• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• 한국환경과학회지
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• 제8권3호
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• pp.299-307
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• 1999

In order to fast predict the wind-driven current in a small bay, a convolution method in which the wind-driven current can be generated only with the local wind is developed and applied in the idealized bay and the idealized Sachon Bay. The accuracy of the convlution method is assessed through a series of the numerical experiements carried out in the jidealized bay and the idealized Sachon Bay. The optimum response function for the convolution method is obtained by minimizing the root man square (rms) difference between the current given by the numerical model and the current given by the convolution method. The north-south component of the response function shows simultaneous fluctuations in the wind and wind-driven current at marginal region while it shows "sea-saw" fluctuations (in which the wind and wind-driven current have opposite direction) at the central region in the idealized Sachon Bay. The present wind is strong enough to influence on the wind-driven current especially in the idealized Sachon Bay. The spatial average of the rms ratio defined as the ratio of the rms error to the rms speed is 0.05 in the idealized bay and 0.26 in the idealized Sachon Bay. The recover rate of kinetic energy(rrke) is 99% in the idealized bay and 94% in the idealized Sachon Bay. Thus, the predicted wind-driven current by the convolution model is in a good agreement with the computed one by the numerical model in the idealized bay and the idealized Sachon Bay.achon Bay.

• 한국환경과학회지
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• 제13권10호
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• pp.891-902
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• 2004

In order to predict air pollution and Yellow-sand dispersion precisely, it is necessary to clarify the sensitivity of meteorological field input interval. Therefore numerical experiment by atmospheric dynamic model(RAMS) and atmospheric dispersion model(PDAS) was performed for evaluating the effect of temporal and spatial resolution of meteorological data on particle dispersion. The results are as follows: 1) Base on the result of RAMS simulation, surface wind direction and speed can either synchronize upper wind or not. If surface wind and upper wind do not synchronize, precise prediction of Yellow-sand dispersion is strongly associated with upwelling process of sand of particle. 2) There is no significant discrepance in distribution of particle under usage of difference temporal resolution of meteorological information at early time of simulation, but the difference of distribution of particles become large as time goes by. 3) There is little difference between calculated particles distributions in dispersion experiments with high temporal resolution of meteorological data. On the other hand, low resolution of meteorological data occur the quantitative difference of particle density and there is strong tendency to the quantitative difference.

• Journal of Power Electronics
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• 제15권4호
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• pp.1047-1053
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• 2015

A time-domain simulation tool to predict the dynamic power output of wind turbines in an offshore wind farm was developed in this study. A wind turbine model consisting of first or second order transfer functions of various wind turbine elements was combined with the Ainslie's eddy viscosity wake model to construct the simulation tool. The wind turbine model also includes an aerodynamic model that is a look up table of power and thrust coefficients with respect to the tip speed ratio and pitch angle of the wind turbine obtained by a commercial multi-body dynamics simulation tool. The wake model includes algorithms of superposition of multiple wakes and propagation based on Taylor's frozen turbulence assumption. Torque and pitch control algorithms were implemented in the simulation tool to perform max-Cp and power regulation control of the wind turbines. The simulation tool calculates wind speeds in the two-dimensional domain of the wind farm at the hub height of the wind turbines and yields power outputs from individual wind turbines. The NREL 5MW reference wind turbine was targeted as a wind turbine to obtain parameters for the simulation. To validate the simulation tool, a Danish offshore wind farm with 80 wind turbines was modelled and used to predict the power from the wind farm. A comparison of the prediction with the measured values available in literature showed that the results from the simulation program were fairly close to the measured results in literature except when the wind turbines are congruent with the wind direction.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.33-36
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• 2007

We have persistently constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (ERS and Qscat). They are available for users as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO) data together with heat flux components. Recently, a new version data of the Qscat/SeaWinds based on improved algorithm for rain flag and high wind-speed range have been delivered, and allowed us to reconstruct gridded product with higher spatial resolution. These products are validated by comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON, NDBC and the Kuroshio Extension Observation (KEO) buoys, together with numerical weather prediction model products such as the NCEP-1 and 2. Results reveal that the new product has almost the same magnitude in mean difference as the previous version of Qscat product and much smaller than the NCEP-1 and 2. On the other hand, it is slightly larger root-mean-square (RMS) difference than the previous one and NCEPs for the comparison using the KEO buoy data. This may be due to the deficit of high wind speed data in the buoy measurement. The high resolution product, together with sea surface temperature (SST) one, is used to examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region.

• 한국항행학회논문지
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• 제22권5호
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• pp.478-484
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• 2018

본 연구는 기온, 강수량, 풍향, 풍속, 습도, 운량, 일조, 일사 등 시간별 기상 데이터를 이용하여, 일사 및 일조 그리고 태양광 발전예측을 하였다. 지도학습에서 입출력패턴은 예측에서 가장 중요한 요소이지만 인간이 직접 결정해야하기 때문에, 반복적인 실험에 의해 결정해야 한다. 본 연구는 일사 및 일조 예측을 위하여 4가지 모델의 입출력 패턴을 제안하였다. 또한, 예측된 일조 및 일사 데이터와 전라남도 영암 태양광 발전소의 발전량 데이터를 사용하여 태양광 발전량을 예측하였다. 실험결과 일조 및 일사 예측에서 모델 4가 가장 예측결과가 우수했으며, 모델 1에 비해 일조의 RMSE는 1.5배 정도 그리고 일사의 RMSE는 3배 정도 오차가 줄었다. 태양광 발전예측 실험결과 일조 및 일사와 마찬가지로 모델 4가 가장 예측결과가 좋았으며, 모델 1 보다 RMSE가 2.7배 정도 오차가 줄었다.

• 대기
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• 제27권4호
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• pp.385-398
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• 2017

Numerical weather prediction experiments were carried out by applying topographic effects to reduce or enhance the solar radiation by terrain. In this study, x and ${\kappa}({\phi}_o,\;{\theta}_o)$ are precalculated for topographic effect on high resolution numerical weather prediction (NWP) with 1 km spatial resolution, and meteorological variables are analyzed through the numerical experiments. For the numerical simulations, cases were selected in winter (CASE 1) and summer (CASE 2). In the CASE 2, topographic effect was observed on the southward surface to enhance the solar energy reaching the surface, and enhance surface temperature and temperature at 2 m. Especially, the surface temperature is changed sensitively due to the change of the solar energy on the surface, but the change of the precipitation is difficult to match of topographic effect. As a result of the verification using Korea Meteorological Administration (KMA) Automated Weather System (AWS) data on Seoul metropolitan area, the topographic effect is very weak in the winter case. In the CASE 1, the improvement of accuracy was numerically confirmed by decreasing the bias and RMSE (Root mean square error) of temperature at 2 m, wind speed at 10 m and relative humidity. However, the accuracy of rainfall prediction (Threat score (TS), BIAS, equitable threat score (ETS)) with topographic effect is decreased compared to without topographic effect. It is analyzed that the topographic effect improves the solar radiation on surface and affect the enhancements of surface temperature, 2 meter temperature, wind speed, and PBL height.

• 농업과학연구
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• 제47권4호
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• pp.845-857
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• 2020

The precise estimation of accelerated soil wind erosion that can cause severe economic and environmental impacts still has not been achieved to date. The objectives of this investigation were to verify the applicability of a Wind Erosion Prediction System (WEPS) that expressed the soil loss as mass per area for specific areas of interest on a daily basis for a single event in arable lands. To this end, we selected and evaluated the results published by Hagen in 2004 and the soil depth converted from the mass of soil losses obtained by using the WEPS. Hagen's results obtained from the WEPS model followed the 1 : 1 line between predicted and measured value for soil losses with only less than 2 kg·m-2 whereas the values between the measured and predicted loss did not show any correlation for the given field conditions due to the initial field surface condition although the model provided reasonable estimates of soil loss. Calculated soil depths of the soil loss by wind for both the observed and predicted ones ranged from 0.004 to 3.113 cm·10 a-1 and from 0 to 2.013 cm·10 a-1, respectively. Comparison of the soil depths between the observed and predicted ones did not show any good relationship, and there was no soil loss in the predicted one while slight soil loss was measured in the observed one. Therefore, varying the essential model inputs and factors related to wind speed and soil properties are needed to accurately estimate soil loss for a given field in arable land.

• 한국태양에너지학회 논문집
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• 제35권3호
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• pp.17-25
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• 2015

The main objective of this study is to predict the wind power generation at the wind farm using various wake models. Modeling of wind farm is a prerequisite for prediction of annual energy production at the wind farm. In this study, we modeled 20 MW class Seongsan wind farm which has 10 wind turbines located at the eastern part of Jeju Island. WindSim based on the computational fluid dynamics was adopted for the estimation of power generation. The power curve and thrust coefficient with meteorology file were prepared for wind farm modelling. The meteorology file was produced based on the measured data of the Korea Wind Atlas provided by Korea Institute of Energy Research. Three types of wake models such as Jensen, Larsen, and Ishihara et al. wake models were applied to investigate the wake effects. From the result, Jensen and Ishihara wake models show nearly the same value of power generation whereas the Larsen wake model shows the largest value. New positions of wind turbines are proposed to reduce the wake loss, and to increase the annual energy production of the wind farm.

• 대기
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• 제26권1호
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• pp.85-95
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• 2016

In this study, we investigated the variabilities of wind speed of 850 hPa and precipitable water over the East Asia region using the NCEP Final Analysis data from December 2001 to November 2011. A large variance of wind speed was observed in northern and eastern China during the winter period. During summer, the regions of the East China Sea, the South Sea of Japan and the East Sea show large variances in the wind speed caused by an extended North Pacific High and typhoon activities. The large variances in the wind speed in the regions are shown to be correlated with the inter-annual variability of precipitable water over the inland region of windward side of the Korean Peninsula. Based on the investigation, sensitivity tests to the domain size were performed using the WRF model version 3.6 for heavy precipitation events over the Korean Peninsula for 26 and 27 July 2011. Numerical experiments of different domain sizes were set up with 5 km horizontal and 50 levels vertical resolutions for the control and the first experimental run, and 9 km horizontal for the second experimental run. We found that the major rainfalls correspond to shortwave troughs with baroclinic structure over Northeast China and extended North Pacific High. The correlation analysis between the observation and experiments for 1-h precipitation indicated that the second experiment with the largest domain had the best performance with the correlation coefficient of 0.79 due to the synoptic-scale systems such as short-wave troughs and North Pacific High.