• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.206-213
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• 2003

The main purpose of this paper is to present a simulation model for assessing the impacts of a variable speed wind turbine (VSWT) on the distribution network and perform a simulation analysis of voltage profiles along the wind turbine installed feeder using the presented model. The modeled wind energy conversion system consists of a fixed pitch wind turbine, a synchronous generator, a rectifier and a voltage source inverter (VSI). Detailed study on the voltage impacts of a variable speed wind turbine is conducted in terms of steady state and dynamic behaviors. Various capacities and different modes of variable speed wind turbines are simulated and investigated. Case studies demonstrate how feeder voltages are influenced by capacity and control modes of wind turbines and changes in wind speed under different network conditions. Modeling and simulation analysis is based on PSCAD/EMTDC a software package.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.2021-2024
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• 2003

Information security is becoming a more important factor in distribution of digital contents. Generally, illegal facsimile of high-quality multimedia products such as DVDs, MP3s and AACs is possible without damaging quality. Thus, the illegal distribution of duplicated contents on the Web is causing digital content providers great economic loss. Therefore, a study of security and efficient distribution of digital contents is required. The most important issues in the design of a digital content distribution system are user convenience, execution speed and security. In this study, we designed a digital contents distribution system that uses web caching technology and encryption/decryption techniques in hierarchical structures. We propose a digital content distribution system that improves user convenience, security and execution speed. The superior performance of the proposed system has been proven in the tests. The results of experiment show that the developed system has improved the security of DC without decreasing process speed.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

• Wind and Structures
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• v.33 no.6
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• pp.423-435
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• 2021

Although existing algorithms can predict wind speed using historical observation data, for engineering feasibility, most use moment methods and probability density functions to estimate fitted parameters. However, extreme wind speed prediction accuracy for long-term return periods is not always dependent on how the optimized frequency distribution curves are obtained; long-term return periods emphasize general distribution effects rather than marginal distributions, which are closely related to potential extreme values. Moreover, there are different wind speed parent sample types; how to theoretically select the proper extreme value distribution is uncertain. The influence of different sampling time intervals has not been evaluated in the fitting process. To overcome these shortcomings, updated steps are introduced, involving parameter sensitivity analysis for different sampling time intervals. The extreme value prediction accuracy of unknown parent samples is also discussed. Probability analysis of mean wind is combined with estimation of the probability plot correlation coefficient and the maximum likelihood method; an iterative estimation algorithm is proposed. With the updated steps and comparison using a Monte Carlo simulation, a fitting policy suitable for different parent distributions is proposed; its feasibility is demonstrated in extreme wind speed evaluations at Longhua and Chuansha meteorological stations in Shanghai, China.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.197-205
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• 2008

In order to estimate mean wind speed in the Gwangyang-Myodo Region, the probability distribution model of extreme values has been used in the statistical analysis of joint distribution probability of daily maximum wind speed and corresponding direction in this paper. For this purpose frequency of daily maximum records at respective stations is inquired into and sample of largest yearly wind speed of sixteen compass direction and non-direction is extracted from daily data of maximum wind speed and appropriate direction of the meteorological observing stations nearby the bridge construction site. These extreme speed records are applied to Gumbel and Weibull distribution model and parameters are estimated through method of moment and method of least squares etc. And also, distribution and parameters are inquired into whether it is fitted through the probability plot correlation coefficient examination. From fitted parameters the largest yearly wind speed of sixteen compass direction and non-direction is extrapolated taking into account factors regarding sample size of data and distance from the bridge construction site according to the appropriate stations.

• 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 Korean Port Research
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• v.14 no.1
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• pp.66-75
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• 2000

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.111-121
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• 1999

From the traffic analyses, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results obtained: ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy.ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period shown 10mph decrease when compared with the 24hours' average speed, but the speed did not show a big difference in the afternoon peak period.ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge sectionⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.117-121
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• 2019

In this study, research and a demonstration for applying DC distribution systems to ships as an environmental and energy conservation solution in domestic and foreign countries were actively carried out. In order to apply a generator to a DC distribution system, a variable speed engine was used. Both engine speed and fuel consumption were reduced. In this paper, a DC generator for DC distribution was constructed using a diesel generator, a generator controller, a governor, and an AVR. A system configuration method for a generator, power quality test, and the power characteristics of a variable speed generator were analyzed. The voltage (250 - 440 VAC) and frequency (34 - 60 Hz) of the variable speed generator were set to 60 - 100 % of the rated value, and the engine was set to operate from 1100 - 1800 rpm. It was confirmed that the voltage, current, and frequency of the generator output fluctuated in a stable manner according to the power amount when changing the engine speed of the generator according to the load variation.