• Journal of the Korean Solar Energy Society
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• v.32 no.3
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• pp.146-152
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• 2012

To install a wind power generator, the survey on the wind environment resources must be conducted in advance. The survey on the wind environment resources is to collect and analyze data regarding the wind speed and direction on a data logger. The data logger consists of a sensor, signal processing circuit and storage device. According to the analysis of the stored data, the amount of power generation by the types of generators can be predicted and the most optimal generator including safety grade can be selected, and in case of installing a generator in the future, it can be utilized as basic data regarding supporting base and foundation construction method of survey points. Data logger was developed for a small wind power generator that is suitable for the international standard(IEC 61400) by using DSP-F28335 micro controller in this paper. It was developed to measure the wind speed of 1 [m/s]~17 [m/s], the wind direction of 0 [$^{\circ}$]~359 [$^{\circ}$], and temperature of -30 [$^{\circ}C$]~50 [$^{\circ}C$], and the comparative experiment with other companies' data loggers was conducted, and an error was measured to be less than ${\pm}0.1$ [m/s] for wind speed and less than +1 [$^{\circ}$] for wind direction.

• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.1-8
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• 2011

In this study, we performed a sensitivity analysis to see how the true north error of a wind direction vane installed to a meteorological mast affects predictions of the annual-average wind speed and the annual energy production. For this study, two meteorological masts were installed with a distance of about 4km on the ridge in complex terrain and the wind speed and direction were measured for one year. Cross predictions of the wind speed and the AEP of a virtual wind turbine for two sites in complex terrain were performed by changing the wind direction from $-45^{\circ}$ to $45^{\circ}$with an interval of $5^{\circ}$. A commercial wind resource prediction program, WindPRO, was used for the study. It was found that the prediction errors in the AEP caused by the wind direction errors occurred up to more than 20% depending on the orography and the main wind direction at that site.

• Atmosphere
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• v.26 no.4
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• pp.617-633
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• 2016

Jangbogo station is located in Terra Nova Bay over the East Antarctica, which is often affected by individual storms moving along nearby storm tracks and a katabatic flow from the continental interior towards the coast. A numerical simulation for two strong wind events of maximum instantaneous wind speed ($41.17m\;s^{-1}$) and daily mean wind speed ($23.92m\;s^{-1}$) at Jangbogo station are conducted using the polar-optimized version of Weather Research and Forecasting model (Polar WRF). Verifying model results from 3 km grid resolution simulation against AWS observation at Jangbogo station, the case of maximum instantaneous wind speed is relatively simulated well with high skill in wind with a bias of $-3.3m\;s^{-1}$ and standard deviation of $5.4m\;s^{-1}$. The case of maximum daily mean wind speed showed comparatively lower accuracy for the simulation of wind speed with a bias of -7.0 m/s and standard deviation of $8.6m\;s^{-1}$. From the analysis, it is revealed that the each case has different origins for strong wind. The highest maximum instantaneous wind case is caused by the approach of the strong synoptic low pressure system moving toward Terra Nova Bay from North and the other daily wind maximum speed case is mainly caused by the katabatic flow from the interiors of Terra Nova Bay towards the coast. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation and investigation of high wind events at Jangbogo station. However, additional efforts in utilizing the high resolution terrain is required to reduce the simulation error of high wind mainly caused by katabatic flow, which is received a lot of influence of the surrounding terrain.

• Wind and Structures
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• v.33 no.6
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• pp.447-462
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• 2021

High spatial and temporal surface pressure measurements were carried out in the state-of-the-art tornado simulator, the Wind Engineering, Energy and Environment (WindEEE) Dome, to explore the characteristics of stationary and translating tornado-like vortices (TLV) for a wide range of swirl ratios (S=0.21 to 1.03). The translational speed of the TLV and the surface roughness were varied to examine their effects on tornado ground pressures, wandering, and vortex structure. It was found that wandering is more pronounced at low swirl ratios and has a substantial effect on the peak pressure magnitude for stationary TLV (error percentage ≤ 35%). A new method for removing wandering was proposed which is applicable for a wide range of swirl ratios. For translating TLV, the near-surface part lagged behind the top of the vortex, resulting in a tilt of the tornado vertical axis at higher translating speeds. Also, a veering motion of the tornado base towards the left of the direction of the translation was observed. Wandering was less pronounced for higher translation speeds. Increasing the surface roughness caused an analogous effect as lowering the swirl ratio.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.105-110
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• 2020

This study provides a method and data for predicting the flight initiation wind speed of wind-borne debris. From the force equilibrium acting on debris including aerodynamic and inertia forces, the equation for predicting the flight initiation wind speeds are presented. Wind tunnel tests were carried out to provide necessary aerodynamic data in the equation for the debris with various aspect ratios. The proposed equation for flight initiation wind speeds was validated from free flying tests in the wind tunnel. The flights of debris were mostly initiated by slip when width to thickness was less than 10, otherwise overturning were dominant. The actual flight initiation speeds were lower than that of the computed ones. The surface boundary layer flow and the gap between the debris and surface might affect the prediction error.

• Journal of Wind Energy
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• v.4 no.2
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• pp.17-24
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• 2013

Idealized PID-controlled rotor-speed error for blade pitch control of wind turbines responds as a second-order system with natural frequency and damping ratio for closed-loop system. RISO National Laboratory has recommended specific natural frequency(=0.6 rad/s) and damping ratio(=0.7) for 2 MW wind turbine. The baseline controller for 5 MW wind turbine of NREL(National Renewable Energy Laboratory) is designed based on the same values of RISO recommendation. This study investigates the effect of the natural frequency and damping ratio of the controller for NREL 5 MW wind turbine. It is confirmed that RISO recommendation shall be tuned for each wind turbine.

• Wind and Structures
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• v.36 no.6
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• pp.423-434
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• 2023

Aerodynamic force coefficients are generally obtained from traditional wind tunnel tests or computational fluid dynamics (CFD). Unfortunately, the techniques mentioned above can sometimes be cumbersome because of the cost involved, such as the computational cost and the use of heavy equipment, to name only two examples. This study proposed to build a deep neural network model to predict the aerodynamic force coefficients based on data collected from CFD simulations to overcome these drawbacks. Therefore, a series of CFD simulations were conducted using different geometric parameters to obtain the aerodynamic force coefficients, validated with wind tunnel tests. The results obtained from CFD simulations were used to create a dataset to train a multilayer perceptron artificial neural network (ANN) model. The models were obtained using three optimization algorithms: scaled conjugate gradient (SCG), Bayesian regularization (BR), and Levenberg-Marquardt algorithms (LM). Furthermore, the performance of each neural network was verified using two performance metrics, including the mean square error and the R-squared coefficient of determination. Finally, the ANN model proved to be highly accurate in predicting the force coefficients of similar bridge sections, thus circumventing the computational burden associated with CFD simulation and the cost of traditional wind tunnel tests.

• Journal of Environmental Science International
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• v.8 no.3
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• pp.309-318
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• 1999

In order to fast predict the wind-driven current in a small bay, a convolution method in which the wind-driven current can be generated only wih the local wind is developed and applied in the Sachon Bay. The root mean square(rms) ratio defined as the ratio of the rms error to the rms speed is 0.37. The rms ratio is generally less than 0.2, except for all the mouths of Junju Bay and Namhae-do and in the region between Saryang Island and Sachon. The spatial average of the recover rate of kinetic energy(rrke) is 87%. Thus, the predicted wind-driven current by the convolution model is in a good agreement with the computed one by the numerical model. The raio of the difference between observed residual current (Vr) and predicted wind-driven current (Vc) to a residual current, that is, (Vr-Vc)/Vr shows 56%, 62% at 2 moorings in the Sachon Bay.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.278-281
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• 2008

In these days the installation of wind turbines or wind parks includes a high financial risk. So for the planning and the constructing of wind farms, long-term data of wind speed and wind direction is required. However, in most cases only few data are available at the designated places. Traditional Measure-Correlate-Predict (MCP) can extend this data by using data of nearby meteorological stations. But also Neural Networks can create such long-term predictions. The key issue of this paper is to demonstrate the possibility and the quality of predictions using Neural Networks. Thereto this paper compares the results of different MCP Models and Neural Networks for creating long-term data with various indexes.

• Atmosphere
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• v.24 no.3
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• pp.419-432
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• 2014

An assessment of typhoon intensity predictability of numerical models was conducted to develop the typhoon intensity forecast guidance comparing with the RSMC-Tokyo best track data. Root mean square error, box plot analysis and time series of wind speed comparison were performed to evaluate the each model error level. One of noticeable fact is that all models have a trend of error increase as typhoon becomes stronger and the Global Forecast System showed the best performance among the models. In the detailed analysis in two typhoon cases [Danas (1324) and Haiyan (1330)], GFS showed good performance in maximum wind speed and intensity trend in the best track, however it could not simulate well the rapid intensity increasing period. On the other hand, ECMWF and Hurricane-WRF overestimated the typhoon intensity but simulated track trend well.