• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.247-253
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• 2011

A sustainability of electricity supply has emerged as a critical issue for low carbon green growth in South Korea. Wind power is the fastest growing source of renewable energy. However, due to its own intermittency and volatility, the power supply generated from wind energy has variability in nature. Hence, accurate forecasting of wind speed and power plays a key role in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. This paper presents a short-term wind speed prediction method based on support vector regression. Moreover, particle swarm optimization is adopted to find an optimum setting of hyper-parameters in support vector regression. An illustration is given by real-world data and the effect of model regularization by particle swarm optimization is discussed as well.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.29-34
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• 2010

Wind speed and wind direction are usually taken using two parameters: wind speed and wind direction. This paper studies the average wind speed and direction calculation methods. The paper first introduces to basic wind's knowledge, and then presents several methods in calculating average wind speed and direction. Lastly some graphs are plotted base on these computational methods and the implementation of these methods in an actual buoy system.

• Journal of Environmental Science International
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• v.9 no.6
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• pp.475-482
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• 2000

The purpose of this study is to find out the temporal and spatial characteristics of the diurnal wind variation between coastal and inland areas using the hourly wind data of 58 AWS-stations in the South Korea which are collected during the 10 years from 1980. Diurnal variation is investigated by using the Fast Fourier Transform(FFT), and the wind direction in investigated by comparing C(sub)r with C(sub)v represented the constancy of wind. For the scalar wind speed, the maximum wind speed occurs in the daytime 14h to 16h. The maximum diurnal amplitude at coastal areas occurs from 12h to 16h, and is about 2 hours faster than that at inland areas. Vector mean wind speed is strong at coastal areas and Chupungnyong, Kumi, Taegu of inland areas. The diurnal variation ellipses make a right angle with coastline show that the land and sea breezes are prevailing. The constancy of wind is strong at all observations in January. In the relationship between $C_r and C_v, C_v is higher than C_r$.

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

• East Asian Journal of Business Economics (EAJBE)
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• v.3 no.3
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• pp.14-26
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• 2015

A wind speed forecast is a crucial and sophisticated task in a wind farm for planning turbines and corresponds to an estimate of the expected production of one or more wind turbines in the near future. By production is often meant available power for wind farm considered (with units KW or MW depending on both the wind speed and direction. Such forecasts can also be expressed in terms of energy, by integrating power production over each time interval. In this study, we technically focused on mathematical modeling of wind speed and direction forecast based on locally data set gathered from Aghdasiyeh station in Tehran. The methodology is set on using most common techniques derived from literature review. Hence we applied the most sophisticated forecasting methods to embed seasonality, trend, and irregular pattern for wind speed as an angular variables. Through this research, we carried out the most common techniques such as the Box and Jenkins family, VARMA, the component method, the Weibull function and the Fourier series. Finally, the best fit for each forecasting method validated statistically based on white noise properties and the final comparisons using residual standard errors and mean absolute deviation from real data.

• Proceedings of the KSRS Conference
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• v.1
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• pp.146-149
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• 2006

Marine surface winds observed by two microwave sensors, SeaWinds and Advanced Microwave Scanning Radiometer (AMSR), on the Advanced Earth Observing Satellite-II (ADEOS-II) are evaluated by comparison with off-shore moored buoy observations. The wind speed and direction observed by SeaWinds are in good agreement with buoy data with root-mean-squared (rms) differences of approximately 1 m $s^{-1}$ and $20^{\circ}$, respectively. No systematic biases depending on wind speed or cross-track wind vector cell location are discernible. The effects of oceanographic and atmospheric environments on the scatterometry are negligible. The wind speed observed by AMSR also exhibited reasonable agreement with the buoy data in general with rms difference of 1.2 m $s^{-1}$. Systematic bias which was observed in earlier versions of the AMSR winds has been removed by algorithm refinements. Intercomparison of wind speeds globally observed by SeaWinds and AMSR on the same orbits also shows good agreements. Global wind speed histograms of the SeaWinds data and European Centre for Medium-range Weather Forecasts (ECMWF) analyses agree precisely with each other, while that of the AMSR wind shows slight deviation from them.

• Asian Journal of Atmospheric Environment
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• v.10 no.2
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• pp.80-89
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• 2016

In the complex terrain where local wind systems are formed, accurate understanding of regional wind variability is required for wind resource assessment. In this paper, cluster analysis based on the similarity of time-series wind vector was applied to classify wind regions with similar wind characteristics and the meteorological validity of regionalization method was evaluated. Wind regions in Jeju Island and Busan were classified using the wind resource map of Korea created by a mesoscale numerical weather prediction modeling. The evaluation was performed by comparing wind speed, wind direction, and wind variability of each wind region. Wind characteristics, such as mean wind speed and prevailing wind direction, in the same wind region were similar and wind characteristics in different wind regions were meteor-statistically distinct. It was able to identify a singular wind region at the top area of Mt. Halla using the inconsistency of wind direction variability. Furthermore, it was found that the regionalization results correspond with the topographic features of Jeju Island and Busan, showing the validity.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.67-74
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• 2022

To analyze the motion of aircraft through computing the dynamics equations, true airspeed is essential for obtaining aerodynamic loads. Although the airspeed is measured by on-board instruments such as pitot tubes, measurement data are difficult to obtain for commercial flights because they include sensitive data about the airline operations. One of the commonly available trajectory data, Automatic Dependent Surveillance-Broadcast data, provide aircraft's speed in the form of ground speed. The ground speed is a vector sum of the local wind velocity and the true airspeed. This paper present a method to estimate true airspeed by combining the trajectory, meteorological, and topology data available to the public. To integrate each data, we first matched the coordinate system and then unified the altitude reference to the mean sea level. We calculated the wind vector for all trajectory points by interpolating from the lower resolution grid of the meteorological data. Finally, we calculate the true airspeed from the ground speed and the wind vector. These processes were applied to several sample trajectories with corresponding meteorological data and the topology data, and the estimated true airspeeds are presented.

• Atmosphere
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• v.17 no.4
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• pp.327-337
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• 2007

In this study, we examined the new ensemble training approach to reduce the systematic error and improve prediction skill of wind by using the Short-range Ensemble prediction system (SENSE), which is the mesoscale multi-model ensemble prediction system. The SENSE has 16 ensemble members based on the MM5, WRF ARW, and WRF NMM. We evaluated the skill of surface wind prediction compared with AWS (Automatic Weather Station) observation during the summer season (June - August, 2006). At first stage, the correction of initial state for each member was performed with respect to the observed values, and the corrected members get the training stage to find out an adaptive weight function, which is formulated by Root Mean Square Vector Error (RMSVE). It was found that the optimal training period was 1-day through the experiments of sensitivity to the training interval. We obtained the weighted ensemble average which reveals smaller errors of the spatial and temporal pattern of wind speed than those of the simple ensemble average.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.28 no.4
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• pp.398-411
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• 1992

The characteristics of local climate in the vicinity of Duckyang Bay have been investigated with the analysis of the surface observation data of Gohug District and the aerological data of Kwangju. In principal features of local climate, the annual range in temperature appeared identical with the mean value(24~$25^{\circ}C$) of the south coastal area, and evaporation from April to September was likely less than precipitation. The average speed of surface wind in Summer seemed higher than in other seasons on account of wea breeze. Relative humidity was 74%, annual average. In the mean cloud cover Summer(6.4) showed greater deal of amount than Winter(4.2). Duration of sunshine was the longest in May(268.4hrs), while the shortest in February(188.4hrs). The amount of the precipitable water was the greatest in July, whereas the least in January, and in Summer the greatest, in Autumn the second greatest, and in Spring the third greatest, and in Winter the least in consideration of seasonal orders. The Summer deviation was most remarkable around all sides. The direction of vector wind appeared the most changeable on the earth surface. At an altitude of 300mb all the winds blew west around all months. Moreover, water vapor transport was measured to be the greatest in Summer; while the least in Winter. So was the deviation of water vapor transport. And lastly frequency of occurrence of days in which a little cloud appeared(less than 5/10) was high except for Summer, when northerly winds blew; while frequency of occurrence of day plenty of clouds floated was outstandingly high at the time of strong southerly winds.