• Journal of the Korean Solar Energy Society
• /
• v.28 no.6
• /
• pp.24-32
• /
• 2008

This paper discussed the Feasibility study of wind power generation considering the topographical characteristics of Korea. In order to estimate the exact generation of wind power plants, we analyzed and compared wind resources in mountain areas and plain areas by introducing not only wind speed, the most important variable, but also wind distribution and wind standard deviation that can reflect the influence of landform sufficiently. According to the results of this study, generation was almost the same at wind power plants installed in southwestern coastal areas where wind speed was low as at those installed in mountain areas in Gangwondo where wind speed was high. This demonstrates that the shape parameter of wind distribution is low due to the characteristics of mountain areas, and the standard deviation of wind speed is large due to the effect of mountain winds, therefore, actual generation compared to southwestern coastal areas is almost similar in mountain areas even though wind speed is high.

• Journal of the Korean Solar Energy Society
• /
• v.26 no.4
• /
• pp.63-71
• /
• 2006

The installed capacity of wind turbines in KOREA are growing and enlarging by the central government's support program. Thus, the importance of power performance verification and its uncertainty analysis are recognizing rapidly. This paper described the Power testing results of a 1.5MW wind turbine and analysed an uncertainty level of measurements. The measured power curves are very closely coincide with the calculated one and the annual power production under the given Rayleigh wind speed distribution are estimated with the $4.7{\sim}22.0%$ of uncertainty but, in the dominant wind speed region as $7{\sim}8m/s$, the uncertainty are stably decreased to $7{\sim}8%$.

• Journal of the Korean Solar Energy Society
• /
• v.32 no.6
• /
• pp.37-43
• /
• 2012

Long-term variations in wind speed and capacity factor(CF) on Seongsan wind farm of Jeju Island, South Korea were derived statistically. The selected areas for this study were Subji, having a year wind data at 30m above ground level, Sinsan, having 30-year wind data at 10m above ground level and Seongsan wind farm, where long-term CF was predicted. The Measure-Correlate-Predict module of WindPRO was used to predict long-tem wind characteristics at Seongsan wind farm. Eachyear's CF was derived from the estimated 30-year time series wind data by running WAsP module. As a result, for the 30-year CFs, Seongsan wind farm was estimated to have 8.3% for the coefficien to fvariation, CV, and-16.5% ~ 13.2% for the range of variation, RV. It was predicted that the annual CF at Seongsan wind farm varied within about ${\pm}4%$.

• Journal of the Korean Solar Energy Society
• /
• v.35 no.3
• /
• pp.1-8
• /
• 2015

The MERRA reanalysis data provided online by NASA was applied to predict the monthly energy productions of Donghai Bridge Offshore wind farms in China. WindPRO and WindSim that are commercial software for wind farm design and energy prediction were used. For topography and roughness map, the contour line data from SRTM combined with roughness information were made and used. Predictions were made for 11 months from July, 2010 to May, 2011, and the results were compared with the actual electricity energy production presented in the CDM(Clean Development Mechanism)monitoring report of the wind farm. The results from the prediction programs were close to the actual electricity energy productions and the errors were within 4%.

• Journal of the Korean Solar Energy Society
• /
• v.31 no.2
• /
• pp.63-71
• /
• 2011

The remote-sensng campaign was performed at the Pohang Accelerator Laboratory where is located in a basin 6km inland from Yeongil Bay. The campaign aimed uncertainty assessment of Remtech PA0 SODAR through a mutual comparison with WindCube LIDAR, the remote-sensing equipment for wind resource assessment. The joint observation was carried out by changing the setup for measurement heights three times over two months. The LIDAR measurement was assumed as the reference and the uncertainty of SODAR measurement was quantitatively assessed. Compared with LIDAR, the data availability of SODAR was about half. The wind speed measurement was fitted to a slope of 0.94 and $R^2$ of 0.79 to the LIDAR measurement. However, the relative standard deviation was about 17% under 150m above ground level. Therefore, the Remtech PA0 SODAR is judged to be unsuitable for the evaluation of wind resource assessment and wind turbine performance test, which require accuracy of measurement.

• Journal of the Korean Solar Energy Society
• /
• v.32 no.5
• /
• pp.1-10
• /
• 2012

This paper proposes a modeling and controller design approach for a wind-diesel hybrid system including dump load. Wind turbine depends on nature such as wind speed. It causes power fluctuations of wind turbine. Excessive power fluctuation at stand-alone power grid is even worse than large-scale power grid. The proposed control scheme for power quality is fuzzy PI controller. This controller has advantages of PI and fuzzy controller. The proposed model is carried out by using Matlab/Simulink simulation program. In the simulation study, the proposed controller is compared with a conventional PI controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-diesel hybrid power system.

• Journal of the Korean Solar Energy Society
• /
• v.36 no.1
• /
• pp.11-18
• /
• 2016

The local wind systems in the Pohang region were categorized into wind sectors. Still, thorough knowledge of wind resource assessment, wind environment analysis, and atmospheric environmental impact assessment was required since the region has outstanding wind resources, it is located on the path of typhoon, and it has large-scale atmospheric pollution sources. To overcome the resolution limitation of meteorological dataset and problems of categorization criteria of the preceding studies, the high-resolution wind resource map of the Korea Institute of Energy Research was used as time-series meteorological data; the 2-step method of determining the clustering coefficient through hierarchical clustering analysis and subsequently categorizing the wind sectors through non-hierarchical K-means clustering analysis was adopted. The similarity of normalized time-series wind vector was proposed as the Euclidean distance. The meteor-statistical characteristics of the mean vector wind distribution and meteorological variables of each wind sector were compared. The comparison confirmed significant differences among wind sectors according to the terrain elevation, mean wind speed, Weibull shape parameter, etc.

• Solar Energy
• /
• v.5 no.2
• /
• pp.3-10
• /
• 1985

This paper is concerned with the characterized method of wind speed distribution for calculation of wind power density of regional group and wind potential in Korea. It is shown that the Rayleigh distribution, K = 2, is not suitable for analyzing wind data in Korea. Simple relationship, K = 0.21 V + 0.84, is derived from Weibull wind distribution by analyzing wind data obtained from 24 meteorological station and is a suitable tool for estimation of wind power density. Application of this result, the domestic ideal and actual wind potential are estimated as $3.16{\times}10^9$ KWH/year and $7.14{\times}$10^8 KWH/year respectively for the case of 10 meter height, $1m^2$ swept area and $0.1{\times}0.1Km^2$ land area. And for the case of 50 meter height, ideal and actual wind potential are increased as $7.56{\times}10^9$ KWH/year and $2.37{\times}10^9$ KWH/year respectively.

• Journal of the Korean Solar Energy Society
• /
• v.31 no.2
• /
• pp.72-81
• /
• 2011

The wind data obtained from an AWS(Automated Weather Station) was used to predict the AEP(annual energy production) of Gangwon wind farm having a total capacity of 98 MWin Korea. A wind energy prediction program based on the Reynolds averaged Navier-Stokes equation was used. Predictions were made for three consecutive years starting from 2007 and the results were compared with the actual AEPs presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from the prediction program were close to the actual AEPs and the errors were within 7.8%.

• Journal of the Korean Solar Energy Society
• /
• v.37 no.1
• /
• pp.1-14
• /
• 2017

A series of coupled time domain simulations considering stochastic waves and wind based on five 1-h time-domain analyses are performed in normal operating conditions. Power performance and tower base Fore-Aft bending moment and pitching motion response of the floating spar-buoy wind turbine with 2 MW direct-drive PMSG have been analyzed by using HAWC2 that account for aero-hydro-servo-elastic time domain simulations. When the floating spar-buoy wind turbine is tilted in the wind direction, maximum of platform pitching motion is close to $4^{\circ}$. Statistical characteristics of tower base Fore-Aft bending moment of floating spar-buoy wind turbine are compared to that of land-based wind turbine. Maximum of tower base Fore-Aft bending moment of floating spar-buoy wind turbine and land-based wind is 94,448 kNm, 40,560 kNm respectively. This results is due to changes in blade pitch angle resulting from relative motion between wave and movement of the floating spar-buoy wind turbine.