• Wind and Structures
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• v.21 no.4
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• pp.443-460
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• 2015

In this paper, an integrator based method to estimate the effective wind speed in wind turbine systems is proposed. First, the aerodynamic torque was accurately estimated through a proportional gain based observer where the generator speed is the measured output of the system. The torque signal contains not only useful frequencies of the wind, but also high frequencies and the ones due to structural vibration. The useful information of the wind signal is low frequency. A spectral analysis permitted the determination of the useful frequencies. The high frequencies were then filtered before introducing the torque signal in the wind speed observer. The desired effective wind speed was extracted through an integrator based observer using the previously estimated aerodynamic torque. The strength of the method is to avoid numerical solutions used in literature of the wind speed estimation. The effectiveness of the proposed wind speed estimator and its use to control the generator speed has been tested under turbulent situations using the FAST software (Fatigue, Aerodynamics, Structures, and Turbulence), for large scale Megawatt turbine.

• Journal of Forest and Environmental Science
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• v.32 no.2
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• pp.212-218
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• 2016

The research was conducted windward of an irrigated Acacia amplicips Maslin windbreak established to protect As Salam Cement Plant from winds and moving sands. Two belts with approximate optical porosities of 50% and 20% were studied in River Nile State, Sudan. The research aimed at assessing the efficiency of the two belts in wind speed reduction and sand deposition. Research methods included: (i) estimation of optical porosity, (ii) measurements of windward wind speeds at a control and at distances of 0.5 h (h stands for windbreak height), 1 h and 2 h at two vertical levels of 0.25 h and 0.5 h, (iii) estimation of relative wind speeds at the three positions (distance and height) at windward and (iv) estimation of wind erosive forces and prediction of zones of sand deposition. Results show that while the two belts reduced windward wind speeds at the two levels for the three distances, belt II was more effective. Nearest sand deposition occurred at 2 h and 1h windward of belt II and belt I, respectively, at level 0.25 h. At level 0.5 h, sand was deposited only at 2 h windward of belt II and no sand deposition occurred windward of belt I. The study concludes that less porous windbreaks are more effective in reducing wind speed and in depositing sand in windward direction at a distance of not less than twice the belt height.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.710-715
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• 2010

As wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is how to efficiently operate the wind turbines in a wide range of wind speeds. The wind speed has a huge impact on the dynamic response of wind turbine. For this purpose, many control algorithms are in need for a method to measure wind speed to increase performance. Unfortunately, no accurate measurement of the effective wind speed is online available from direct measurements, which means that it must be estimated in order to make such control methods applicable in practice. In this paper, a new method based on Kalman filter and artificial neural network is presented for the estimation of the effective wind speed. To verify the performance of the proposed scheme, some simulation studies are carried out.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.5
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• pp.585-595
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• 2007

Representative impacts and effectiveness of surface meteorological observation data assimilation were examined in order to use wind resources estimation around southern coastal area of the Korean Peninsula. The data used in study are observational wind and temperature data at 5 and 41 sites of Regional Meteorological Offices and Automatical Weather Systems, respectively. Observation wind speed data tends to show small effective radius with limited area. Especially assimilation impacts of data observed at peninsula type sites like Yeosu play only around the inside of the peninsula. This limited effective radius for wind speed is caused by the strong correlation between topography and wind speed. And the efficient radius for surface air temperature is larger than that of wind. Data assimilation for observational air temperature is useful to increase the accuracy of wind energy estimation. However assimilation of wind data requires special care in its application due to high sensitivity of topographical complexity.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.852-857
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• 2010

As the wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is on how to efficiently operate the wind turbines in a wide range of wind speeds. In general, the wind speed is the main factor that impact on the dynamics of wind turbine system. Wind turbine algorithms are thus required to improve the performance of wind speed measurements. However, the accurate measurement of the effective wind speed using wind gauge and similar sensors is difficult such that control systems are needed for wind speed estimation using various techniques. Therefore, this research suggests the Maximum Power Point Tracking (MPPT) method for tracking the wind speed based on neural networks. Design experiments were carried out in laboratory environment to validate the application of the proposed method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.130-139
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• 2017

The crop damage caused by strong wind was predicted using the wind speed data available from Korean Meteorological Administration (KMA). Wind speed data measured at 19 automatic weather stations in 2012 were compared with wind data available from the KMA's digital forecast. Linear regression equations were derived using the maximum value of wind speed measurements for the three-hour period prior to a given hour and the digital forecasts at the three-hour interval. Estimates of daily maximum wind speed were obtained from the regression equation finding the greatest value among the maximum wind speed at the three-hour interval. The estimation error for the daily maximum wind speed was expressed using normal distribution and Weibull distribution probability density function. The daily maximum wind speed was compared with the critical wind speed that could cause crop damage to determine the level of stages for wind damage, e.g., "watch" or "warning." Spatial interpolation of the regression coefficient for the maximum wind speed, the standard deviation of the estimation error at the automated weather stations, the parameters of Weibull distribution was performed. These interpolated values at the four synoptic weather stations including Suncheon, Namwon, Imsil, and Jangsu were used to estimate the daily maximum wind speed in 2012. The wind damage risk was determined using the critical wind speed of 10m/s under the assumption that the fruit of a pear variety Mansamgil would begin to drop at 10 m/s. The results indicated that the Weibull distribution was more effective than the normal distribution for the estimation error probability distribution for assessing wind damage risk.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.859-866
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• 2009

The article discusses an issue of estimating the airspeed of an autonomous flying vehicle. Airspeed is the difference between ground speed and wind speed. It is desirable to know any two among the three speeds for navigation, guidance and control of an autonomous vehicle. For example, ground speed and position are used to guide a vehicle to a target point and wind speed and airspeed are used to maximize flight performance such as a gliding range. However, the target vehicle has not an airspeed sensor but a ground speed sensor (GPS/INS). So airspeed or wind speed has to be estimated. Here, airspeed is to be estimated. A vehicle's dynamics and its dynamic parameters are used to estimate airspeed with attitude and angular speed measurements. Kalman filter is used for the estimation. There are also two major sources arousing a robust estimation problem; wind speed and altitude. Wind speed and direction depend on weather conditions. Altitude changes as a vehicle glides down to the ground. For one reference altitude, multiple model Kalman filters are pre-designed based on several reference airspeeds. We call this group of filters as a cluster. Filters of a cluster are activated simultaneously and probabilities are calculated for each filter. The probability indicates how much a filter matches with measurements. The final airspeed estimate is calculated by summing all estimates multiplied by probabilities. As a vehicle glides down to the ground, other clusters that have been designed based on other reference altitudes are activated. Some numerical simulations verify that the proposed method is effective to estimate airspeed.

• Wind and Structures
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• v.31 no.4
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• pp.299-309
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• 2020

In this study, wind data such as speeds, loads and potential of Muğla which is located in the southwest of Turkey were statistically analyzed. The wind data which consists of hourly wind speed between 2010 and 2013 years, was measured at the 10-meters height in four different ground stations (Datça, Fethiye, Marmaris, Köyceğiz). These stations are operated by The Turkish State Meteorological Service (T.S.M.S). Furthermore, wind data was analyzed by using Log-Normal and Gamma distributions, since these distributions fit better than Weibull, Normal, Exponential and Logistic distributions. Root Mean Squared Error (RMSE) and the coefficients of the goodness of fit (R²) were also determined by using statistical analysis. According to the results, extreme wind speed in the research area was 33 m/s at the Datça station. The effective wind load at this speed is 0.68 kN/㎡. The highest mean power densities for Datça, Fethiye, Marmaris and Köyceğiz were found to be 46.2, 1.6, 6.5 and 2.2 W/㎡, respectively. Also, although Log-normal distribution exhibited a good performance i.e., lower AD (Anderson - Darling statistic (AD) values) values, Gamma distribution was found more suitable in the estimation of wind speed and power of the region.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1098_1099
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• 2009

In this paper, we present the estimation of wind turbine power generation using Cascade Architectures of Fuzzy Neural Networks(CAFNN). The proposed model uses the wind speed average, the standard deviation and the past output power as input data. The CAFNN identification process uses a 10-min average wind speed with its standard deviation. The method for rule-based fuzzy modeling uses Gaussian membership function. It has three fuzzy variables with three modifiable parameters. The CAFNN's configuration has three Logic Processors(LP) that are constructed cascade architecture and an effective optimization method uses two-level genetic algorithm. First, The CAFNN is trained with one-day average input variables. Once the CAFNN has been trained, test data are used without any update. The main advantage of using CAFNN is having simple structure of system with many input variables. Therefore, The proposed CAFNN technique is useful to predict the wind turbine(WT) power effectively and hence that information will be helpful to decide the control strategy for the WT system operation and application.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.3
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• pp.65-78
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• 2013

To analyze influences under open fault conditions in switching devices, an integrated simulation and condition monitoring scheme for a permanent magnet synchronous generator (PMSG) based variable speed grid-connected wind turbine system are presented. Among various faults in power electronics components, the open fault in switching devices may arise when the switches are destructed by an accidental over current, or a fuse for short protection is blown out. Under such a faulty condition, the grid-side inverter as well as the generator-side converter does not operate normally, producing an increase of current harmonics, and a reduction in output and efficiency. As an effective way for a condition monitoring of generation system by online basis without requiring any diagnostic apparatus, the estimation schemes for generated voltage, flux linkage, and stator resistance are proposed and the validity of the proposed scheme is proved through comparative simulations.