• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.8
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• pp.60-66
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• 2013

The wind-speeds among geographically close wind-farms have high correlations seasonally. This paper presents a novel wind-speed sampling method which sincerely reflects the correlation among wind-speeds of different wind-farms. In the proposed method, the wind-speed samples are generated through the statistical data analysis of the measured past wind-speed data and are adequate to be applied to generation adequacy assessment based on random sampling. In the proposed method, the specific probability distribution need not to be assumed and sufficiently accurate wind-speed samples can be generated based only on the measured past data. The proposed method is applied to the two wind-farm problem to show its applicability.

• International Journal of High-Rise Buildings
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• v.8 no.4
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• pp.313-324
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• 2019

This paper presents the analysis of wind speeds data measured on top of three neighboring high-rise buildings close to a beach in Xiamen city, China, during Typhoon "Usagi" 2013. Wind tunnel simulation was carried out to validate the field measurement results. Turbulence intensity, turbulence integral scale, power spectrum and cross correlation of recorded wind speed were studied in details. The low frequency trend component of the typhoon speed was also discussed. The field measurement results show turbulence intensity has strong dependence to the wind speed, upwind terrain and even the relative location to the Typhoon center. The low frequency fluctuation could severely affect the characteristics of wind. Cross correlation of the measured wind speeds on different buildings also showed some dependence on the upwind terrain roughness. After typhoon made landfall, the spatial correlation of wind speeds became weak with the coherence attenuating quickly in frequency domain.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1271-1279
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• 2013

In this paper, a study on the prediction method of basic wind speed at the construction site of long-span bridge using short-term measurements was conducted. To determine the basic wind speed in the wind resistant design for the long-span bridge away from the weather station, statistical analysis of long-term data at site is required. Wind observation mast was installed at site, and short-term measurements were gathered and the correlation analysis between the site and the station was done using regression analysis and MCP(Measure-Correlate-Predict). The long-term wind data of the site was obtained from correlation formula after topographical revision of long-term data of the station. And basic wind speed could be estimated by extreme probability distribution analysis. The research results show that the wind speed by regression analysis is predicted lower than by MCP and after this study a series of correlation analyses at several sites will show clearly the difference two methods. And also a quality control of long-term wind data is very important in estimation of wind speed.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.485-491
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• 2009

The importance of renewable energy sources has been growing at a high rate as a result of being environment friendly. In particular, wind power is one of the most successfully utilized of such sources to produce electrical energy. Because of the randomness of wind speed, the reliability impact on this highly variable energy power is important aspect that needs to be assessed. In this paper, the impact on the reliability indices of wind speed correlation between two farms is considered.

• Journal of Environmental Science International
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• v.5 no.2
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• pp.141-152
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• 1996

This study is an attempt to investigate the chemical components of precipitation and its variation according to surface wind. Precipitation samples were collected by an wet-only precipitation sampler during the period of October 1994 to September 1995 at Kyungsan in Korea. The results obtained in t체s study are summerized as follows. The annual average of precipitation pH is 5.0, the highest month of pH is July of 5.5, and the lowest month of pH is December of 4.4. The most frequent appearance is in the range of pH 5.0 to 5.5 and its rate is 56.8%, The order of ion concentration In precipitation is SO42->NO3->Cl- in case of anion and $Ca^{2+}$>$NH_4^{+}$>$Na^+$>$Mg^{2+}$ in case of cation. It is found from our analysis that the correlation coefficient among the precipitation pH and ion components is below r=0.3, while the correlation coefficient between $SO_4^{2-}$ and NO_3^{-}$, $Na^+$ and $Cl^+$ is above r=0.8, respectively. The mean pH of precipitation is 4.8 under the westerly wind and 5.2 under the easterly wind. The concentrations of anion and cation under the westerly wind are more than the concentrations under the easterly wind. In autumn, the concentration of Na+ and $Cl^+$ under the easterly wind are higher than the concentration under the westerly wind. The correlation coefficients between wind speed and pH, ion components show very low correlation of -0.41 r 0.2. But the present study show that the correlation coefficient between wind speed and pH of precipitation is positive and the correlation coefficients between wind speed and ion concentration is negative.

• Journal of Environmental Science International
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• v.11 no.7
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• pp.651-662
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• 2002

Weather elements were observed by the AWS (Automatic Weather System) and dustfall particles were collected by the modified American dust jar (wide inlet bottle type) at 4 sampling sites in Busan area from March. 1999 to February, 2000. Thirteen chemical species (Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Ni, Pb, Si, and Zn) were analyzed by AAS and ICP. The purposes of this study were to estimate qualitatively various bulk deposition flux of dustfall and insoluble components by applying regional and seasonal wind intensity. Frequency of wind speed were found in order of low(1-3m/s), very low(<1m/s), medium(3-8m/s) and high(>8m/s), and annual mean had higher range at low(1-3m/s) for 56.3%. Strong negative linear correlation were observed between dustfall and wind direction (northeastern and eastern), but strong positive linear correlation were observed between dustfall and wind direction (western and northwestern) at industrial, commercial and coastal zone(p<0.05). While a negative correlation were observed between wind speed frequency of very low(<1 m/s) and dustfall, and positive correlation were observed between wind speed frequency of low(1-3m/s) and dustfall in coastal zone(p<0.05). The correlation coefficient was observed 0.556 between wind speed frequency of low(1-3m/s) and Ni by commercial zone(p<0.05). The correlation coeffcient show well-defined insoluble trace metals (Al, Ca, Cr, Cu, Fe, Pb, and Zn) and wind speed frequency of low(1-3m/s) at coastal zone, which was found significant difference(p<0.01).

• Wind and Structures
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• v.19 no.3
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• pp.271-294
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• 2014

The impact of artefacts in archived wind observations on the design wind speed obtained by extreme value analysis is demonstrated using case studies. A signpost protocol for detecting candidate artefacts is described and its performance assessed by comparing results against previously validated data. The protocol targets artefacts by exploiting the serial correlation between observations. Additional "sieve" algorithms are proposed to identify types of correctable artefact from their "signature" in the data. In extreme value analysis, artefacts displace valid observations only when they are larger, hence always increase the design wind speed. Care must be taken not identify large valid values as artefacts, since their removal will tend to underestimate the design wind speed.

• Smart Structures and Systems
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• v.3 no.3
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• pp.341-356
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• 2007

A good understanding of normal modal variability of civil structures due to varying environmental conditions such as temperature and wind is important for reliable performance of vibration-based damage detection methods. This paper addresses the quantification of wind-induced modal variability of a cable-stayed bridge making use of one-year monitoring data. In order to discriminate the wind-induced modal variability from the temperature-induced modal variability, the one-year monitoring data are divided into two sets: the first set includes the data obtained under weak wind conditions (hourly-average wind speed less than 2 m/s) during all four seasons, and the second set includes the data obtained under both weak and strong (typhoon) wind conditions during the summer only. The measured modal frequencies and temperatures of the bridge obtained from the first set of data are used to formulate temperature-frequency correlation models by means of artificial neural network technique. Before the second set of data is utilized to quantify the wind-induced modal variability, the effect of temperature on the measured modal frequencies is first eliminated by normalizing these modal frequencies to a reference temperature with the use of the temperature-frequency correlation models. Then the wind-induced modal variability is quantitatively evaluated by correlating the normalized modal frequencies for each mode with the wind speed measurement data. It is revealed that in contrast to the dependence of modal frequencies on temperature, there is no explicit correlation between the modal frequencies and wind intensity. For most of the measured modes, the modal frequencies exhibit a slightly increasing trend with the increase of wind speed in statistical sense. The relative variation of the modal frequencies arising from wind effect (with the maximum hourly-average wind speed up to 17.6 m/s) is estimated to range from 1.61% to 7.87% for the measured 8 modes of the bridge, being notably less than the modal variability caused by temperature effect.

• Journal of environmental and Sanitary engineering
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• v.7 no.2
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• pp.141-152
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• 1992

Simple correlation analysis, factor analysis, and multi-verite analysis have been performed to analyze the relationship between air pollution and meteorological factors for air pollution and meteorological data measured at Kwanghwamun in Seoul during the period of one year (January 1990" December 1990). As a result of simple correlation and factor analysis, $SO_2$, TSP and CO concentrations have shown high negative correlation with temperature and among these indicating that these are related with pollutants emission trend based upon heating fuel usage. Ozone has a good correlation with solar radiation and relative humidity to have a closed relation with $0_3$ generation reaction mechanism. The result of multi-variate correlation analysis shows that the concentration of $SO_2$ and CO are adequate for correlation model with ambient temperature and wind speed and 0$_{3}$ concentrations are adequate for that with solar radiation and wind speed. $SO_2$ and CO levels are considered to be affected first of all by heating fuel usage as a emission source and wind speed as a dispersion effect. The $SO_2$ concentration in the condition that the temperature fall below zero is explained by multiplicative model with wind speed, only one variable.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.719-728
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• 2013

Probabilistic assessment of voltage stability margin (VSM) with existence of correlated wind speeds is investigated. Nataf transformation is adopted to establish wind speed correlation (WSC) model. Based on the saddle-node bifurcation transversality condition equations and Monte Carlo simulation technique, probability distribution of VSM is determined. With correlation coefficients range low to high value, the effect of WSC on VSM is studied. In addition, two risk indexes are proposed and the possible threat caused by WSC is evaluated from the viewpoint of risk analysis. Experimental results show that the presence of correlated wind speeds is harmful to safe and stable operation of a power system as far as voltage stability is concerned. The achievement of this paper gives a detailed elaboration about the influence of WSC on voltage stability and provides a potentially effective analytical tool for modern power system with large-scale wind power sources integration.