• Title/Summary/Keyword: Wind Speed Data

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Simulation Modeling cnd Analysis of Pitch Controlled Variable Speed Wind Turbine System (피치제어형 가변속 풍력터빈 시스템의 시뮬레이션 모델링과 해석)

  • Kim, Eel-Hwan;Kang, Geong-Bo
    • 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.

A Remote Sensed Data Combined Method for Sea Fog Detection

  • Heo, Ki-Young;Kim, Jae-Hwan;Shim, Jae-Seol;Ha, Kyung-Ja;Suh, Ae-Sook;Oh, Hyun-Mi;Min, Se-Yun
    • 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.

Converting Ieodo Ocean Research Station Wind Speed Observations to Reference Height Data for Real-Time Operational Use (이어도 해양과학기지 풍속 자료의 실시간 운용을 위한 기준 고도 변환 과정)

  • BYUN, DO-SEONG;KIM, HYOWON;LEE, JOOYOUNG;LEE, EUNIL;PARK, KYUNG-AE;WOO, HYE-JIN
    • 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 ${\leq}25m\;s^{-1}$.

Field Testing and Performance Evaluation of 1.5 kW Darrieus Wind Turbine (1.5 kW 다리우스 풍력터빈 현장 실증 및 성능분석)

  • ALI, SAJID;JANG, CHOON-MAN
    • Journal of Hydrogen and New Energy
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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.

Sensitivity Analysis of Wind Resource Micrositing at the Antarctic King Sejong Station (남극 세종기지에서의 풍력자원 국소배치 민감도 분석)

  • Kim, Seok-Woo;Kim, Hyun-Goo
    • 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.

Analysis on Wind Profile Characteristics in a Sublayer of Atmospheric Boundary Layer over a Semi-Complex Terrain - LIDAR Remote Sensing Campaign at Pohang Accelerator Laboratory (준복잡지형 대기경계층 저층 풍속분포 특성분석 - 포항가속기 라이다 원격탐사 캠페인을 중심으로)

  • Kim, Hyun-Goo
    • 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.

Real-Time Hardware Simulator for Grid-Tied PMSG Wind Power System

  • Choy, Young-Do;Han, Byung-Moon;Lee, Jun-Young;Jang, Gil-Soo
    • 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.

A Study on the Observation of the Typhoons that Affected Southeastern Region of the Korean Peninsula (한반도 동남권역에 영향을 미친 태풍 관측 연구)

  • Jung, Woo-Sik;Park, Jong-Kil;Kim, Eun-Byul
    • 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.

Evaluation and Improvement of the KMAPP Surface Wind Speed Prediction over Complex Terrain Areas (복잡 지형 지역에서의 KMAPP 지상 풍속 예측 성능 평가와 개선)

  • Keum, Wang-Ho;Lee, Sang-Hyun;Lee, Doo-Il;Lee, Sang-Sam;Kim, Yeon-Hee
    • Atmosphere
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    • v.31 no.1
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    • pp.85-100
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    • 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.

Validation of QuikSCAT Wind with Resolution of 12.5 km in the Vicinity of Korean Peninsula (한반도 연안에서의 12.5 km 해상도 QuikSCAT 해상풍 검증)

  • Jeong, Jin-Yong;Shim, Jae-Seol;Lee, Dong-Kyu;Min, In-Ki;Kwon, Jae-Il
    • 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.