• Smart Structures and Systems
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• v.19 no.1
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• pp.67-90
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• 2017

The interdisciplinary research area of small scale energy harvesting has attracted tremendous interests in the past decades, with a goal of ultimately realizing self-powered electronic systems. Among the various available ambient energy sources which can be converted into electricity, wind energy is a most promising and ubiquitous source in both outdoor and indoor environments. Significant research outcomes have been produced on small scale wind energy harvesting in the literature, mostly based on piezoelectric conversion. Especially, modeling methods of wind energy harvesting techniques plays a greatly important role in accurate performance evaluations as well as efficient parameter optimizations. The purpose of this paper is to present a guideline on the modeling methods of small-scale wind energy harvesters. The mechanisms and characteristics of different types of aeroelastic instabilities are presented first, including the vortex-induced vibration, galloping, flutter, wake galloping and turbulence-induced vibration. Next, the modeling methods are reviewed in detail, which are classified into three categories: the mathematical modeling method, the equivalent circuit modeling method, and the computational fluid dynamics (CFD) method. This paper aims to provide useful guidance to researchers from various disciplines when they want to develop and model a multi-way coupled wind piezoelectric energy harvester.

• 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.

• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.163-168
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• 2015

In order to integrate high wind generation resources into power grid, it is an essential to predict power outputs of wind generating resources. As wind farm outputs depend on natural wind resources that vary over space and time, spatial modeling based on geographic information such as latitude and longitude is needed to estimate power outputs of wind generation resources. In this paper, we introduce the basic concept of spatial modeling and present the spatial prediction model based on Kriging techniques. The empirical data, wind farm power output in Texas, is considered to verify the proposed prediction model.

• Wind and Structures
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• v.6 no.2
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• pp.91-106
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• 2003

The paper presents the results of 1:50 geometrical scale laboratory modeling of wind-induced point pressure on the roof of the Texas Tech University (TTU) test building. The nominal (prevalent at the TTU site) wind and two bounding (low and high turbulence) flows were simulated in a boundary-layer wind tunnel at Colorado State University. The results showed significant increase in the pressure peak and standard deviation with an increase in the flow turbulence. It was concluded that the roof mid-plane pressure sensitivity to the turbulence intensity was the cause of the previously reported field-laboratory mismatch of the fluctuating pressure, for wind normal and $30^{\circ}$-off normal to the building ridge. In addition, it was concluded that the cornering wind mismatch in the roof corner/edge regions could not be solely attributed to the wind-azimuth-independent discrepancy between the turbulence intensity of the approach field and laboratory flows.

• Wind and Structures
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• v.16 no.6
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• pp.629-660
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• 2013

This paper reviews the current state-of-the-art in the numerical evaluation of wind loads on buildings. Important aspects of numerical modeling including (i) turbulence modeling, (ii) inflow boundary conditions, (iii) ground surface roughness, (iv) near wall treatments, and (vi) quantification of wind loads using the techniques of computational fluid dynamics (CFD) are summarized. Relative advantages of Large Eddy Simulation (LES) over Reynolds Averaged Navier-Stokes (RANS) and hybrid RANS-LES over LES are discussed based on physical realism and ease of application for wind load evaluation. Overall LES based simulations seem suitable for wind load evaluation. A need for computational wind load validations in comparison with experimental or field data is emphasized. A comparative study among numerical and experimental wind load evaluation on buildings demonstrated generally good agreements on the mean values, but more work is imperative for accurate peak design wind load evaluations. Particularly more research is needed on transient inlet boundaries and near wall modeling related issues.

• Journal of Power Electronics
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• v.5 no.2
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• pp.83-98
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• 2005

As wind turbine technology and control has advanced over the last decade, this has led to a high penetration of wind turbines into the power system. Whether it be for a large wind turbine or an offshore wind farm with hundreds of MW power capacity, the electrical system has become more and more important in controlling the interaction between the mechanical system of the wind turbine and the main power system. The presence of power electronics in wind turbines improves their controllability with respect not only to its mechanical loads but also to its power quality. This paper presents an overview of a developed simulation platform for the modeling, design and optimization of wind turbines. The ability to simulate the dynamic behavior of wind turbines and the wind turbine grid interaction using four simulation tools (Matlab, Saber, DIgSILENT and HAWC) is investigated, improved and extended.

• 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.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.321-323
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• 2008

This study suggests a modeling of grid-connected wind turbine generation systems and performs simulation according to increase/decrease of real wind speed. MATLAB/Simulink implemented modeling of grid-connected wind turbine generation system. Terminal voltage, grid voltage, and active/reactive power shall be observed following the performance of simulation.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.3
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• pp.249-261
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• 2003

A three-dimensional mesoscale atmospheric dispersion modeling system consisting of the Lagrangian particle dispersion model (LPDM) and the meteorological mesoscale model (MM5) was employed to simulate the transport and dispersion of non-reactive pollutant during the nuclear spill event occurred from Sep. 31 to Oct. 3, 1999 in Tokaimura city, Japan. For the comparative analysis of numerical experiment, two more sets of foreign mesoscale modeling system; NCEP (National Centers for Environmental Prediction) and DWD (Deutscher Wetter Dienst) were also applied to address the applicability of air pollution dispersion predictions. We noticed that the simulated results of horizontal wind direction and wind velocity from three meteorological modeling showed remarkably different spatial variations, mainly due to the different horizontal resolutions. How-ever, the dispersion process by LPDM was well characterized by meteorological wind fields, and the time-dependent dilution factors ($\chi$/Q) were found to be qualitatively simulated in accordance with each mesocale meteorogical wind field, suggesting that LPDM has the potential for the use of the real time control at optimization of the urban air pollution provided detailed meteorological wind fields. This paper mainly pertains to the mesoscale modeling approaches, but the results imply that the resolution of meteorological model and the implementation of the relevant scale of air quality model lead to better prediction capabilities in local or urban scale air pollution modeling.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11b
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• pp.153-156
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• 2001

Maximum Power Point Tracking(MPPT) is used in wind power generation systems to maximize wind power turbin output power, irrespective of wind speed conditions and of the load electrical characteristics. In this paper we do the equivalent modeling the mechanical energy of wind power turbine according to wind speed into the synchronous generator. We analyse the equivalent modeling output part of rectifier into DC/DC converter input part theoretically. We design a control algorithm for variable voltage according to wind speed intensity and density so that load voltage of chopper is controlled steadily using the maximum power point tracking (MPPT) control method. We analyse a battery charging characteristics and a charging circuit for power storage enabling the supply of stable power to the load. We design a system and do the modeling of it analytically so that it supplies a stable power to the load by constructing a DC-AC inverter point. Also we design a charging circuit usable in actual wind power generation system of 30kW and confirm its validity.