• Journal of the Korean earth science society
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• 제34권7호
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• pp.633-644
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• 2013

This study evaluates wind farm efficiency at Haengwon in Jeju Island. The actual energy production at Haengwon wind farm is compared with the estimated energy production based on Korean wind map which is developed at the National Institute of Meteorological Research/KMA. The validation of wind map at Gujwa located near the Haengwon wind farm shows that the wind speed is overestimated. The diurnal variation of wind speed shows a maximum value in the afternoon due to the effect of sea-land breeze. The ratio of the actual energy production at Haengwon wind farm and the estimated energy production based on the Korean wind map is 24.8%, while the distribution of energy frequency is similar each other. The difference of energy production is caused by mechanical error of the turbine and the overestimation of the simulated wind map. This study will contribute to the repowering of turbines for improving the efficiency of wind farm in the future.

• New & Renewable Energy
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• 제1권1호
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• pp.44-53
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• 2005

To understand general status of the national wind environment and to distinguish potential areas to be developed as a largescale wind farm, a synoptic wind map of the Korean Peninsula is established by processing remote sensing data of the satellite, NASA QuikSCAT which Is deployed for the SeaWinds Project since 1999. According to the validation results obtained by comparing with the measurement data of marine buoys of KMA(Korea Meteorological Administration), the cross-correlation factor Is greatly Improved up to 0.87 by blending the sea-surface dat3 of QuikSCAT with NCEP/NCAR CDAS data. It is found from the established synoptic wind map that the wind speed in winter is prominent temporally and the South Sea shows high energy density up to the wind class 6 spatially. The reason is deduced that the northwest winds through the yellow Sea and the northeast winds through the East Sea derived by the low-pressure developed in Japan are accelerated passing through the Korea Channel and formed high wind energy region in the South Sea; the same trends are confirmed by the statistical analysis of meteorological observation data of KMA.

• Journal of Environmental Science International
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• 제22권6호
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• pp.717-721
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• 2013

In order to analyze the effect of environmental protection on wind energy dissemination quantitatively, the onshore wind resource potential is estimated using Environmental Conservation Value Assessment Map and Korea Wind Resource Map. The onshore wind resource potential of 11 GW is calculated if wind farm development is prohibited within Class 1 area of Environmental Conservation Value Assessment plus 500 m buffer area. Therefore it is worried that environmental protection would be a practical barrier of accomplishing 4,155 thousand TOE target of wind energy dissemination until 2030.

• Journal of Environmental Science International
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• 제22권10호
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• pp.1305-1316
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• 2013

A long-term wind resource map was made to provide the key design data for the 2.5 GW Korean West-South Offshore Wind Project, and its reliability was validated. A one-way dynamic downscaling of the MERRA reanalysis meteorological data of the Yeongwang-Gochang offshore was carried out using WindSim, a Computational Fluid Dynamics based wind resource mapping software, to establish a 33-year time series wind resource map of 100 m x 100 m spatial resolution and 1-hour interval temporal resolution from 1979 to 2012. The simulated wind resource map was validated by comparison with wind measurement data from the HeMOSU offshore meteorological tower, the Wangdeungdo Island meteorological tower, and the Gochang transmission tower on the nearby coastline, and the uncertainty due to long-term variability was analyzed. The long-term variability of the wind power was investigated in inter-annual, monthly, and daily units while the short-term variability was examined as the pattern of the coefficient of variation in hourly units. The results showed that the inter-annual variability had a maximum wind index variance of 22.3% while the short-term variability, i.e., the annual standard deviation of the hourly average wind power, was $0.041{\pm}0.001$, indicating steady variability.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2009년도 춘계학술대회 논문집
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• pp.529-531
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• 2009

To construct the wind map for mainland Korea, the well designed atmospheric numerical modeling system was used. Three nest domains were construced with spatial resolutions between $10{\times}10km$ up to the hightest resolution of $1{\times}1km$. Parameterization schemes like MRF(PBL), RRTM(radiation), Grell(cumulus) were chosen since wind data simulated is in better agreement with the observed wind data. High-resolution atmospheric numerical model was applied to simulate the motion of the atmosphere and to produce the wind map around the South Korea. The results of several simulations were improved compare to the past system, because of using the fine geographical data, such as terrain height and land-use data, and the meteorological data assimilation.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 추계학술대회 논문집
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• pp.332-333
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• 2008

This paper presents an estimation method of national wind resource potential using a national and GIS(Geographical Information System). The wind resource potential is classified into theoretical, geographical and technical potentials and each category narrows down the previous definition by excluding impossible area to be developed as a wind farm using GIS datasets for onshore and offshore. As a basic unit of wind energy potential at a certain area, API(Average Power Intercepted) is calculated from WPD(Wind Power Density) given by a national wind map which is established by numerical wind simulation, so that a logical and relatively accurate potential estimation is possible comparing with other methods based on a field measurement interpolation which is inevitable to avoid critical assumptions.

• Journal of Korean Society for Geospatial Information Science
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• 제23권1호
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• pp.15-22
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• 2015

To create a wind resource map, we need a contour map, a roughness map and wind data. We need a land cover map for the roughness map of these data. A land cover map represents the area showing similar characteristics after color indexing based on the scientific method. The features of land cover is classified by Remote sensing technique. In this study, we verified the application of the NDVI technique is reasonable after we created the wind resource map using roughness maps by unsupervised classification and NDVI technique. As a result, the wind resource map using the NDVI technique showed a 60% accordance rate and difference in class less than one. From the results, The NDVI technique is found alternative to create roughness maps by the unsupervised classification.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 춘계학술대회 논문집
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• pp.300-302
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• 2008

For the evaluation of wind resources, numerical simulation was carried out as a tool for establishing wind map around the korean peninsula. Initial and boundary condition are given by 3 hourly RDAPS(Regional Data Assimilation and Prediction System) data of KMA(Korea Meteorology Administration) and high resolution terrain elevation land cover(30 seconds) data from USGS(United States Geological Survey). Furthermore, Data assimilation was adopted to improve initial meteorological data with buoy and QuikSCAT seawinds data. The simulation was performed from 2003 to 2006 year. To understand wind data correctly in complex terrain as the korean peninsula, at this research, Wind map was classified 4 categories by distance from coastline and elevation.

• The Korean Journal of Applied Statistics
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• 제23권6호
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• pp.1157-1167
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• 2010

This paper details a method for establishing a wind energy map having($1Km{\times}1Km$) resolution. The map is essential for measurement and efficiency-testing of wind energy resources and wind site analysis. To this end, a statistical wind field model is estimated that covers 345,682 regions obtained by $1Km{\times}1Km$ lattices made over South Korea. The paper derives various characteristics of a regional wind energy resource under the statistical wind field model and estimates them to construct the wind energy map. Kolmogorov-Smirnov test, based on TMY(typical meteorological year) wind data of 76 weather station areas, shows that a Log-normal model is adequate for the statistical wind field model. The model is estimated by using the wind speed data of 345,682 regions provided by the National Institute of Meteorological Research(NIMR). Various wind energy statistics are studied under the Log-normal wind field model. As an application, the wind energy density(W$/m^2$) map of South Korea is constructed with a resolution of $1Km{\times}1Km$ and its utility for the wind site analysis is discussed.

• Journal of the Korean Solar Energy Society
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• 제36권4호
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• pp.21-29
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• 2016

Commercial wind farm design tools and the national wind map are used to determine the implementation potential of offshore wind power in Korea in this study. For this, the territorial waters of Korea were divided into nine analysis regions and a commercial CFD code was used to obtain wind resource maps at 100m A.S.L. which is the hub height of a 5MW wind turbine used in this study. With the wind resource obtained, factors including water depth, distance from substations, minimum and maximum capacity of a wind farm, distance between turbines and wind farms were considered to determine wind power potential. Also, the conservation areas, military zones, ports, fishing grounds, etc. were considered and excluded. As the result, a total capacity of 6,720 MW was found to be the implementation potential and this corresponds to $3.38MW/km^2$ in API. Also if the distance from the substation is not considered, the potential increased to be 10,040 MW. This offshore wind farm potential is considered enough to satisfy the target of wind farm capacities in the 7th national plan for electricity demand and supply.