• 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 $C_r and C_v, C_v is higher than C_r$.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2402-2409
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• 2009

This paper proposed a simple and helpful analysis model of voltage variation in order to predict the voltage variation at PCC (Point of Common Coupling), when a wind turbine is connected in an isolated grid. The PCC voltage flucuates when the wind turbine outputs active power to an isolated grid. This voltage variation is proportional to the product of the line impedance from the ideal generator to the PCC and the wind turbine output current. And It is different according as where wind turbine is connected. To solve the problem of voltage variation, this paper proposed the reactive power control. To verify the proposed analysis model, this paper utilized PSCAD/EMTDC Simulation and the field measurement data of the voltage variation during the wind power generation.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.782-788
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• 2014

Wind power generation has been viewed as a promising renewable energy to meet challenge of climate change. However, wind power is susceptible to climate change because previous investigation shows there are declining trends of the land surface wind speeds over middle and lower latitudes. Since long term variation trends is notably different from inter-annual random variation and could have notable impact on wind farm from planning perspective, observed meteorological data of Taiwan is investigated to find out long term variation trends of wind speed and its impact on wind power generation. It is discovered that wind speed in majority of stations in west coast of Taiwan have ascending trends while that of all investigated stations in east coast have descending trends. Since east of Taiwan is not suitable for wind power development for its higher likelihood suffering Typhoons and most of established wind farm locate in west coast of Taiwan, it is speculated that long term variation trend of wind do not have notable negative impact on wind power generation in Taiwan.

• Atmosphere
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• v.16 no.3
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• pp.169-185
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• 2006

We have investigated the wind speed variations over the leeward region when the strong wind blows. In this study we employ Envi-met numerical model to simulate the effect of surface boundary conditions. This model is applied for three cases which are characterized by land use and terrain height. The base case having natural geographical condition shows the weakest wind speed around lee side of Chunsudae. The others which remove the vegetation and cut off the terrain above 20 m ASL represent the stronger wind speed than base case. The main factor of this result is the surface friction. The distinct variation of wind is found at offshore area between Chunsudae and the southern part of village, but the northern part where is apart from Chunsudae shows a small variation of wind pattern. The weakening of wind speed around residential area is a maximum of 4~10 m/s when the wind blows in the village as strong as 55 m/s. The gust wind speed is weakened about 7~17 m/s in this case if the coefficient of gust wind adapted as 1.75.

• Wind and Structures
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• v.18 no.6
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• pp.633-650
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• 2014

The uncertainty of extreme wind speeds is one key contributor to the uncertainty of wind loads and their effects on structures. The probability distribution of annual extreme wind speeds may be characterized using a classical Gumbel Type distribution. The expression that establishes the relationship between the extreme wind speeds at different recurrence periods and the corresponding coefficients of variation is formulated, and its efficacy is validated. The coefficients of variation are calibrated to be about 0.125 and 0.184 according to defined Chinese and US design specifications, respectively. Based on the wind data of 54 cities in China, 49 meteorological stations in the US, 3 stations in Singapore, the coefficients span intervals of (0.1, 0.35), (0.08, 0.20) and (0.06, 0.14), respectively. For hurricanes in the US, the coefficients range approximately from 0.3 to 0.4. This convenient technique is recommended as one alternative tool for coefficient of variation analyses in the future revisions of related codes. The sensitivities of coefficients of variation for 49 meteorological stations in the US are quantified and demonstrated. Some contradictions and incompatibilities can be clearly detected and illustrated by comparing the coefficients of variation obtained with different combinations of recurrence period wind data.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.993-1002
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• 2022

This paper relates to a method of modeling the thrust dynamic load caused by the thrust variation occurring on the blade due to the tower shadow below the rated wind speed. A method that uses thrust coefficient is presented by introducing "tower shadow coefficient of thrust variation". For a 2MW wind turbine, the values of "tower shadow coefficient of thrust variation" are calculated and analyzed at wind speeds below the rated. The dynamic load model of thrust under tower shadow is evaluated in Matlab/Simulink using the obtained "tower shadow coefficient of thrust variation" and thrust coefficient. It shows that the thrust variations acting on the three blades by the tower shadow can be expressed using both the thrust coefficient and the introduced "tower shadow coefficient of thrust variation".

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.4
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• pp.407-414
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• 2016

As wind turbines are getting larger in size with multi-MW capacity, the blades are getting longer, over 40 m, and hence the asymmetric loads produced during the rotation of the rotor blades are increasing. Some factors such as wind shear, tower shadow, and turbulence have an effect on the asymmetric loads on the blades. This paper focuses on a method of modeling the dynamic load acting on a blade because of thrust variation under wind shear. A method that uses thrust coefficient is presented. For this purpose, "wind shear coefficient of thrust variation" is defined and introduced. Further, we calculate the values of the "wind shear coefficient of thrust variation" for a 2 MW on-shore wind turbine, and analyze them for speeds below the rated wind speed. Then, we implement a dynamic model that represents the thrust variation under wind shear on a blade, using MATLAB/Simulink. It is shown that it is possible to express thrust variations on three blades under wind shear by using both thrust coefficient and "wind shear coefficient of thrust variation."

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.1-8
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• 2013

Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and -9.57%~9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within ${\pm}10%$.

• Journal of Power Electronics
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• v.9 no.1
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• pp.85-92
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• 2009

This paper studies the method to predict voltage variation that can be presented in the case of operating a small-sized wind turbine in grid connection to the isolated small-sized power system. In order to do this, it makes up the simplified simulation model of the existing power plant connected to the isolated system, load, transformer, and wind turbine on the basis of PSCAD/EMTDC and compares them with the operating characteristics of the actual established wind turbine. In particular, it suggests a simplified model formed with equivalent impedance of the power system network including the load to analytically predict voltage variation at the connected point. It also confirms that the voltage variation amount calculated by the suggested method accords well with both simulation and actually measured data. The results can be utilized as a tool to ensure security and reliability in the stage of system design and preliminary investigation of a small-sized grid connected wind turbine.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.1
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• pp.69-74
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• 2010

In a grid connected variable speed wind turbine, the PCC voltage and the wind power fluctuate as the wind velocity changed. And this voltage variation is changed due to location of PCC. This paper calculate the value of PCC voltage variation which is proportional to the product of the line impedance from the ideal generator to the PCC and the wind turbine output current. And to reduce this PCC voltage variation, this paper calculate the required reactive power analytically using the vector diagram method. Output reactive current is changed, if the reactive current is limited by inverter capacity or grid code have the margin of voltage variation. If the grid connected inverter is controlled by proposed algorithm, the PCC voltage variation is minimized though the wind turbine output change at random. To verify calculated voltage variation and required reactive power, this paper utilized Matlab and PSCAD/EMTDC simulation and real small wind turbine and power system in Sapsido, island in the Yellow Sea.