• Atmosphere
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• v.18 no.3
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• pp.171-182
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• 2008

In this study, we analyzed the spatial and temporal distribution of wind resources over Korea based on hourly observational data recorded over a period of 5 years from 457 stations belonging to Korea Meteorological Administration (KMA). The surface and 850 hPa wind data obtained from the Korea Local Analysis and Prediction System (KLAPS) and the Regional Data Assimilation and Prediction System (RDAPS) over a period of 1 year are used as supplementary data sources. Wind speed is generally high over seashores, mountains, and islands. In 62 (13.5%) stations, mean wind speeds for 5 years are greater than $3ms^{-1}$. The effects of seasonal wind, land-sea breeze, and mountain-valley winds on wind resources over Korea are evaluated as follows: First, wind is weak during summer, particularly over the Sobaek Mountains. However, over the coastal region of the Gyeongnam-province, strong southwesterly winds are observed during summer owing to monsoon currents. Second, the wind speed decreases during night-time, particularly over the west coast, where the direction of the land breeze is opposite to that of the large-scale westerlies. Third, winds are not always strong over seashores and highly elevated areas. The wind speed is weaker over the seashore of the Gyeonggi-province than over the other seashores. High wind speed has been observed only at 5 stations out of the 22 high-altitude stations. Detailed information on the wind resources conditions at the 21 stations (15 inland stations and 6 island stations) with high wind speed in Korea, such as the mean wind speed, frequency of wind speed available (WSA) for electricity generation, shape and scale parameters of Weibull distribution, constancy of wind direction, and wind power density (WPD), have also been provided. Among total stations in Korea, the best possible wind resources for electricity generation are available at Gosan in Jeju Island (mean wind speed: $7.77ms^{-1}$, WSA: 92.6%, WPD: $683.9Wm^{-2}$) and at Mt. Gudeok in Busan (mean wind speed: $5.66ms^{-1}$, WSA: 91.0%, WPD: $215.7Wm^{-2}$).

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.2
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• pp.149-156
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• 2014

This paper proposes the battery charging algorithm for small-scale wind power generator using three phase PWM converter. it is impossible to control output power of the converter in over wind speed region since back EMF of PMSG is higer than battery voltage. Therefore, battery charging algorithm is proposed to expand battery charging over wind speed region. The suggested method is using the q-axis current for battery charging in the rated wind speed region. In the over wind speed region after it lower back EMF of PMSG using d-axis current it can control output power of the converter. The validity of the proposed algorithm are verified by experiments.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.959-960
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• 2007

The wind power has been used steadily since long ago, but the importance of it has been faded because of the abundant and convenient fossil energy. Now, due to the energy crisis, experiencing the environmental problems etc, the necessity of using it growing bigger. Because the small wind turbines under a few kW grade has the merits of setting up with low costs by individuals, and get the energy saving effects that, it has the secured, separate markets from the range systems, and the developing of it is continuously proceeding. The small wind turbine system must have the output power regulating system for the over wind speed, to run steadily in the various wind speed environment. In case of the small wind turbine system, to prevent the breaking and for safety, at the over wind speed, additional system is required, and in most cases, output power is restricted by mechanical means. In this paper, the furling system makes the tail and the head move to make the blades to the wind in slanted angle, restrict the output power at the over wind speed. In thesis, small prototype wind turbine is made, and analyzing the output power characteristics at the over wind speed, and to verify, through the logical study and tests.

• Atmosphere
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• v.20 no.2
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• pp.63-71
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• 2010

In this study, we derived the wind speed at 50 m and 80 m above sea level from 567 stations over a period of 1 year and correlated to measured wind speed at 5 radiosonde sites. From these correlations, we derived and analyzed the spatial distribution of wind map over Korea based on hourly observational data recorded over a period of 5 years from 2004 to 2008. As a results, wind speed is generally high over seashores, mountains, and islands. Mean wind speed over Korea at 50 and 80 m above sea level for 5 years during 2004 to 2008 seasonally are highest at Spring, and then followed by Winter, Fall, and Summer. In 76 (14%) stations, mean wind speed at 80 m above sea level for 5 years during 2004 to 2008 are greater than $5ms^{-1}$. The prevailing winds over Korea at 80 m above sea level for 5 years during 2004 to 2008 are North (44%), Northwest (16%), and West (15%). In 99 stations, the % of wind faster than $5ms^{-1}$ was higher than 40%, and in 62 stations, the % of wind faster than $5ms^{-1}$ was higher than 50%. In 178 station, the % of prevailing winds was higher than 30%, and there are 7 stations which also have wind speeds over $5ms^{-1}$, ranking from highest to lowest, Dongsong, Daegwallyeong, Baekun Mt., Hyangrobong Mt., Sorak Mt., Gosan, and Misiryeong Mt..

• New & Renewable Energy
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• v.10 no.2
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• pp.29-39
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• 2014

This study examines the future variability of surface wind speed and solar radiation based on climate change scenario over the Korean Peninsula. Climate change scenarios used in this study are RCP 4.5 and 8.5 with a 12.5 km horizontal resolution. Climate change scenario RCP 4.5 and 8.5 reproduce the general features of wind speed over the Korean Peninsula, such as strong wind speed during spring and winter and weak wind speed during summer. When compared with the values of wind speed and solar radiation of the future, they are expected to decrease current wind and solar resource map. Comparing the resource maps using RCP 4.5 and 8.5 scenarios, wind speed and solar radiation decrease with increasing greenhouse gas concentration. Meteorological resource maps of future wind and solar radiation should be improved with high resolution for the industrial application.

• Atmosphere
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• v.31 no.1
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• pp.85-100
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• 2021

The necessity of accurate high-resolution meteorological forecasts becomes increasing in socio-economical applications and disaster risk management. The Korea Meteorological Administration Post-Processing (KMAPP) system has been operated to provide high-resolution meteorological forecasts of 100 m over the South Korea region. This study evaluates and improves the KMAPP performance in simulating wind speeds over complex terrain areas using the ICE-POP 2018 field campaign measurements. The mountainous measurements give a unique opportunity to evaluate the operational wind speed forecasts over the complex terrain area. The one-month wintertime forecasts revealed that the operational Local Data Assimilation and Prediction System (LDAPS) has systematic errors over the complex mountainous area, especially in deep valley areas, due to the orographic smoothing effect. The KMAPP reproduced the orographic height variation over the complex terrain area but failed to reduce the wind speed forecast errors of the LDAPS model. It even showed unreasonable values (~0.1 m s-1) for deep valley sites due to topographic overcorrection. The model's static parameters have been revised and applied to the KMAPP-Wind system, developed newly in this study, to represent the local topographic characteristics better over the region. Besides, sensitivity tests were conducted to investigate the effects of the model's physical correction methods. The KMAPP-Wind system showed better performance in predicting near-surface wind speed during the ICE-POP period than the original KMAPP version, reducing the forecast error by 21.2%. It suggests that a realistic representation of the topographic parameters is a prerequisite for the physical downscaling of near-ground wind speed over complex terrain areas.

• Atmosphere
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• v.21 no.4
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• pp.439-446
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• 2011

NCEP reanalysis data were analyzed in order to provide distribution of global wind resource and wind speed in the surface layer for the years 2000-2009. Wind speed at 10 m above ground level (AGL) was converted to wind speed at 80 m above the ground level using the power law. The global average 80 m wind speed shows a maximum value of $13ms^{-1}$ at the storm track region. High wind speed over the land exists in Tibet, Mongolia, Central North America, South Africa, Australia, and Argentina. Wind speed over the ocean increased with a large value in the South China Sea, Southeast Asia, East Sea of the Korea. Sea surface wind in Western Europe and Scandinavia are suitable for wind farm with a value of $7-8ms^{-1}$. Areas with great potential for wind farm are also found in Eastern and Western coastal region of North America. Sea surface wind in Southern Hemisphere shows larger values in the high latitude of South America, South Africa and Australia. The distribution of low-resolution reanalysis data represents general potential areas for wind power and can be used to provide information for high-resolution wind resource mapping.

• Journal of Wind Energy
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• v.9 no.4
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• pp.9-15
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• 2018

In a previous study, a technique for measuring wind speed and direction by using a roll-rotating three-axis ultrasonic anemometer was proposed and verified by wind tunnel tests. In the tests, instead of a roll sensor, roll angle was trimmed to make no up flow in the transformed wind speeds. Verification was done in point of the residual error of the rotation effect treatment. In this study, roll angle was measured from the roll motor encoder and the transformed wind speed and direction on the test section axis were compared with the ones provided to the test section. As a result, up to yaw $20^{\circ}$ at a wind speed of 12 m/sec or over, the RMS error of wind speed was within the double of the ultrasonic anemometer error. But at yaw $30^{\circ}$, it was over the double of the ultrasonic anemometer error. Regardless of wind speed, at yaw $20^{\circ}$ and $30^{\circ}$, the direction error was within the double of the ultrasonic anemometer error. But at yaw $10^{\circ}$ or less, it was within the error of the ultrasonic anemometer itself. This is a very favorable characteristic to be used for wind turbine yaw control.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.173-174
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• 2015

If a wind speed decreases during inertial control of a wind turbine generator (WTG), the rotor speed might decrease below the minimum operating limit, which is called over-deceleration (OD). When OD occurs, inertial control should be disabled and then the output power of a WTG significantly decreases. This significant power reduction causes a subsequent frequency drop. This paper proposes the stepwise inertial control to prevent OD when a wind speed decreases during inertial control. To do this, the proposed scheme changes the additional power output based on the rotor speed. The performance of the proposed scheme is investigated using an EMTP-RV simulator. The results show that the proposed inertial control scheme prevent OD even when the wind speed decreases during inertial control.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.484-489
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• 2014

Three phase PWM(Pulse Width Modulation) converter of the small-scale wind power system is able to charge battery under the rated wind speed regions. However, it is impossible to control output power of converter at the over win speed region because back-EMF(Electro Motive Force) of PMSG(Permanent Magnet Synchronous Generator) is higher than the battery terminal voltage of PMSG is reduced. However, the cut-off wind speed exists although battery charging algorithm is implemented by flux weakening control method. Therefore, this paper performs analysis of other factors which affects limitation wind speed. The validity of the analysis are verified through simulation.