• Atmosphere
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• v.31 no.1
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• pp.1-15
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• 2021

High-resolution wind resources maps (maps, here after) with spatial and temporal resolutions of 100 m and 3-hours, respectively, over South Korea have been produced and evaluated for the period from July 2016 to June 2017 using Korea Meteorological Administration (KMA) Post Processing (KMAPP). Evaluation of the 10 m- and 80 m-level wind speed in the new maps (KMAPP-Wind) and the 1.5 km-resolution KMA NWP model, Local Data Assimilation and Prediction System (LDAPS), shows that the new high-resolution maps improves of the LDAPS winds in estimating the 10m wind speed as the new data reduces the mean bias (MBE) and root-mean-square error (RMSE) by 33.3% and 14.3%, respectively. In particular, the result of evaluation of the wind at 80 m which is directly related with power turbine shows that the new maps has significantly smaller error compared to the LDAPS wind. Analyses of the new maps for the seasonal average, maximum wind speed, and the prevailing wind direction shows that the wind resources over South Korea are most abundant during winter, and that the prevailing wind direction is strongly affected by synoptic weather systems except over mountainous regions. Wind speed generally increases with altitude and the proximity to the coast. In conclusion, the evaluation results show that the new maps provides significantly more accurate wind speeds than the lower resolution NWP model output, especially over complex terrains, coastal areas, and the Jeju island where wind-energy resources are most abundant.

• 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.

• 한국가시화정보학회:학술대회논문집
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• 2007.11a
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• pp.101-104
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• 2007

Kiwifruit vines with broad leaves are easily torn or shed by high-speed wind. In this study, the threshold wind speed at which a cane is broken was investigated experimentally with varying physical parameters of a kiwifruit vine under two different ABL (atmospheric boundary layer) conditions. In addition, the temporal variation of wind-blown young canes was visualized using a high-speed camera. The average threshold wind speeds for ABL types A and B are about 20.5 m/s and 18.9 m/s, respectively. A wind-blown young cane takes periodic up-and-down motion when it is broken off. The mean motion frequency of young canes of the kiwifruit vines was found to be about 4.5Hz.

• Journal of the Korean Solar Energy Society
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• v.33 no.1
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• pp.32-39
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• 2013

Effects of Weibull shape parameter, k, on capacity factors of wind turbines were investigated. Wind distributions with mean wind speeds of 5 m/s, 6 m/s, 7 m/s and 8 m/s were simulated and used to estimate the annual energy productions and capacity factors of a 2MW wind turbine for various Weibull shape parameters. It was found from the study that the capacity factors of wind turbines are much affected by Weibull shape parameters. When the annual mean wind speed at the hub height of a wind turbine was about 7 m/s, and the air density was assumed to be 1.225 $kg/m^3$, the maximum capacity factor of a 2 MW wind turbine having a rated wind speed of 13 m/s was found to occur with the shape parameter of 2. It was also found that as the mean wind speed increased, the Weibull k parameter which yielded the maximum capacity factor increased. The simulated results were also validated by predictions of capacity factors of wind turbines using wind data measured in complex terrain.

• Atmosphere
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• v.21 no.4
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• pp.471-480
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• 2011

This study investigates the characteristics of surface wind in North Korea using mesoscale model WRF. Hourly wind fields were simulated for one year representing mean characteristics of an 11-years period from 1998 to 2008. The simulations were performed on a nested grid from 27 km to 1 km horizontal resolution. The simulated wind map at 10 m above ground level is verified with 27 surface observations. Statistical verification skill score indicates that wind speed tends to overestimate in surface layer. The average RMSE value of the simulated wind speed is around $2.8ms^{-1}$. Wind map in North Korea showed that strong wind speed is distributed in the mountainous and western coastal region. The results of this wind mapping study contribute for the founding of wind energy potential location.

• Wind and Structures
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• v.26 no.3
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

• Asian Journal of Atmospheric Environment
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• v.9 no.4
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• pp.288-297
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• 2015

In this study, wind conditions and its energy potential have been assessed by conducting a Weibull analysis of the wind speed data (over the period of 2002-2011) measured from a port city (Mongla) and an isolated island (Sandwip) in Bangladesh. The monthly mean wind speed at Mongla ranged from 1.60 m/s (December) to 2.47 m/s (April). The monthly values of Weibull shape parameter (k) were from 1.27 to 2.53. In addition, the values of the scale parameter (c) and the monthly wind power density ranged from 1.76 to 2.79 m/s and 3.95 to $17.45W/m^2$, respectively. The seasonal mean wind speed data varied from 1.72 (fall) to 2.29 m/s (spring) with the wind power density from 5.33 (fall) to $14.26W/m^2$ (spring). In the case of Sandwip, the results were comparable to those of Mongla, but moderate reductions in all the comparable variables were observed. The wind data results of these two areas have been compared with those of eight other locations in the world with respect to wind power generation scale. According to this comparison, the wind power generation scale for Mongla and Sandwip was adequate for stand-alone small/micro-scale applications such as local household consumption, solar-wind hybrid irrigation pumps, and battery charging.

• Wind and Structures
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• v.15 no.1
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• pp.1-15
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• 2012

High-resolution wind data were acquired from a 100-m high offshore tower during the passage of Typhoon Hagupit in September, 2008. The meteorological tower was equipped with an ultrasonic anemometer and a number of cup anemometers at heights between 10 and 100 m. Wind characteristics of the strong typhoon, such as mean wind speed and wind direction, turbulence intensity, turbulence integral length scale, gust factor and power spectra of wind velocity, vertical profiles of mean wind speed were investigated in detail based on the wind data recorded during the strong typhoon. The measured results revealed that the wind characteristics in different stages during the typhoon varied remarkably. Through comparison with non-typhoon wind measurements, the phenomena of enhanced levels of turbulence intensity, gust factors, turbulence integral length scale and spectral magnitudes in typhoon boundary layer were observed. The monitored data and analysis results are expected to be useful for the wind-resistant design of offshore structures and buildings on seashores in typhoon-prone regions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.10
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• pp.1455-1460
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• 2014

Wind turbine generators were designed on general regulations of wind condition. At real situations, it could be different from the design conditions. There are many control methods and definitions of transient region, because an efficient wind turbine generator control logic is the important matter in generator performance and annual energy production at real conditions. In this document, the power generation sensitivity for wind speed and turbulence intensities was defined to know the sensitive transient region. Wind conditions are applied for the ranges of 7~10m/s mean wind speed and 14~20% turbulence intensity. The sensibility of HR-D86 wind generator was increased in transient region(8~10m/s) on power curve diagram through a torque control to a pitch control. And then GH-bladed simulations was performed for performance analysis of the torque mode switching in transient region on 2MW direct drive wind generator(HR-D86) which is designed IEC class II for onshore. Through the sensitivity and performance analysis, the sensitivity for real wind condition could be the performance index for an wind generator. And the torque mode switching in transient region can increase the mean power generation on HR-D86 wind turbine generator.

• Journal of Wind Energy
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• v.14 no.1
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• pp.37-43
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• 2023

In this study, synthetic time series wind data was generated numerically using a second-order Markov chain. One year of wind data in 2020 measured by the AWS on Wido Island was used to investigate the statistics for measured wind data. Both the transition probability matrix and the cumulative transition probability matrix for annual hourly mean wind speed were obtained through statistical analysis. Probability density distribution along the wind speed and autocorrelation according to time were compared with the first- and the second-order Markov chains with various lengths of time series wind data. Probability density distributions for measured wind data and synthetic wind data using the first- and the second-order Markov chains were also compared to each other. For the case of the second-order Markov chain, some improvement of the autocorrelation was verified. It turns out that the autocorrelation converges to zero according to increasing the wind speed when the data size is sufficiently large. The generation of artificial wind data is expected to be useful as input data for virtual digital twin wind turbines.