• Journal of Korean Association for Spatial Structures
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• v.16 no.1
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• pp.65-72
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• 2016

Aerodynamic performance of solar wing system has been evaluated through wind tunnel test. The test model has 12 panels, each supported by 2 cables. The panels were installed horizontally flat, and gaps between panels were set constant. Sag ratios of 2% and 5%, and wind directions between $0^{\circ}$ and $90^{\circ}$ were considered. Mass of test model was determined considering the mass of full scale model, and Froude number and Elastic parameter were satisfied by adjusting the mean wind speed. From the wind tunnel test, it was found that the aerodynamic performance of the solar wing system is very dependent on the wind directions and sag ratios. When the sag was 2%, the fluctuating displacements between the wind directions of $0^{\circ}$ and $30^{\circ}$ increase proportionally to the square of the mean wind speed, implying buffeting-like vibration and a sudden increase in fluctuating displacement was found at large mean wind speed for the wind directions larger than $40^{\circ}$. When the wind direction was larger than $60^{\circ}$, a sudden increase was found both at low and large mean wind speed. When the sag ratio is 5%, distribution of mean displacements is different from that of sag ratio of 2%, and the fluctuating displacements show very different trend from that of sag ratio of 2%.

• Wind and Structures
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• v.13 no.5
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• pp.433-449
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• 2010

Wind tunnel model tests were conducted for a residential apartment block located within the complex terrain of The Hong Kong University of Science and Technology (HKUST). The test building is typical of medium-rise residential buildings in Hong Kong. The model study was conducted using modelling techniques and assumptions that are commonly used to predict design wind loads and pressures for buildings sited in regions of significant topography. Results for the building model with and without the surrounding topography were compared to investigate the effects of far-field and near-field topography on wind characteristics at the test building site and wind-induced external pressure coefficients at key locations on the building facade. The study also compared the wind tunnel test results to topographic multipliers and external pressure coefficients determined from nine international design standards. Differences between the external pressure coefficients stipulated in the various standards will be exacerbated when they are combined with the respective topographic multipliers.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.7
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• pp.54-61
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• 2015

This paper presents short-term wind farm power forecasting method using multivariate analysis and time series. Based on factor analysis, the proposed method makes new independent variables which newly composed by raw independent variables such as wind speed, ramp rate, wind power. Newly created variables are used in the time series model for forecasting wind farm power. To demonstrate the improved accuracy, the proposed method is compared with persistence model commonly used as reference in wind power forecasting using data from Jeju Island. The results of case studies are presented to show the effectiveness of the proposed forecasting method.

• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.163-168
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• 2015

In order to integrate high wind generation resources into power grid, it is an essential to predict power outputs of wind generating resources. As wind farm outputs depend on natural wind resources that vary over space and time, spatial modeling based on geographic information such as latitude and longitude is needed to estimate power outputs of wind generation resources. In this paper, we introduce the basic concept of spatial modeling and present the spatial prediction model based on Kriging techniques. The empirical data, wind farm power output in Texas, is considered to verify the proposed prediction model.

• Wind and Structures
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• v.31 no.3
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• pp.217-227
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• 2020

Based on translation models, both Gaussian and non-Gaussian wind fields are generated using spectral representation method for investigating the influence of non-Gaussian characteristics and directivity effect of wind load on fatigue damage of wind turbine. Using the blade aerodynamic model and multi-body dynamics, dynamic responses are calculated. Using linear damage accumulation theory and linear crack propagation theory, crack initiation life and crack propagation life are discussed with consideration of the joint probability density distribution of the wind direction and mean wind speed in detail. The result shows that non-Gaussian characteristics of wind load have less influence on fatigue life of wind turbine in the area with smaller annual mean wind speeds. Whereas, the influence becomes significant with the increase of the annual mean wind speed. When the annual mean wind speeds are 7 m/s and 9 m/s at hub height of 90 m, the crack initiation lives under softening non-Gaussian wind decrease by 10% compared with Gaussian wind fields or at higher hub height. The study indicates that the consideration of the influence of softening non-Gaussian characteristics of wind inflows can significantly decrease the fatigue life, and, if neglected, it can result in non-conservative fatigue life estimates for the areas with higher annual mean wind speeds.

• Wind and Structures
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• v.23 no.5
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• pp.465-483
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• 2016

This study aims to enhance the understanding of the surface pressure distribution around rectangular bodies, by considering aspects such as the suction pressure at the leading edge on the top and side faces when the body aspect ratio and wind direction are changed. We carried out wind tunnel measurements and numerical simulations of flow around a series of rectangular bodies (a cube and two rectangular bodies) that were placed in a deep turbulent boundary layer. Based on a modern numerical platform, the Navier-Stokes equations with the typical two-equation model (i.e., the standard $k-{\varepsilon}$ model) were solved, and the results were compared with the wind tunnel measurement data. Regarding the turbulence model, the results of the $k-{\varepsilon}$ model are in overall agreement with the experimental results, including the existing data. However, because of the blockage effects in the computational domain, the pressure recovery region is underpredicted compared to the experimental data. In addition, the $k-{\varepsilon}$ model sometimes will fail to capture the exact flow features. The primary emphasis in this study is on the flow characteristics around rectangular bodies with various aspect ratios and approaching wind directions. The aspect ratio and wind direction influence the type of wake that is generated and ultimately the structural loading and pressure, and in particular, the structural excitation. The results show that the surface pressure variation is highly dependent upon the approaching wind direction, especially on the top and side faces of the cube. In addition, the transverse width has a substantial effect on the variations in surface pressure around the bodies, while the longitudinal length has less influence compared to the transverse width.

• Wind and Structures
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• v.10 no.3
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• pp.287-300
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• 2007

Wind action is a factor of fundamental importance in the structural design of light or slender constructions. Codes for structural design usually assume that the incident mean wind velocity is parallel to the ground, which constitutes a valid simplification for frequent winds caused by meteorological phenomena such as Extratropical Storms (EPS) or Tropical Storms. Wind effects due to other phenomena, such as thunderstorms, and its combination with EPS winds in so-called squall lines, are simply neglected. In this paper a model that describes the three-dimensional wind velocity field originated from a downburst in a thunderstorm (TS) is proposed. The model is based on a semi empirical representation of an axially-symmetrical flow line pattern that describes a stationary field, modulated by a function that accounts for the evolution of the wind velocity with time. The model allows the generation of a spatially and temporally variable velocity field, which also includes a fluctuating component of the velocity. All parameters employed in the model are related to meteorological variables, which are susceptible of statistical assessment. A background wind is also considered, in order to account for the translational velocity of the thunderstorm, normally due to local wind conditions. When the translation of the TS is caused by an EPS, a squall line is produced, causing the highest wind velocities associated with TS events. The resulting vertical velocity profiles were also studied and compared with existing models, such as the profiles proposed by Vicroy, et al. (1992) and Wood and Kwok (1998). The present model predicts horizontal velocity profiles that depend on the distance to the storm center, effect not considered by previous models, although the various proposals are globally compatible. The model can be applied in any region of interest, once the relevant meteorological variables are known, to simulate the excitation due to TS winds in the design of transmission lines, long-span crossings, cable-stayed bridges, towers or similar structures.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.34-34
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• 2023

The Chah-Nimeh reservoirs, which are a sort of natural lakes located in the border of Iran and Afghanistan, are the main drinking and agricultural water resources of Sistan arid region. Considering the occurrence of intense seasonal wind, locally known as levar wind, this study aims to explore the possibility to provide a TSM (Total Suspended Matter) monitoring model of Chah-Nimeh reservoirs using multi-temporal satellite images and in-situ wind speed data. The results show that a strong correlation between TSM concentration and wind speed are present. The developed empirical model indicated high performance in retrieving spatiotemporal distribution of the TSM concentration with R²=0.98 and RMSE=0.92g/m³. Following this observation, we also consider a machine learning-based model to predicts the average TSM using only wind speed. We connect our in-situ wind speed data to the TSM data generated from the inversion of multi-temporal satellite imagery to train a neural network based mode l(Wind2TSM-Net). Examining Wind2TSM-Net model indicates this model can retrieve the TSM accurately utilizing only wind speed (R²=0.88 and RMSE=1.97g/m³). Moreover, this results of this study show tha the TSM concentration can be estimated using only in situ wind speed data independent of the satellite images. Specifically, such model can supply a temporally persistent means of monitoring TSM that is not limited by the temporal resolution of imagery or the cloud cover problem in the optical remote sensing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2202-2211
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• 2010

The wind power prediction system is composed of a meteorological forecasting module, calculation module of wind power output and HMI(Human Machine Interface) visualization system. The final information from this system is a short-term (6hr ahead) and mid-term (48hr ahead) wind power prediction value. The meteorological forecasting module for wind speed and direction forecasting is a combination of physical and statistical model. In this system, the WRF(Weather Research and Forecasting) model, which is a three-dimensional numerical weather model, is used as the physical model and the GFS(Global Forecasting System) models is used for initial condition forecasting. The 100m resolution terrain data is used to improve the accuracy of this system. In addition, optimization of the physical model carried out using historic weather data in Jeju. The mid-term prediction value from the physical model is used in the statistical method for a short-term prediction. The final power prediction is calculated using an optimal adjustment between the currently observed data and data predicted from the power curve model. The final wind power prediction value is provided to customs using a HMI visualization system. The aim of this study is to further improve the accuracy of this prediction system and develop a practical system for power system operation and the energy market in the Smart-Grid.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.585-592
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• 2013

As the needs for alternative energy and renewable energy increase, there has been a lot of investment in developing wind energy, which does not cause air pollution nor the greenhouse gas effect. Wind energy is an environment friendly energy that is unlimited in its resources and is possible to be produced wherever the wind blows. However, since wind energy heavily relies on wind that has unreliable characteristics, it may be difficult to have efficient energy transmissions. For this reason, an important factor in wind energy forecasting is the estimation of available wind power. In this study, Gunsan wind farm data was used to compare ARMA model to neural network model to analyze for more accurate prediction of wind power generation. As a result, the neural network model was better than the ARMA model in the accuracy of the wind power predictions.