• Journal of Korean Society for Atmospheric Environment
• /
• v.14 no.3
• /
• pp.219-228
• /
• 1998

In the present investigation, a numerical model developed for the prediction of the wind flow over complex terrain is validated by comparing with the field experiments. For the solution of the Reynolds - Averaged Clavier- stokes equations which are the governing equations of the microscale atmospheric flow, the model is constructed based on the finite-volume formulation and the SIMPLEC pressure-correction algorithm for the hydrodynamic computation. The boundary- fitted coordinate system is employed for the detailed depiction of topography. The boundary conditions and the modified turbulence constants suitable for an atmospheric boundary- layer are applied together with the k- s turbulence model. The full- scale experiments of Cooper's Ridge, Kettles Hill and Askervein Hill are chosen as the validation cases . Comparisons of the mean flow field between the field measurements and the predicted results show good agreement. In the simulation of the wind flow over Askervein Hill , the numerical model predicts the three dimensional flow separation in the downslope of the hill including the blockage effect due to neighboring hills . Such a flow behavior has not been simulated by the theoretical predictions. Therefore, the present model may offer the most accurate prediction of flow behavior in the leeside of the hill among the existing theoretical and numerical predictions.

• Atmosphere
• /
• v.31 no.1
• /
• pp.85-100
• /
• 2021

The necessity of accurate high-resolution meteorological forecasts becomes increasing in socio-economical applications and disaster risk management. The Korea Meteorological Administration Post-Processing (KMAPP) system has been operated to provide high-resolution meteorological forecasts of 100 m over the South Korea region. This study evaluates and improves the KMAPP performance in simulating wind speeds over complex terrain areas using the ICE-POP 2018 field campaign measurements. The mountainous measurements give a unique opportunity to evaluate the operational wind speed forecasts over the complex terrain area. The one-month wintertime forecasts revealed that the operational Local Data Assimilation and Prediction System (LDAPS) has systematic errors over the complex mountainous area, especially in deep valley areas, due to the orographic smoothing effect. The KMAPP reproduced the orographic height variation over the complex terrain area but failed to reduce the wind speed forecast errors of the LDAPS model. It even showed unreasonable values (~0.1 m s-1) for deep valley sites due to topographic overcorrection. The model's static parameters have been revised and applied to the KMAPP-Wind system, developed newly in this study, to represent the local topographic characteristics better over the region. Besides, sensitivity tests were conducted to investigate the effects of the model's physical correction methods. The KMAPP-Wind system showed better performance in predicting near-surface wind speed during the ICE-POP period than the original KMAPP version, reducing the forecast error by 21.2%. It suggests that a realistic representation of the topographic parameters is a prerequisite for the physical downscaling of near-ground wind speed over complex terrain areas.

• Journal of Power Electronics
• /
• v.9 no.1
• /
• pp.85-92
• /
• 2009

This paper studies the method to predict voltage variation that can be presented in the case of operating a small-sized wind turbine in grid connection to the isolated small-sized power system. In order to do this, it makes up the simplified simulation model of the existing power plant connected to the isolated system, load, transformer, and wind turbine on the basis of PSCAD/EMTDC and compares them with the operating characteristics of the actual established wind turbine. In particular, it suggests a simplified model formed with equivalent impedance of the power system network including the load to analytically predict voltage variation at the connected point. It also confirms that the voltage variation amount calculated by the suggested method accords well with both simulation and actually measured data. The results can be utilized as a tool to ensure security and reliability in the stage of system design and preliminary investigation of a small-sized grid connected wind turbine.

• International Journal of Advanced Culture Technology
• /
• v.6 no.4
• /
• pp.190-194
• /
• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• Wind and Structures
• /
• v.5 no.2_3_4
• /
• pp.337-346
• /
• 2002

Wind tunnel pressure measurements and numerical simulations based on the Reynolds Stress Model (RSM) are compared with full and model scale data in the flow area of impingement, separation and wake for $60^{\circ}$ and $90^{\circ}$ wind azimuth angles. The phase averaged fluctuating pressures simulated by the RSM model are combined with modelling of the small scale, random pressure field to produce the total, instantaneous pressures. Time averaged, rsm and peak pressure coefficients are consequently calculated. This numerical approach predicts slightly better the pressure field on the roof of the TTU (Texas Tech University) building when compared to the wind tunnel experimental results. However, it shows a deviation from both experimental data sets in the impingement and wake regions. The limitations of the RSM model in resolving the intermittent flow field associated with the corner vortex formation are discussed. Also, correlations between the largest roof suctions and the corner vortex "switching phenomena" are observed. It is inferred that the intermittency and short duration of this vortex switching might be related to both the wind tunnel and numerical simulation under-prediction of the peak roof suctions for oblique wind directions.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_3
• /
• pp.1643-1652
• /
• 2020

To investigate the characteristics of detailed flows in a building-congested district, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. For realistic numerical simulations, we used the meteorological variables such as wind speeds and directions and potential temperatures predicted by LDAPS as the initial and boundary conditions of the CFD model. We trilinearly interpolated the horizontal wind components of LDAPS to provide the initial and boudnary wind velocities to the CFD model. The trilinearly interpolated potential temperatures of LDAPS is converted to temperatures at each grid point of the CFD model. We linearly interpolated the horizontal wind components of LDAPS to provide the initial and boundary wind velocities to the CFD model. The linearly interpolated potential temperatures of LDAPS are converted to temperatures at each grid point of the CFD model. We validated the simulated wind speeds and directions against those measured at the PKNU-SONIC station. The LDAPS-CFD model reproduced similar wind directions and wind speeds measured at the PKNU-SONIC station. At 07 LST on 22 June 2020, the inflow was east-north-easterly. Flow distortion by buildings resulted in the east-south-easterly at the PKNU-SONIC station, which was the similar wind direction to the measured one. At 19 LST when the inflow was southeasterly, the LDAPS-CFD model simulated southeasterly (similar to the measured wind direction) at the PKNU-SONIC station.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.20 no.1
• /
• pp.93-100
• /
• 2008

A multi-nesting grid storm surge model, Korea Ocean Research and Development Institute-Storm surge model, was calibrated to simulate storm surges. To check the performance of this storm surge model, a series of numerical experiments were explored including tidal calibration, the influence of the open boundary condition, the grid resolutions, and typhoon paths on the surge heights using the typhoon Maemi, which caused a severe coastal disasters in Sep. 2003. In this study the meteorological input data such as atmospheric pressure and wind fields were calculated using CE wind model. Total 11 tidal gauge station records with 1-minute interval data were compared with the model results and the storm surge heights were successfully simulated. The numerical experiments emphasized the importance of meteorological input and fine-mesh grid systems on the precise storm surge prediction. This storm surge model could be used as an operational storm surge prediction system after more intensive verification.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.2
• /
• pp.689-700
• /
• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• Structural Engineering and Mechanics
• /
• v.10 no.6
• /
• pp.545-559
• /
• 2000

A Wind and Structural Health Monitoring System (WASHMS) has been installed in the Tsing Ma suspension Bridge in Hong Kong with one of the objectives being the verification of analytical processes used in wind-resistant design. On 2 August 1997, Typhoon Victor just crossed over the Bridge and the WASHMS timely recorded both wind and structural response. The measurement data are analysed in this paper to obtain the mean wind speed, mean wind direction, mean wind inclination, turbulence intensity, integral scale, gust factor, wind spectrum, and the acceleration response and natural frequency of the Bridge. It is found that some features of wind structure and bridge response are difficult to be considered in the currently used analytical process for predicting buffeting response of long suspension bridges, for the Bridge is surrounded by a complex topography and the wind direction of Typhoon Victor changes during its crossing. It seems to be necessary to improve the prediction model so that a reasonable comparison can be performed between the measurement and prediction for long suspension bridges in typhoon prone regions.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.142-145
• /
• 2006

The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the NOAA HWind wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.