• 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.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.345-347
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• 2006

In this paper, a novel method for wind speed estimation in wind power generation systems is presented. The proposed algorithm is based on estimating the wind speed using Support-Vector-Machines for regression (SVR). The wind speed is estimated using the generator power-speed characteristics as a set of training vectors. SVR is trained off-line to predict a continuos-valued function between the system's inputs and wind speed value. The predicted off-line function as well as the instantaneous generator power and speed are then used to determine the unknown winds speed on-line. The simulation results show that SVR can define the corresponding wind speed rapidly and accurately to determine the optimum generator speed reference for maximum power point tracking.

• Atmosphere
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• v.26 no.4
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• pp.617-633
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• 2016

Jangbogo station is located in Terra Nova Bay over the East Antarctica, which is often affected by individual storms moving along nearby storm tracks and a katabatic flow from the continental interior towards the coast. A numerical simulation for two strong wind events of maximum instantaneous wind speed ($41.17m\;s^{-1}$) and daily mean wind speed ($23.92m\;s^{-1}$) at Jangbogo station are conducted using the polar-optimized version of Weather Research and Forecasting model (Polar WRF). Verifying model results from 3 km grid resolution simulation against AWS observation at Jangbogo station, the case of maximum instantaneous wind speed is relatively simulated well with high skill in wind with a bias of $-3.3m\;s^{-1}$ and standard deviation of $5.4m\;s^{-1}$. The case of maximum daily mean wind speed showed comparatively lower accuracy for the simulation of wind speed with a bias of -7.0 m/s and standard deviation of $8.6m\;s^{-1}$. From the analysis, it is revealed that the each case has different origins for strong wind. The highest maximum instantaneous wind case is caused by the approach of the strong synoptic low pressure system moving toward Terra Nova Bay from North and the other daily wind maximum speed case is mainly caused by the katabatic flow from the interiors of Terra Nova Bay towards the coast. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation and investigation of high wind events at Jangbogo station. However, additional efforts in utilizing the high resolution terrain is required to reduce the simulation error of high wind mainly caused by katabatic flow, which is received a lot of influence of the surrounding terrain.

• KIEE International Transactions on Power Engineering
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• v.4A no.2
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• pp.51-57
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• 2004

This paper describes the dynamic performance of a variable speed wind turbine system responding to a wide variety of wind variations. Modeling of the wind generation using power electronics interface is proposed for dynamic simulation analysis. Component models and equations are addressed and their incorporations into a transient analysis program, PSCAD/EMTDC are provided. A wind model of four components is described, which enables observing dynamic behaviors of the wind turbine resulting from wind variations. Controllable power inverter strategies are intended for capturing the maximum power under variable speed operation and maintaining reactive power generation at a pre-determined level for constant power factor control or voltage regulation control. The components and control schemes are modeled by user-defined functions. Simulation case studies provide variable speed wind generator dynamic performance for changes in wind speed

• Architectural research
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• v.18 no.4
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• pp.137-144
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• 2016

The objective of this study was to determine the optimal angle of a wind louver that would induce the optimal wind speed for indoor. Being controlled to have an optimized angle depending on the direction from which wind is blowing and the wind speed, the wind louver to be installed on the building envelop comes to create indoor comfort through a constant wind speed using the function that reduces the indoor wind speed by changing the angle when the wind speed is not lower than a certain level and makes wind flow into the room to the maximum when the wind direction is adverse to catching the wind or the wind speed is not higher than a certain level. To determine the optimal wind louver angle, a core-centered office building with cross-ventilation problems in the climate of Seoul, Korea, which experiences four distinct seasons, was considered for analysis in this study. A module 1 office space model was used for the CFD simulation to analyze the average indoor wind speed with respect to the outdoor wind speed (varied between 1 and 8 m/s), the wind louver angle, and the outdoor wind direction (varied between $0^{\circ}$ and $180^{\circ}$ in steps of $10^{\circ}$).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.951-958
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• 2008

This paper describes development of hardware simulator for the PMSG wind power system, which was designed considering wind characteristic, blade characteristic and blade inertia compensation. The simulator consists of three major parts, such as wind turbine model using induction motor, PMSG generator, converter-inverter set. and control system. The turbine simulator generates torque and speed signals for a specific wind turbine with respect to given wind speed. This torque and speed signals are scaled down to fit the input of 2kW PMSG. The PMSG-side converter operates to track the maximum power point, and the grid-side inverter controls the active and reactive power supplied to the grid. The operational feasibility was verified by computer simulations with PSCAD/EMTDC, and the implementation feasibility was confirmed through experimental works with a hardware set-up.

• 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.

• Wind and Structures
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• v.23 no.4
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• pp.351-366
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• 2016

Nowadays, wind energy is the most rapidly developing technology and energy source and it is reusable. Due to its cleanliness and reusability, there have been rapid developments made on transferring the wind energy systems to electric energy systems. Converting the wind energy to electrical energy can be done only with the wind turbines. So installing a wind turbine depends on the wind speed at that location. The expected wind power can be estimated using a perfect probability distribution. In this paper Weibull and Weibull distribution with multiple parameters has been used in deriving the mathematical expression for estimating the wind power. Statistically the parameters of Weibull and Weibull distribution are estimated using the maximum likelihood techniques. We derive a probability distribution for the power output of a wind turbine with given rated wind speeds for the regions where the wind speed histograms present a bimodal pdf and compute the first order moment of this distribution.

• The KSFM Journal of Fluid Machinery
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• v.9 no.2 s.35
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• pp.7-12
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• 2006

This study is to develop a system of electric power generation utilizing the wind resources available in the domestic wind environment. We tested drag-type vortical wind turbine models, which have two different types of blades: a flat plate and circular arc shape. Through a performance test, conditions of maximum rotational speed were found by measuring the rpm of wind turbine. The rotational speed was measured by a tachometer in a wind tunnel and the tunnel wind speed was by using a pilot-static tube and a micro manometer. The performance test for a prototype was accomplished by calculating power, power coefficient, torque coefficient from the measurement of torque and rpm by a dynamometer controller From the measurements for miniature turbine models with two different blades, the circular arc shape was found to Produce a maximum rotational speed for the same wind velocity condition. Based on this result, the prototype with the circular arc blade was made and tested. We found that it produces 500W at the wind velocity of 10.8 m/s and the power coefficient was 20%.

• 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.