• Journal of Industrial Technology
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• v.22 no.A
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• pp.49-57
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• 2002

The accurate wind speed information at the hub height of a wind turbine is very essential to the exact estimation of the wind turbine power performance testing. Several methods on the site calibration, which is a technique to estimate the wind speed at the wind turbine's hub height based on the measured wind data using a reference meteorological mast, are introduced. A site calibration result and the wind resource assessment for the Taekwanryung test site are presented using a one-month wind data from a reference meteorological mast and a temporal mast installed at the site of wind turbine. From this analysis, it turns out that the current location of the reference meteorological mast is wrongly determined, and the self-developed codes for the site calibration are working properly. Besides, an analysis on the uncertainty allocation for the wind speed correction using site calibration is performed.

• Journal of Environmental Impact Assessment
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• v.16 no.6
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• pp.503-510
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• 2007

Since 1990s many skyscrapers have been built in Seoul. However, gusty winds occur among tall buildings by descending turbulences due to the upper air blocking. This study aims to investigate the wind characteristics of skyscraper prevailing wind direction. In order to evaluate the building wind in this area, The wind speed and the wind direction were measured using propeller type RM-Young wind monitor in this study. The maximum wind speed was recorded by 15.1 m/sec and the main wind direction is WNW and NW. The ultimate purpose of this study is to figure out the phenomena of building wind impact and also to provide essential basic data for establishing proper guidelines in building wind impact assessment for skyscrapers in Korea.

• Journal of Environmental Science International
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• v.10 no.2
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• pp.135-142
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• 2001

In order to investigate horizontal wind field in the boundary layer around Pusan area, wind speed and wind direction measured at 14 AWS(Automatic Weather Station), 1997, was used. The wind direction at PRM(Pusan Regional Meterological Office) was showed that southwest and northeast wind dominated for spring and summer, northeast wind for fall and northwest for winter. Anticline flow was showed at \`Gaekumm\` which is located between Mt. Backyang(641m) and Mt. Yumkwang(503m) and affected on wind field at \`Pusanjin\`. The low wind speed and various wind direction was represented at the basin topography, \`Buckgu\`, \`Jeasong\`, \`Ilkwang\` and \`Kijang\`. The annual mean wind speed at 14 sites, 2.5ms(sup)-1, was lower than that measured at PRMO, 3.9ms(sup)-1. The wind direction analysis showed that the case of same direction in compare with that measured at PRMO is about 54% and case of opposite direction is about 12%. Annual and seasonal mean windrose showed wind direction is affected by not only synoptic weather state but also topography.

• Wind and Structures
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• v.19 no.5
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• pp.467-480
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• 2014

The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.

• Wind and Structures
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• v.3 no.3
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• pp.177-191
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• 2000

This paper presents an approach for evaluating directionality effects for both wind speeds and wind loads in hurricane-prone regions. The focus of this study is on directional wind loads on low-rise structures. Using event-based simulation, hurricane directionality effects are determined for an open-terrain condition at various locations in the southeastern United States. The wind speed (or wind load) directionality factor, defined as the ratio of the N-year mean recurrence interval (MRI) wind speed (or wind load) in each direction to the non-directional N-year MRI wind speed (or wind load), is less than one but increases toward unity with increasing MRI. Thus, the degree of conservatism that results from neglecting directionality effects decreases with increasing MRI. It may be desirable to account for local exposure effects (siting effects such as shielding, orientation, etc.) in design. To account for these effects in a directionality adjustment, the factor described above for open terrain would need to be transformed to other terrains/exposures. A "local" directionality factor, therefore, must effectively combine these two adjustments (event directionality and siting or local exposure directionality). By also considering the direction-specific aerodynamic coefficient, a direction-dependent wind load can be evaluated. While the data necessary to make predictions of directional wind loads may not routinely be available in the case of low-rise structures, the concept is discussed and illustrated in this paper.

• Wind and Structures
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• v.27 no.1
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• pp.29-40
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• 2018

To investigate the characteristics of the combined wind field produced by the natural wind field and the train-induced wind field on the bridge, the aerodynamic models of train and bridge are established and the overset mesh technology is applied to simulate the movement of high-speed train. Based on ten study cases with various crosswind velocities of 0~20 m/s and train speeds of 200~350 km/h, the distributions of combined wind velocities at monitoring points around the train and the pressure on the car-body surface are analyzed. Meanwhile, the difference between the train-induced wind fields calculated by static train model and moving train model is compared. The results show that under non-crosswind condition, the train-induced wind velocity increases with the train speed while decreases with the distance to the train. Under the crosswind, the combined wind velocity is mainly controlled by the crosswind, and slightly increases with the train speed. In the combined wind field, the peak pressure zone on the headstock surface moves from the nose area to the windward side with the increase of wind velocity. The moving train model ismore applicable in analyzing the train induced wind field.

• Atmosphere
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• v.20 no.2
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• pp.195-210
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• 2010

This study uses mesoscale model WRF to investigate characteristics of wind fields in South Korea, a region with a complex terrain. Hourly wind fields were simulated for one year representing mean characteristics of an 11-year period from year 1998 to year 2008. The simulations were performed on a nested grid from 27 km down to 1 km horizontal resolution. Seasonal variation of wind speed indicates that wind is strongest during the spring and winter seasons. Spatial distribution of mean wind speed shows wind energy potential at its peak in mountainous region of Gangwon-do, the east coast, and Jeju Island. Wind speed peaks at night in mountainous and eastern coastal regions, and in the afternoon inland and in the southwestern coastal region. The simulated wind map was verified with four upper-air sounding observations. Wind speed was shown to have a more pronounced overestimation tendency relative to observation in the winter rather than summer. The results of this wind mapping study help identify locations with the highest wind energy potential in South Korea.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.15 no.2
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• pp.138-142
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• 2003

Influences of Ieodo Ocean Research Station(IORS) on the ambient wind field were investigated through a wind tunnel experiment. To secure accurate wind speeds and directions, distortions due to the structure itself on which wind-measuring devices are to be installed should be taken into account. It was shown that the wind speed ratio was sensitive to wind direction and measuring position rather than approaching wind speed. The wind speed ratios measured at main wind tower were more than B .0 in every approaching direction, and the distortion of wind direction was under 6$^{\circ}$.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.869-877
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• 2016

Necessity has compelled man to improve upon the art of tapping wind energy for power generation; an apt reliever of strain exerted on the non-renewable fossil fuel. The power generation in a Wind Farm (WF) depends on site and wind velocity which varies with time and season which in turn determine wind power modeling. It implies, the development of an accurate wind speed model to predict wind power fluctuations at a particular site is significant. In this paper, Box-Jenkins ARIMA (Auto Regressive Integrated Moving Average) time series model for wind speed is developed for a 99MW wind farm in the southern region of India. Because of the uncertainty in wind power developed, the economic viability and reliability of power generation is significant. Life Cycle Costing (LCC) method is used to determine the economic viability of WF generated power. Reliability models of WF are developed with the help of load curve of the utility grid and Capacity Outage Probability Table (COPT). ARIMA wind speed model is used for developing COPT. The values of annual reliability indices and variations of risk index of the WF with system peak load are calculated. Such reliability models of large WF can be used in generation system planning.

• Wind and Structures
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• v.37 no.2
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• pp.153-161
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• 2023

Wind speed data from Nepal and adjoining countries have been analyzed to estimate an extreme wind speed climatology for the region. Previously wind speed information for Nepal was adopted from the Indian National Standard and applied to two orographically different regions: above and below 3000 m elevation respectively. Comparisons of the results of this analysis are made with relevant codes and standards. The study confirms that the assigned basic wind speed of 47 m/s for the plains and hills of Nepal (below 3000 m) is appropriate, however, data to substantiate a basic wind speed of 55 m/s above 3000 m is unavailable. Using a composite analysis of 15 geographically similar stations, the study also generated 435 years of annual maxima wind data and fitted them to Type I and Type III extreme value distributions. The results suggest that Type III distribution may better represent the data. The findings are also consistent with predictions made by Holmes and Weller (2002) and to a certain extent those of Sarkar et al. (2014), but lower than the analysis undertaken by Lakshmanan et al. (2009) for northern India. The study also highlights that the use of a load factor of 1.5 on wind load implies lower strength design MRI's of around 260 years compared to the 700 years of ASCE 7-22.