• New & Renewable Energy
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• v.7 no.2
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• pp.43-50
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• 2011

The only practical way to measure wind resource at high-altitude over 100 m above ground for a feasibility study on a high-rise building integrated wind turbine might be ground-based remote sensing. The remote-sensing campaign was performed at a 145 m-building roof in Jamsil where is a center of metropolitan city Seoul. The campaign aimed uncertainty assessment of Leosphere WindCube LIDAR and Scintec MPAS SODAR through a mutual comparison. Compared with LIDAR, the data availability of SODAR was about 2/3 at 550 m altitude while both showed over 90% under 400 m, and it is shown that the data availability decrease may bring a distortion of statistical analysis. The wind speed measurement of SODAR was fitted to a slope of 0.92 and $R^2$ of 0.90 to the LIDAR measurement. The relative standard deviation of wind speed difference and standard deviation of wind direction difference were evaluated to be 30% and 20 degrees, respectively over the whole measurement heights.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.1-16
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• 2008

Steam and advection fogs are frequently observed in the Yellow Sea from March to July except for May. This study uses remote sensing (RS) data for the monitoring of sea fog. Meteorological data obtained from the Ieodo Ocean Research Station provided a valuable information for the occurrence of steam and advection fogs as a ground truth. The RS data used in this study were GOES-9, MTSAT-1R images and QuikSCAT wind data. A dual channel difference (DCD) approach using IR and shortwave IR channel of GOES-9 and MTSAT-1R satellites was applied to detect sea fog. The results showed that DCD, texture-related measurement and the weak wind condition are required to separate the sea fog from the low cloud. The QuikSCAT wind data was used to provide the wind speed criteria for a fog event. The laplacian computation was designed for a measurement of the homogeneity. A new combined method, which includes DCD, QuikSCAT wind speed and laplacian computation, was applied to the twelve cases with GOES-9 and MTSAT-1R. The threshold values for DCD, QuikSCAT wind speed and laplacian are -2.0 K, $8m\;s^{-1}$ and 0.1, respectively. The validation results showed that the new combined method slightly improves the detection of sea fog compared to DCD method: improvements of the new combined method are $5{\sim}6%$ increases in the Heidke skill score, 10% decreases in the probability of false detection, and $30{\sim}40%$ increases in the odd ratio.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.2
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• pp.124-130
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• 2005

This paper presents the simulation modeling and analysis of variable wind speed turbine system(VWTS) using Psim program In the simulation, using the Vestas V47 VWTS located in Hangwon wind farm in Jeju-Do as a model, wind model, blade model, pitch control model and grided connected generator are modeled. The VWTS is controlled by the optimal pitch angle for maximum output power under the rated wind speed and for the rated output power over the rated wind speed. To verify the effectiveness of proposed method, simulation results are compared with the actual data from the model system According to the comparison of these results, this method shows excellent performance. So it is very useful for understanding and applications of wind power control system.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.4
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• pp.153-178
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• 2018

Most operational uses of wind speed data require measurements at, or estimates generated for, the reference height of 10 m above mean sea level (AMSL). On the Ieodo Ocean Research Station (IORS), wind speed is measured by instruments installed on the lighthouse tower of the roof deck at 42.3 m AMSL. This preliminary study indicates how these data can best be converted into synthetic 10 m wind speed data for operational uses via the Korea Hydrographic and Oceanographic Agency (KHOA) website. We tested three well-known conventional empirical neutral wind profile formulas (a power law (PL); a drag coefficient based logarithmic law (DCLL); and a roughness height based logarithmic law (RHLL)), and compared their results to those generated using a well-known, highly tested and validated logarithmic model (LMS) with a stability function (${\psi}_{\nu}$), to assess the potential use of each method for accurately synthesizing reference level wind speeds. From these experiments, we conclude that the reliable LMS technique and the RHLL technique are both useful for generating reference wind speed data from IORS observations, since these methods produced very similar results: comparisons between the RHLL and the LMS results showed relatively small bias values ($-0.001m\;s^{-1}$) and Root Mean Square Deviations (RMSD, $0.122m\;s^{-1}$). We also compared the synthetic wind speed data generated using each of the four neutral wind profile formulas under examination with Advanced SCATterometer (ASCAT) data. Comparisons revealed that the 'LMS without ${\psi}_{\nu}^{\prime}$ produced the best results, with only $0.191m\;s^{-1}$ of bias and $1.111m\;s^{-1}$ of RMSD. As well as comparing these four different approaches, we also explored potential refinements that could be applied within or through each approach. Firstly, we tested the effect of tidal variations in sea level height on wind speed calculations, through comparison of results generated with and without the adjustment of sea level heights for tidal effects. Tidal adjustment of the sea levels used in reference wind speed calculations resulted in remarkably small bias (<$0.0001m\;s^{-1}$) and RMSD (<$0.012m\;s^{-1}$) values when compared to calculations performed without adjustment, indicating that this tidal effect can be ignored for the purposes of IORS reference wind speed estimates. We also estimated surface roughness heights ($z_0$) based on RHLL and LMS calculations in order to explore the best parameterization of this factor, with results leading to our recommendation of a new $z_0$ parameterization derived from observed wind speed data. Lastly, we suggest the necessity of including a suitable, experimentally derived, surface drag coefficient and $z_0$ formulas within conventional wind profile formulas for situations characterized by strong wind (${\geq}33m\;s^{-1}$) conditions, since without this inclusion the wind adjustment approaches used in this study are only optimal for wind speeds ${\leq}25m\;s^{-1}$.

• Transactions of the Korean hydrogen and new energy society
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• v.30 no.6
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• pp.608-613
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• 2019

The purpose of the present study is to analyze and evaluate the performance of a small Darrieus wind turbine installed at the Urumsil region of Deokjeok-do Island in the west of South Korea 50 km away from Incheon. This place has no government electricity so alternate resources of energy needed to be installed there. For this purpose a small Darrieus wind turbine with the capacity of 1.5 kW was developed and installed at the site. The experimental power output of the wind turbine is less than the designed power at the same values of wind speed. This power loss is mainly due to the highly unsteady nature wind of sudden changes in magnitude of wind speed and wind angle. The results of current study can be used to make a future power generation plan for Deokjeok-do and other nearby small islands.

• Journal of the Korean Solar Energy Society
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• v.27 no.4
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• pp.1-9
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• 2007

Sensitivity analysis of wind resource micrositing has been performed through the application case at the Antarctic King Sejong station with the most representative micrositing softwares: WAsP, WindSim and Meteodyn WT. The wind data obtained from two met-masts separated 625m were applied as a climatology input condition of micro-scale wind mapping. A tower shading effect on the met-mast installed 20m apart from the warehouse has been assessed by the CFD software Fluent and confirmed a negligible influence on wind speed measurement. Theoretically, micro-scale wind maps generated by the two met-data located within the same wind system and strongly correlated meteor-statistically should be identical if nothing influenced on wind prediction but orography. They, however, show discrepancies due to nonlinear effects induced by surrounding complex terrain. From the comparison of sensitivity analysis, Meteodyn WT employing 1-equation turbulence model showed 68% higher RMSE error of wind speed prediction than that of WindSim using the ${\kappa}-{\epsilon}$ turbulence model, while a linear-theoretical model WAsP showed 21% higher error. Consequently, the CFD model WindSim would predict wind field over complex terrain more reliable and less sensitive to climatology input data than other micrositing models. The auto-validation method proposed in this paper and the evaluation result of the micrositing softwares would be anticipated a good reference of wind resource assessments in complex terrain.

• Journal of Environmental Science International
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• v.21 no.2
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• pp.145-152
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• 2012

The mean wind speed and turbulence intensity profiles in the atmospheric boundary layer were extracted from a LIDAR remote sensing campaign in order to apply for CFD validation. After considering the semi-steady state field data requirements to be used for CFD validation, a neutral atmosphere campaign period, in which the main wind direction and the power-law exponent of the wind profile were constantly maintained, was chosen. The campaign site at the Pohang Accelerator Laboratory, surrounded by 40~50m high hills, with an apartment district spread beyond the hills, is to be classified as a semi-complex terrain. Nevertheless, wind speed profiles measured up to 100m above the ground fitted well into a theoretical-experimental logarithmic-law equation. The LIDAR remote-sensing data of the sub-layer of the atmospheric boundary layer has been proven to be superior to the data obtained by conventional extrapolation of the wind profile with 2 or 3 anemometer measurements.

• Journal of Electrical Engineering and Technology
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• v.6 no.3
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• pp.375-383
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• 2011

This paper describes a real-time hardware simulator for a grid-tied Permanent Magnet Synchronous Generator (PMSG) wind power system, which consists of an anemometer, a data logger, a motor-generator set with vector drive, and a back-to-back power converter with a digital signal processor (DSP) controller. The anemometer measures real wind speed, and the data is sent to the data logger to calculate the turbine torque. The calculated torque is sent to the vector drive for the induction motor after it is scaled down to the rated simulator power. The motor generates the mechanical power for the PMSG, and the generated electrical power is connected to the grid through a back-to-back converter. The generator-side converter in a back-to-back converter operates in current control mode to track the maximum power point at the given wind speed. The grid-side converter operates to control the direct current link voltage and to correct the power factor. The developed simulator can be used to analyze various mechanical and electrical characteristics of a grid-tied PMSG wind power system. It can also be utilized to educate students or engineers on the operation of grid-tied PMSG wind power system.

• Ocean and Polar Research
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• v.30 no.1
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• pp.47-58
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• 2008

Several validation studies have been made for QuikSCAT(QSCAT) wind data around the world, mainly in the offshore. However, until now, there were no validation studies for QSCAT wind with resolution of 12.5 km ('QSCAT 12.5 km wind') in the vicinity of Korean Peninsula. To validate 'QSCAT 12.5 km wind' and to investigate its characteristics around Korean Peninsula, the wind data from Ieodo Ocean Research Station, KMA buoys, and KORDI Realtime Observation Stations have been compared. Validation results showed that 'QSCAT 12.5 km wind' RMSE of wind direction and speed were $25.85^{\circ}$ and 1.83 m/s, respectively, at Ieodo Station. The mean wind speed correlation coefficient of KMA buoys and KORDI Realtime Observation Station were 0.78 and 0.61, and the mean wind speed RMSE were 2.2 m/s and 3.2 m/s, respectively. This seems to be mainly because of the distance between QSCAT and in-situ observation stations. The RMSE of wind direction were bigger than $40^{\circ}$ at all in-situ observation stations located near the shore, within 20 km from coastlines. Geophysical features where in-situ observation stations are located seem to affect wind validation scores.

• Journal of Environmental Science International
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• v.20 no.9
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• pp.1191-1203
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• 2011

In case of Typhoon Dianmu, the temperature, wind speed, wind direction and the rainfall per hour changed dramatically when the center of the typhoon passed through Gimhae. Such a change was commonly found in the regions where the center of the typhoon passed through but almost not in the regions far away from it. For example, in the case of Typhoon Malou where the center of the typhoon was far away from the observation site, such a phenomenon was not observed. The analysis of the vertical observation data showed that there was a little change in the wind speed and wind direction in the vertical direction in the case of Typhoon Dianmu of which center passed through Gimhae. There was a great change in the wind speed according to the height in the lower atmosphere just before the center of the typhoon approached the region. When the center of the typhoon was passing through the region, the vertical wind speed was decreased. However, the wind speed was rapidly increased again after the center of the typhoon had passed through the region. Unlike the Dianmu, the difference in the wind speed and wind direction between the upper layer and lower layer of the atmosphere was relatively great in the case of Malou.