• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.554-556
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• 2009

Wind classification for exact estimation of wind energy resources was carried out using numerically simulated wind data for three years. The MM5(a fifth-generation Mesoscale Model), developed at Penn State University and the National Center for Atmospheric Research (NCAR), was used to estimate the wind fields in this study. We also use a variant of the K-mean clustering to classify the wind district and define the relation between districts. Wind estimated at surface and 100 m high at Busan area is classified into the 10 and 7 classes, respectively. These discrepancies of wind districts pattern at surface and upper air meteorological data indicates the quantity of wind resources can be changed according to the level of wind data used in estimation. Therefore, the estimation of wind district classification by reasonable wind data is utilized to build the effective policy for wind energy dissemination.

• Journal of Wind Energy
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• v.14 no.3
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• pp.34-42
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• 2023

The reduction of operation and maintenance (O&M) costs is a critical factor in determining the competitiveness of wind energy. Predictive maintenance based on the estimation of remaining useful life (RUL) is a key technology to reduce logistic costs and increase the availability of wind turbines. Although a mechanical component usually has sudden changes during operation, most RUL estimation methods use the trend of a state index over the whole operation period. Therefore, overestimation of RUL causes confusion in O&M plans and reduces the effect of predictive maintenance. In this paper, two RUL estimation methods (load based and data driven) are proposed for the bearings of a wind turbine with the results of trend classification, which differentiates constant and increasing states of the state index. The proposed estimation method is applied to a bearing degradation test, which shows a conservative estimation of RUL.

• ETRI Journal
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• v.37 no.2
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• pp.283-294
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• 2015

A model that precisely forecasts how much wind power is generated is critical for making decisions on power generation and infrastructure updates. Existing studies have estimated wind power from wind speed using forecasting models such as ANFIS, SMO, k-NN, and ANN. This study applies a projected clustering technique to identify wind power patterns of wind turbines; profiles the resulting characteristics; and defines hourly and daily power patterns using wind power data collected over a year-long period. A wind power pattern prediction stage uses a time interval feature that is essential for producing representative patterns through a projected clustering technique along with the existing temperature and wind direction from the classifier input. During this stage, this feature is applied to the wind speed, which is the most significant input of a forecasting model. As the test results show, nine hourly power patterns and seven daily power patterns are produced with respect to the Korean wind turbines used in this study. As a result of forecasting the hourly and daily power patterns using the temperature, wind direction, and time interval features for the wind speed, the ANFIS and SMO models show an excellent performance.

• New & Renewable Energy
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• v.7 no.3
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• pp.83-91
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• 2011

The purpose of this study is to select appropriate location factors for wind power plant, provide detailed classification criteria, and find out appropriate sites for installing wind power plant in Gangwondo. In this study, the following 11 factors were extracted for site selection of wind power plant : wind resource, topography (valley angle, distance to the ridge), forest density, land use, preservation area, national park, Baekdu-Daegan, noise, shade, Transmission Line, and approaching roads. Each factor had relatively different level of importance so that AHP (Analytic Hierarchy Process) technique was used to calculated the weighted value per factor. For overlay analysis, classification criteria were prepared for each factor and each factor was classified into 3 grades : very appropriate, intermediate, poor. According to overlay analysis, the areas which received the highest grade (grade 5) was only in 0.16% of the total area of Gangwondo and had a tendency to exist along the mountain ridge over 600-meter elevation. Through analyzing the yearly average of wind power density, it was proved that the wind power density of areas with grade 4 or 5 had abundant wind resource over $400W/m^2$.

• Atmosphere
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• v.16 no.3
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• pp.235-246
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• 2006

Remote sensing techniques using satellites or the scanning weather radars depend mostly on the presence of clouds or precipitation, and leave the extensive regions of clear air unobserved. But wind profilers provide the most direct measurements of mesoscale vertical air motion in the troposphere, even in the context of heavy precipitation. In this paper, the precipitation events during the Changma period was classified into 4 precipitation types - stratiform, mixed stratiform/ convective, deep convective, and shallow convective. The parameters for the classification of analysis are the vertical structure of reflectivity, Doppler velocity, and spectral width measured with the wind profiler at Haenam for a three-year period (2003-2005). In addition, the synoptic fields and total amount of precipitation were analyzed using the Global Final Analyses (FNL) data and the Global Precipitation Climatology Project (GPCP) data. During the Changma period, the results show that the stratiform type was dominant under the moist-neutral atmosphere in 2003, whereas the deep convective type was under the moist unstable condition in 2004. The stratiform type was no less popular than the deep convective type among four seasons because the moist neutral layer was formed by the convergence between the upper-level jet and the low-level jet, and by the moisture transport along the western rim of the North Pacific subtropical anticyclone.

• Journal of the Korean Solar Energy Society
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• v.25 no.4
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• pp.29-35
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• 2005

Wind turbines can produce an unpolluted electricity getting energy only from the natural resource. It is one of the most economic power generating system among renewables up to now. Currently, ther are many wind turbines in operation world-wide under various external conditions. A wind turbine is composed of many machine components. So it is likely that the many accidents have been occurred in many wind turbines. In this paper, we reviewed "Wind turbine Accident data" of Caithness Windfarms Information Forum 2005. We classified this data and analyzed. The most of wind turbines in our country are foreign product. It is like that application it is possible with information which is important for wind farm operations and maintenance and for the wind turbine design and manufacturing.

• Journal of the Korean Institute of Navigation
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• v.17 no.4
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• pp.43-51
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• 1993

The purposes of this study are to make an analysis the sensible degree in Korea by using the formulas prepared by Watanabe, and to divide the climatic classification by the sensible degree in order to apply in practical life. Most data(air temperature, relative humidity, wind velocity, atmospheric pressure) are extracted from the "Climatic Table of Korea, Volume II(1961~1990)" issued by the Korea Meteorological Administration. As a result of this study, distribution patterns of the sensible degree are similar to isotherms when the wind velocity is zero, and then the sensible degrees are reduced with the increase of latitude. And western coastal and inland regions have larger values than eastern coastal regions in summer. However, the cont-rary distributions are shown in winter. When the wind velocity is not zero, distribution patterns of the sensible degree are influenced by the wind velocity. In summer, the values of central and southern inland regions are especially higher than the coastal regions, and most northern districts and some inland regions (Kangnung, Ulchin, Yongju etc.) have low values in winter. Then, the climate of Korea is divided into four patterns as follows : Yow means the sensible degree when the wind velocity is zero in winter. Yow > 3 : Jeju Island and southern coastal regions Yow = 0~3 : Most southern district and eastern coastal regions of central districts Yow = -3~0 : Most central districts and some eastern coastal regions (Hamheung, Youngheung, Won-san etc.) of northern districts Yow < -3 : Most northern districts and some inland regions(Inje, Hongcheon, Yang-pyeong etc.) of cent-ral districts.districts.

• Journal of Wind Energy
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• v.15 no.1
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• pp.11-20
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• 2024

As the generation capacity of floating offshore wind turbines increases, the wind load applied to each turbine increases. Due to such a high wind load, the capacity of transport equipment (such as tugboats or cranes) required in the transportation and installation phases must be much larger than that of previous small-capacity wind power generation systems. However, for such an important wind load prediction method, the simple formula proposed by the classification society is generally used, and prediction through wind tunnel tests or Computational Fluid Dynamics (CFD) is rarely used, especially for a concept or initial design stages. In this study, the wind load of a 10 MW class floating offshore wind turbine was predicted by a simplified formula and compared with results of wind tunnel tests. In addition, the wind load coefficients at each stage of fabrication, transportation, and installation are presented so that it can be used during a concept or initial design stages for similar floating offshore wind turbines.

• Wind and Structures
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• v.24 no.6
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• pp.657-677
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• 2017

This paper discusses some features and conditions that characterize the Zonda wind, focusing particularly on the implications for wind engineering applications. This kind of wind, typical of mountainous regions, is far from being adequately characterized for computational simulations and proper modeling in experimental facilities such as boundary layer wind tunnels. The objective of this article is to report the research works that are being developed on this kind of wind, describing the main obtained results, and also to establish some general guidelines for the proper analysis of the Zonda in the wind engineering context. A classification for the Zonda wind is indicated and different cases of structural and environmental effects are described. Available meteorological data is analyzed from the wind engineering point of view to obtain the Zonda wind gust factors, as well as basic wind speeds relevant for structural design. Some considerations and possible directions for the Zonda wind-tunnel and computational modeling are provided. Gust factor values larger than those used for open terrain were obtained, nevertheless, the basic wind speed values obtained are similar to values presented by the Argentinian Wind Code for three-second gust, principally at Mendoza airport.

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.287-295
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• 2021

This paper describes a recurrent neural network (RNN) for the fault classification of a blade pitch system of a spar-type floating wind turbine. An artificial neural network (ANN) can effectively recognize multiple faults of a system and build a training model with training data for decision-making. The ANN comprises an encoder and a decoder. The encoder uses a gated recurrent unit, which is a recurrent neural network, for dimensionality reduction of the input data. The decoder uses a multilayer perceptron (MLP) for diagnosis decision-making. To create data, we use a wind turbine simulator that enables fully coupled nonlinear time-domain numerical simulations of offshore wind turbines considering six fault types including biases and fixed outputs in pitch sensors and excessive friction, slit lock, incorrect voltage, and short circuits in actuators. The input data are time-series data collected by two sensors and two control inputs under the condition that of one fault of the six types occurs. A gated recurrent unit (GRU) that is one of the RNNs classifies the suggested faults of the blade pitch system. The performance of fault classification based on the gate recurrent unit is evaluated by a test procedure, and the results indicate that the proposed scheme works effectively. The proposed ANN shows a 1.4% improvement in its performance compared to an MLP-based approach.