• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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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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• 2009.06a
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• pp.557-560
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• 2009

When we urgently need to develop and supply an alternative energy, wind power is growing with much interest because it has relative low cost of power and area of tower. To estimate the wind power resource, it is necessary to make an observation first. Although the large wind falm and resources are near coast and mountain area, the wind energy in urban area has the strong thing of direct access to power generator. In this study, we estimate the probability of wind energy above urban area using SODAR data, which is located at the top of the tall building (140m).

• Journal of Environmental Science International
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• v.18 no.8
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• pp.919-926
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• 2009

Renewable energy or green energy is a hot issue in theses days. Since wind resource can be endlessly supplied by nature, researchers and common people are interested in study how to use that resource at home or company. Especially, many architects have tried to integrate wind power generator for a part of building. So in this paper, three buildings installed wind power turbine are targed to CFD analysis and these buildings are Bahrain trade center, Discovery tower, and Pearl river tower. Bahrain trade center is the first building installed real wind turbine, Discovery tower is constructing at Texas, and Pearl river tower is designed and proved by china researchers. These buildings have very different type of wind power turbine and each turbine has different conditions f3r best power generation. Therefor this paper will focus on characteristic shape of buildings, wind power turbine type, and expected purpose of construction. Moreover, CFD analysis will show wind flow pattern and wind speed while wind is passing through wind turbine of three tall buildings. CFD analysis for three buildings make comparison the wind flow patterns with experimental result.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.418-421
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• 2009

Renewable energy or green energy is a hot issue in theses days. Since wind resource can be endlessly supplied by nature, researchers and common people are interested in study how to use that resource at home or company. Especially, many architects have tried to integrate wind power generator for a part of building. So in this paper, three buildings installed wind power turbine are targed to CFD analysis and these buildings are Bahrain trade center, Discovery tower, and Pearl river tower. Bahrain trade center is the first builidng installed real wind turbine, Discovery tower is constructing at Texas, and Pearl river tower is designed and proved by china researchers. These buildings have very different type of wind power turbine and each turbine has different conditions for best power generation. Therefor this paper will focus on characteristic shape of buildings, wind power turbine type, and expected purpose of construction. Moreover, CFD analysis will show wind flow pattern and wind speed while wind is passing through wind turbine of three tall buildings. CFD analysis for three buildings make comparison the wind flow patterns with experimental result.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.318-321
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• 2008

We classified wind sectors according to the wind features in South Korea. In order to get the information of wind speed and wind direction, we used and improved on the atmospheric numerical model. We made use of detailed topographical data such as terrain height data of an interval of 3 seconds and landuse data produced at ministry of environment, Republic of Korea. The result of simulated wind field was improved. We carried out the cluster analysis to classify the wind sectors using the K-means clustering. South Korea was classified as 10 wind sectors which have a clear wind features.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.3-8
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• 2009

Environmental pollution caused by fossil fuel use and energy sources, the big concern is the rise of the current situation, one of the ways to overcome the interest in renewable energy is Gozo. Located on the west coast, especially the Saemangeum area and the northwest wind, the big advantage of the vast area that's got quite a number of wind turbines is expected. This study affirms that these expectations can be a wind energy resource survey sea area of the average wind speed of Kunsan 5 ~ 7m / s is enough, books are linked to the local marine wind farms can safely say that none of choejeokji said. In addition, the emergence of the wind resource to determine the density of the Weibull distribution is calculated using the number 1, the shape factor as a parameter to calculate the density of the wind a result, Gunsan Province was able to predict the emergence of the wind. In addition, by controlling the remote monitoring through the measurement exceeded the convenience and reliability at the same time you can achieve great results.

• Journal of Power System Engineering
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• v.19 no.4
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• pp.76-81
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• 2015

The production of electricity from wind energy is noticed as economic power generation system in the natural resource. Lately, since lots of wind turbine have installed globally, the accidents have increased gradually. In this paper, we classified domestic information for 10 years, information of new energy and industrial technology development organization(NEDO) for 4years and caithness windfarms information forum(CWIF) for 15 years according to part and cause of wind turbine accident. We found that the main causes of accidents are storm, lightening and carelessness. The results of classifying and analyzing the informations, should be used to take measures on the accident prevention of wind turbine.

• New & Renewable Energy
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• v.7 no.3
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• pp.83-91
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• 2011

The purpose of this study is to select appropriate location factors for wind power plant, provide detailed classification criteria, and find out appropriate sites for installing wind power plant in Gangwondo. In this study, the following 11 factors were extracted for site selection of wind power plant : wind resource, topography (valley angle, distance to the ridge), forest density, land use, preservation area, national park, Baekdu-Daegan, noise, shade, Transmission Line, and approaching roads. Each factor had relatively different level of importance so that AHP (Analytic Hierarchy Process) technique was used to calculated the weighted value per factor. For overlay analysis, classification criteria were prepared for each factor and each factor was classified into 3 grades : very appropriate, intermediate, poor. According to overlay analysis, the areas which received the highest grade (grade 5) was only in 0.16% of the total area of Gangwondo and had a tendency to exist along the mountain ridge over 600-meter elevation. Through analyzing the yearly average of wind power density, it was proved that the wind power density of areas with grade 4 or 5 had abundant wind resource over $400W/m^2$.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.463-466
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• 2009

The numerical simulation optimized by Four Dimensional Data Assimilation (FDDA) with Quick Scatterometer (QuikSCAT) data is carried out to evaluate wind resource characteristics at various heights in the southeastern area of the Korean Peninsula, where wind farms are planned to be built on on- and off-shore as well as comparable diurnal wind variations are characterized at the surface. The temporal and spatial distributions of modeled wind speeds showed good agreement with the observations based on the temporal variation analysis. Model results indicate that the higher model is performed in resolution, the more precise results is at turbine hub height. Occasionally, wind speed variations for each numerical resolution has a different regional and seasonal variations. In the coast area, hub height wind speed of 9km-resolution is simillar to that of 3km-resolution. On the other hand, hub height wind speed of 3km-resolution is simillar to that of 1km-resolution in the Jiri mountainous area.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.79-85
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• 2010

The uncertainty in WindCube LIDAR measurements, which are specific to wind profiling at less than 200m above ground levelin wind resource assessments, was analyzed focusing on the error caused by its volume sampling principle. A two-month SODAR measurement campaign conducted in an urban environment was adopted as the reference wind profile assuming that various atmospheric boundary layer shapes had been captured. The measurement error of LIDAR at a height z was defined as the difference in the wind speeds between the SODAR reference data, which was assumed to be a virtually true value, and the numerically averaged wind speed for a sampling volume height interval of $z{\pm}12.5m$. The pattern of uncertainty in the measurement was found to have a maximum in the lower part of the atmospheric boundary layer and decreased with increasing height. It was also found that the relative standard deviations of the wind speed error ratios were 6.98, 2.70 and 1.12% at the heights of 50, 100 and 150m above ground level, respectively.