction and aggregation. We validate the efficacy of TCOAT through extensive experiments on a real-world wind power generation dataset from Greece and compare its performance against twenty-two state-of-the-art methods. Experimental results demonstrate that TCOAT outperforms existing methods in terms of both accuracy and robustness in wind power forecasting. Moreover, we conduct a generality study on an additional real-world dataset from a different climate condition and wind power characteristics. The results show that TCOAT can achieve comparable or better performance than the state-of-the-art methods, confirming the generalization ability of TCOAT.

The Impact of Dust Deposition on PV Panels’ Efficiency and Mitigation Solutions: Review Article

Conversion efficiency, power production, and cost of PV panels’ energy are remarkably impacted by external factors including temperature, wind, humidity, dust aggregation, and induction characteristics of the PV system such as tilt angle, altitude, and orientation. One of the prominent elements affecting PV panel performance and capability is dust. Nonetheless, dust features including size, shape, type, etc. are geologically known. Several mitigation methods have been studied for the reduction of dust concentration on the exterior face of the PV modules. The outcomes have demonstrated that dust concentration and pollutants remarkably affect the PV panel energy production. This paper reviews the recently developed research on the outcomes of the dust effect on PV panels in different locations and meets the needs of future research on this subject. Moreover, different cleaning methods that could be advantageous for future researchers in opting for the most applicable technique for dust removal are reviewed.

Comparative analysis of different methods in estimating wind speed distribution, and evaluation of large‐scale wind turbine performance in Rahva‐Bitlis, Turkey

AbstractIn this study, wind characteristics and electricity generation potential from wind energy were investigated in the Bitlis‐Rahva region in eastern Turkey. Ten‐minute wind data from the Bitlis meteorological station were used in the study. The determination of the wind speed (WS) distribution was carried out using the WindPRO program together with the Weibull and Rayleigh distributions. R2, RMSE, and χ2 goodness‐of‐fit tests were used to measure the accuracy of the velocity distribution process. A digital elevation model of the power generation site was created to evaluate wind data and predict turbine performance. Wind power generation performance was evaluated using five different wind turbines (WTs). A power curve model was developed for the WTs to determine the capacity for energy generation. According to the error tests, it has been determined that the results obtained with the WindPRO program can represent the observed wind data most accurately. The results from the WindPRO program analysis showed an average annual WS of 3.26 m/s and a power density of 49.77 W/m2. Increasing height was found to increase WS and power density. The prevailing wind direction was found to be South‐Southwest with a frequency value of 27.5%. The largest capacity factor was obtained from the WT with the largest rotor diameter and rated power. Out of all the WTs examined, the turbine with the largest rated power and rotor diameter produced the greatest amount of energy. According to the capacity factor values calculated for the selected WTs, the region is not considered efficient for wind energy investments. However, as WS and power density increase with increasing altitude, it is thought that different higher parts of the region may be more efficient in terms of wind energy utilization.

Multi‐Instruments Observation of Ionospheric‐Thermospheric Dynamic Coupling Over Mohe (53.5°N, 122.3°E) During the April 2023 Geomagnetic Storm

AbstractThe state and variations of the Ionosphere‐Thermosphere (I‐T) system are strongly influenced by dynamical processes, with these effects being amplified during intense space environment disturbances such as geomagnetic storms, producing multi‐scale disturbance features in the I‐T system. The redistribution of energy and momentum through the dynamical processes is currently not well understood. Unfortunately, the dearth of thermospheric observations has yielded limited studies capable of monitoring and analyzing the I‐T dynamical coupling during storms using co‐located measurements. This work examines the responses of the I‐T system during the April 2023 geomagnetic storm based on high‐resolution continuous I‐T system observations at Mohe observatory, a middle latitude station. Both large‐scale features and short‐period oscillations were identified in multiple key parameters of the I‐T system. Similar disturbed patterns in thermospheric winds occurred during the main and recovery phases of the geomagnetic storm. However, the oscillation features in many parameters of the I‐T system are only observed during the main phase. The results of concurrent I‐T system observations unveil the oscillation features of thermospheric winds, temperatures, the ionospheric F2 peak height, electron density, and total electron content. These findings reveal the important influence of wind divergence on thermospheric temperature disturbances and its modulatory effect on ionospheric disturbances.

Wind field characteristics of asymmetric bridge deck for a road-rail same-story bridge

The purpose of this study is to investigate the flow field characteristics of the road-rail same-story asymmetric bridge deck and the influence of the asymmetric arrangement of the bridge deck on the flow field of the main girders. Numerical simulation tests were conducted on this bridge to analyze the distribution characteristics of the flow field near the main girder, as well as the aerodynamic characteristics of the railway bridge deck and highway bridge deck under different wind speeds and directions. The results indicate that the wind speed has less influence on the flow field distribution and aerodynamic characteristics of the road-rail same-story asymmetric bridge deck, but the incoming flow direction has a significant impact on its flow field characteristics. Compared to the railway bridge deck, during the reattachment position of the airflow, the highway bridge deck moves toward the windward side, and the volume of the separation bubble has been reduced, thus improving the effect on the negative pressure area of the railway bridge deck. The road-rail same-story asymmetric bridge deck has different aerodynamic interference characteristics for different wind speeds and different wind directions.

Wind Energy Assessment Using Weibull Distribution with Different Numerical Estimation Methods: A Case Study

The demand for electrical energy is increasing every day, which is one of the critical challenges facing the world today. Hence, the necessity of turning to clean renewable energy sources that are not harmful to the environment as an alternative to the traditional generation based on fossil fuels has become more important than ever before. Wind power is one of the renewable sources that provides a clean solution to generate electricity. In this context, the Kingdom of Saudi Arabia announces renewable energy projects to generate 9 GW from wind in 2032. Hence, the aim of this paper is to investigate the most suitable method of Weibull parameter estimation in order to predict wind characteristics and employ it for wind energy assessment in the Qassim region located in the center of the country. In this study, wind data is collected from NASA's forecasts of global energy resources for 2010–2015 based on their availability at altitudes of 10m and 50m and analyzed by using six different methods for Weibull parameter estimation: the graphical method (GM), standard deviation method (SDM), energy pattern factor method (EPF), moment method (MM), alternative maximum likelihood method (AMLM), and novel energy pattern factor method (NEPF). The efficiency of each method is tested by calculating the root mean square error (RMSE) and the relative wind power density error (RPDE). The comparison shows that the most appropriate method for estimating wind power density in the country is the Moment Method (MM), with the lowest RPDE ratio equal to 0.2018%. It has been found that the wind power density in the Qassim region falls into the class 1 category, as it is less than 100 W/m2 at a height of 10m and less than 200 W/m2at an altitude of 50m. The results show the region is only suitable for small off-grid projects. Doi: 10.28991/ESJ-2023-07-06-024 Full Text: PDF

Ion Kinetics of Plasma Interchange Reconnection in the Lower Solar Corona

The exploration of the inner heliosphere by the Parker Solar Probe has revealed a highly structured solar wind with ubiquitous deflections from the Parker spiral, known as switchbacks. Interchange reconnection (IR) may play an important role in generating these switchbacks, by forming unstable particle distributions that generate wave activity that in turn may evolve to such structures. IR occurs in very low-beta plasmas and in the presence of strong guiding fields. Although IR is unlikely to release enough energy to provide an important contribution to the heating and acceleration of the solar wind, it affects the way the solar wind is connected to its sources, connecting open field lines to regions of closed fields. This “switching on” provides a mechanism by which the plasma near coronal hole boundaries can mix with that trapped inside the closed loops. This mixing can lead to a new energy balance. It may significantly change the characteristics of the solar wind because this plasma is already preheated and can potentially have quite different density and particle distributions. It not only replenishes the solar wind, but also affects the electric field, which in turn affects the energy balance. This interpenetration is manifested by the formation of a bimodal ion distribution, with a core and a beam-like population. Such distributions are indeed frequently observed by the Parker Solar Probe. Here we provide a first step toward assessing the role of such processes in accelerating and heating the solar wind.

Downscaling of surface wind forecasts using convolutional neural networks

Abstract. Near-surface winds over complex terrain generally feature a large variability at the local scale. Forecasting these winds requires high-resolution numerical weather prediction (NWP) models, which drastically increase the duration of simulations and hinder them in running on a routine basis. Nevertheless, downscaling methods can help in forecasting such wind flows at limited numerical cost. In this study, we present a statistical downscaling of WRF (Weather Research and Forecasting) wind forecasts over southeastern France (including the southwestern part of the Alps) from its original 9 km resolution onto a 1 km resolution grid (1 km NWP model outputs are used to fit our statistical models). Downscaling is performed using convolutional neural networks (CNNs), which are the most powerful machine learning tool for processing images or any kind of gridded data, as demonstrated by recent studies dealing with wind forecast downscaling. The previous studies mostly focused on testing new model architectures. In this study, we aimed to extend these works by exploring different output variables and their associated loss function. We found that there is no one approach that outperforms the others in terms of both the direction and the speed at the same time. Finally, the best overall performance is obtained by combining two CNNs, one dedicated to the direction forecast based on the calculation of the normalized wind components using a customized mean squared error (MSE) loss function and the other dedicated to the speed forecast based on the calculation of the wind components and using another customized MSE loss function. Local-scale, topography-related wind features, which were poorly forecast at 9 km, are now well reproduced, both for speed (e.g., acceleration on the ridge, leeward deceleration, sheltering in valleys) and direction (deflection, valley channeling). There is a general improvement in the forecast, especially during the nighttime stable stratification period, which is the most difficult period to forecast. The result is that, after downscaling, the wind speed bias is reduced from −0.55 to −0.01 m s−1, the wind speed MAE is reduced from 1.02 to 0.69 m s−1 (32 % reduction) and the wind direction MAE is reduced from 25.9 to 15.5∘ (40 % reduction) in comparison with the 9 km resolution forecast.

Experimental study of the impact of upstream mountain terrain and urban exposure on approaching wind characteristics

The approaching wind profiles have a significant impact on the wind load of the structures as well as the urban climate, pollutant diffusion, and thermal comfort. Therefore, the study of its evolution is gaining attention as the city sparrows. This paper aims to study the effects of topography and morphology on the characteristics of the approaching wind. Wind tunnel tests were conducted to observe the mean velocity profiles downstream of three kinds of common terrain, which are roughness change from open to urban exposure, open exposure behind mountain terrain, and urban exposure behind mountain terrain. The results show that the ESDU transitional model overestimates velocity inside the IBL and underestimates IBL heights compared with experimental results. The rough exposure behind the mountain leads to smaller recirculation zones and a shorter reattachment location downstream compared with that of open exposure behind mountain. In addition, the evolution of mean velocity profiles over urban exposure behind the mountain is also compared with the results estimated according to current wind load provisions. Unfortunately, none of the current wind load provisions yields a reasonable estimation of the mean velocity profiles. The study aims to provide useful references in the study of the wind environment in mountainous urban area and the estimation of wind load on structures, as well as the future codification of wind load provisions.

Wavelet characterizing the non-stationary features of mountain valley winds both in frequency and time domain

This study aimed to quantify and evaluate the non-stationary characteristics of wind speed in mountain canyon terrain. A non-stationarity index was proposed based on continuous wavelet transform to quantitatively evaluate the non-stationarity of measured wind speed samples in both time and frequency domains. Subsequently, the effect of sample length and observation time interval of wind speed samples on the non-stationarity index was investigated. In addition, the non-stationarity of mountain canyon winds was compared with that of normal climate winds under the same sample length and observation time interval. The results indicate that the non-stationarity index based on wavelet transform can quantitatively evaluate the non-stationary characteristics of wind speed. With an increase in the sample length of wind speed series, the non-stationarity of wind speed increase gradually, and its probability distribution becomes more positively skewed. When the sample length of wind speed does not exceed 10 min, the probability distribution of non-stationarity index for mountain valley terrain and normal climate winds is not significantly different, which implies that it is reasonable for most countries to use a 10-min statistical length to calculate average wind speed. However, the difference in the probability distribution of non-stationarity index between mountain and normal climate winds significantly increases when the sample length exceeds 10 min. Besides, the non-stationarity index can reflect the non-stationary characteristics of wind speed series at different frequency components. Higher frequency components in wind speed exhibit stronger non-stationary characteristics. Moreover, mountain winds exhibit stronger non-stationary characteristics than normal climate winds in amplitude and frequency, especially the high-frequency components in wind speed series with long sample lengths.

Operational Characteristics Assessment of a Wind–Solar–Hydro Hybrid Power System with Regulating Hydropower

Renewable energy generation technology, as an alternative to traditional coal-fired power generation, is receiving increasing attention. However, the intermittent characteristics of wind and solar energy pose certain challenges to the stable operation of power grids. This requires a better understanding of the operational characteristics of renewable energy to improve the comprehensive efficiency. To achieve this, firstly, four indicators (i.e., average fluctuation magnitude, Richards–Baker flashiness, average climbing rate, and change in the time-averaged value) within a single-evaluation-indicator framework are proposed to quantitatively evaluate the fluctuation characteristics of wind, solar, and hydropower and a wind–solar–hydro hybrid power system. Secondly, a comprehensive evaluation indicator is developed by scientifically assigning and recombining the four indicators using entropy weight theory. Furthermore, the comprehensive evaluation index is applied to the wind–solar–hydro hybrid power system to determine the operational characteristics of subsystems and a complementary system at different time scales. Finally, the load tracking coefficient and coupling degree are used to quantify the complementarity degree of the hybrid power system. It is found that the fluctuation degree of the hybrid power system is smaller than that of the individual power system. Meanwhile, both fluctuation and complementary characteristics are strengthened with the increase in time scale. The proposed methods and results shift the volatility from an abstract concept to concrete representation, providing a new perspective and reference for evaluating the operational characteristics of the hybrid power system to achieve power system planning and scheduling.

Day-ahead wind power forecasting based on feature extraction integrating vertical layer wind characteristics in complex terrain

Accurate wind power forecasts help establish efficient power supply plans and stabilize power systems. For long-term forecasts, the outputs of numerical weather prediction (NWP) models are pipelined as inputs for the statistical post-processing model, underscoring the necessity of understanding forecasts simulated from NWP to enhance power prediction accuracy.This study aims to enhance the quality of wind power forecasts in complex terrains, focusing on identifying and processing appropriate wind features of vertical layers simulated by NWP. In complex terrains with significant terrain variability, it is crucial to meticulously analyze and select the optimal vertical layer for each site or turbine individually, as simulated wind speeds at higher vertical layers than those used in previous research could potentially yield stronger correlations. Furthermore, we introduce a data processing technique that integrates wind characteristics across vertical layers, utilizing Principal Component Analysis (PCA). This approach not only provides physically intuitive results but also demonstrates enhanced performance compared to other feature selection methods. By selecting the appropriate vertical layers and applying the proper feature extraction, for wind farms situated in complex terrains in Korea, the annual normalized mean absolute error can be reduced by up to 1.2 %.