• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2268-2277
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• 2017

As constantly increasing wind power penetrates power grid, wind power plants (WPPs) are exerting a direct influence on the traditional power system. Most of WPPs are using variable speed constant frequency (VSCF) wind turbines equipped with doubly fed induction generators (DFIGs) due to their high efficiency over other wind turbine generators (WTGs). Therefore, the analysis of DFIG has attracted considerable attention. Precisely measuring optimum reference speed is basis of utilized maximum wind power in electric power generation. If the measurement of wind speed can be easily taken, the reference of rotation speed can be easily calculated by known system's parameters. However, considering the varying wind speed at different locations of blade, the turbulence and tower shadow also increase the difficulty of its measurement. The aim of this study is to design fuzzy controllers to replace the wind speedometer to track the optimum generator speed based on the errors of generator output power and rotation speed in varying wind speed. Besides, this paper proposes the fuzzy adaptive PID control to replace traditional PID control under rated wind speed in variable-pitch wind turbine, which can detect and analyze important aspects, such as unforeseeable conditions, parameters delay and interference in the control process, and conducts online optimal adjustment of PID parameters to fulfill the requirement of variable pitch control system.

• Wind and Structures
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• v.32 no.5
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• pp.487-499
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• 2021

The wind-blown sand effect on the high-speed train is investigated. Unsteady RANS equation and the SST k-ω turbulent model coupled with the discrete phase model (DPM) are utilized to simulate the two-phase of air-sand. Sand impact force is calculated based on the Hertzian impact theory. The different cases, including various wind velocity, train speed, sand particle diameter, were simulated. The train's flow field characteristics and the sand impact force were analyzed. The results show that the sand environment makes the pressure increase under different wind velocity and train speed situations. Sand impact force increases with the increasing train speed and sand particle diameter under the same particle mass flow rate. The train aerodynamic force connected with sand impact force when the train running in the wind-sand environment were compared with the aerodynamic force when the train running in the pure wind environment. The results show that the head car longitudinal force increase with wind speed increasing. When the crosswind speed is larger than 35m/s, the effect of the wind- sand environment on the train increases obviously. The longitudinal force of head car increases 23% and lateral force of tail increases 12% comparing to the pure wind environment. The sand concentration in air is the most important factor which influences the sand impact force on the train.

• Wind and Structures
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• v.32 no.2
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• pp.81-87
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• 2021

The aim of the current study is to compare the performance of large 2 MW and 3 MW wind turbines operating on existing onshore wind farms using Blade Element Momentum (BEM) theory and Angular Momentum (AM) theory and illustrate the performance characteristic curves of the turbines as a function of wind speed (U∞). To achieve this, the measurement data obtained from two different Wind Energy Power Plants (WEPPs) located in the Hatay region of Turkey was used. Two different horizontal-axis wind turbines with capacities of 2 MW and 3 MW were selected for evaluation and comparison. The hub-height wind speed (UD), turbine power output (P), atmospheric air temperature (Tatm) and turbine rotational speed (Ω) data were used in the evaluation of the turbine performance characteristics. Curves of turbine power output (P), axial flow induction factor (a), turbine rotational speed (Ω), turbine power coefficient (CP), blade tip speed ratio (λ), thrust force coefficient (CT) and thrust force (T) as a function of U∞ were obtained for the 2 MW and 3 MW wind turbines and these characteristic curves were compared. Results revealed that, for the same wind speed conditions, the higher-capacity wind turbine (3 MW) was operating at higher turbine power coefficient rates, while rotating at lower rotational speed ratios than the lower-capacity wind turbine (2 MW).

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1548-1555
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• 2016

This paper presents an application of time series analysis in hourly wind speed simulation and forecast in Jeju Island, Korea. Autoregressive - moving average (ARMA) model, which is well in description of random data characteristics, is used to analyze historical wind speed data (from year of 2010 to 2012). The ARMA model requires stationary variables of data is satisfied by power law transformation and standardization. In this study, the autocorrelation analysis, Bayesian information criterion and general least squares algorithm is implemented to identify and estimate parameters of wind speed model. The ARMA (2,1) models, fitted to the wind speed data, simulate reference year and forecast hourly wind speed in Jeju Island.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.331-334
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• 2003

In this paper, on the subject of a speed control wind turbine, the type of wind speed reference decision between conventional MPPT tracking speed control and MPPT with LPF(Low Pass Filter) speed control algorithm are introduced and its performances are compared using a model based on MATLAB Simulink, and to get more realistic output data, the stored wind data as its wind speed input from 30kW wind power system in Buan, Haechang is used.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.327-333
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• 2019

Wind speed data constitute important weather information for aircrafts flying at low altitudes, such as drones. Currently, the accuracy of low altitude wind predictions is much lower than that of high-altitude wind predictions. Deep neural networks are proposed in this study as a method to improve wind speed forecast information. Deep neural networks mimic the learning process of the interactions among neurons in the brain, and it is used in various fields, such as recognition of image, sound, and texts, image and natural language processing, and pattern recognition in time-series. In this study, the deep neural network model is constructed using the wind prediction values generated by the numerical model as an input to improve the wind speed forecasts. Using the ground wind speed forecast data collected at the Boseong Meteorological Observation Tower, wind speed forecast values obtained by the numerical model are compared with those obtained by the model proposed in this study for the verification of the validity and compatibility of the proposed model.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.205-213
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• 2014

A wind generator (WG) maximum power point tracking (MPPT) system is presented here. It comprises of a variable-speed wind generator, a high-efficiency boost-type dc/dc converter and a control unit. The advantages of the aimed system are that it does not call for the knowledge of the wind speed or the optimal power characteristics and that it operates at a variable speed, thus providing high efficiency. The WG operates at variable speed and thus suffers lower stress on the shafts and gears compared to constant-speed systems. It results in a better exploitation of the available wind energy, especially in the low wind-speed range of 2.5-4.5 m/s. It does not depend on the WG wind and rotor-speed ratings or the dc/dc converter power rating. Higher reliability, lower complexity and cost, and less mechanical stress of the WG. It can be applied to battery-charging applications.

• Journal of Wind Energy
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• v.9 no.4
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• pp.9-15
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• 2018

In a previous study, a technique for measuring wind speed and direction by using a roll-rotating three-axis ultrasonic anemometer was proposed and verified by wind tunnel tests. In the tests, instead of a roll sensor, roll angle was trimmed to make no up flow in the transformed wind speeds. Verification was done in point of the residual error of the rotation effect treatment. In this study, roll angle was measured from the roll motor encoder and the transformed wind speed and direction on the test section axis were compared with the ones provided to the test section. As a result, up to yaw $20^{\circ}$ at a wind speed of 12 m/sec or over, the RMS error of wind speed was within the double of the ultrasonic anemometer error. But at yaw $30^{\circ}$, it was over the double of the ultrasonic anemometer error. Regardless of wind speed, at yaw $20^{\circ}$ and $30^{\circ}$, the direction error was within the double of the ultrasonic anemometer error. But at yaw $10^{\circ}$ or less, it was within the error of the ultrasonic anemometer itself. This is a very favorable characteristic to be used for wind turbine yaw control.

• Journal of Ocean Engineering and Technology
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• v.35 no.6
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• pp.414-425
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• 2021

Overcrowding of high-rise buildings in urban zones change the airflow pattern in the surrounding areas. This causes building wind, which adversely affects the wind environment. Building wind can generate more serious social damage under extreme weather conditions such as typhoons. In this study, to analyze the wind speed and wind speed ratio quantitatively, we installed five anemometers in Haeundae, where high-rise buildings are dense, and conducted on-site monitoring in the event of typhoon OMAIS to determine the characteristics of wind over skyscraper towers surround the other buildings. At point M-2, where the strongest wind speed was measured, the maximum average wind speed in 1 min was observed to be 28.99 m/s, which was 1.7 times stronger than that at the ocean observatory, of 17.0 m/s, at the same time. Furthermore, when the wind speed at the ocean observatory was 8.2 m/s, a strong wind speed of 24 m/s was blowing at point M-2, and the wind speed ratio compared to that at the ocean observatory was 2.92. It is judged that winds 2-3 times stronger than those at the surrounding areas can be induced under certain conditions due to the building wind effect. To verify the degree of wind speed, we introduced the Beaufort wind scale. The Beaufort numbers of wind speed data for the ocean observatory were mostly distributed from 2 to 6, and the maximum value was 8; however, for the observation point, values from 9 to 11 were observed. Through this study, it was possible to determine the characteristics of the wind environment in the area around high-rise buildings due to the building wind effect.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.156-163
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• 2005

This study was attempted to provide some fundamental data for safety structrural design of biological production facility. Wind load and snow load, acting on agricultural structures is working more sensitive than any other load. Therefore, wind speed and snow depth according to return periods for design load estimation were calculated by frequency analysis using the weather data(maximum instantaneous wind speed, maximum wind speed, maximum depth of snow cover and fall) of 68 regions in Korea. Equations for estimating maximum instantaneous wind speed with maximum wind speed were developed for all, inland and seaside regions. The results were about the same as the current eqution in general. Design wind speed and snow depth according to return periods were calculated and Local design wind load and snow load depending on return periods were presented together with iso-wind speed and iso-snow depth maps. The calculated design snow depth by maximum depth of snow cover were higher than design snow depth by maximum depth of snow fall. Considering wind speed and snow depth, protected cultivation is very difficult in Ullungdo, Gangwon seaside and contiguity inland regions, and strong structural design is needed in the west-south seaside against wind speed, and structure design of biological production facility in these regions need special consideration.