• 제목/요약/키워드: Wind prediction

검색결과 932건 처리시간 0.026초

수치모의를 통한 미세규모 순환과 확산에 대한 예측 (Predictions of Local Circulation and Dispersion with Microscale Numerical Model)

  • 안광득;이용희;장동언;조천호
    • 한국군사과학기술학회지
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    • 제6권4호
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    • pp.147-158
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    • 2003
  • The prediction of wind field is very important fact in the radioactive and chemical warfare. In spite of advanced numerical weather prediction modelling and computing technology, the high resolution prediction of wind field is limited by the very high integration costs. In this study we coupled the mesoscale numerical model and microscale diagnostic numerical model with minimized integration costs. This coupled model has not only the ability of prediction of high resolution wind field including complex building but also microscale pollutant diffusion fields. For military operation this system can help making a practical and cost-effective decision in a battle field.

선형이론에 의한 복잡지형 내 난류 특성의 예측 (A Prediction of Turbulent Characteristics in a Complex Terrain by Linear Theory)

  • 윤정은;경남호;김성완
    • 한국태양에너지학회 논문집
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    • 제25권1호
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    • pp.79-86
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    • 2005
  • The external conditions for estimating dynamic wind loads of wind turbines, such as the turbulence, the extreme wind, the mean velocity gradients and the flow angles, are simulated over GangWon Wind Energy Test Field placed in one of the most complex terrain in Korea. Reference meteorological data has been gathered at a height of 30m from 2003 to 2004 with a ultrasonic anemometer. The absolute value of the spectral energy are simulated and the verification of this prediction has been carried out with comparing to the experimental data. The most desirable place for constructing new wind turbine are resulted as Point 2 and Point 3 due to the lower value of Turbulence Intensity and the higher value of wind resource relatively.

유체 역학 기반 도시 기류장 예측을 위한 입력 경계 바람장 특성 연구 (A Study of the Characteristics of Input Boundary Conditions for the Prediction of Urban Air Flow based on Fluid Dynamics)

  • 이태진;이순환;이화운
    • 한국환경과학회지
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    • 제25권7호
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    • pp.1017-1028
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    • 2016
  • Wind information is one of the major inputs for the prediction of urban air flow using computational fluid dynamic (CFD) models. Therefore, the numerical characteristics of the wind data formed at their mother domains should be clarified to predict the urban air flow more precisely. In this study, the formation characteristics of the wind data in the Seoul region were used as the inlet wind information for a CFD based simulation and were analyzed using numerical weather prediction models for weather research and forecasting (WRF). Because air flow over the central part of the Korean peninsula is often controlled not only by synoptic scale westerly winds but also by the westerly sea breeze induced from the Yellow Sea, the westerly wind often dominates the entire Seoul region. Although simulations of wind speed and air temperature gave results that were slightly high and low, respectively, their temporal variation patterns agreed well with the observations. In the analysis of the vertical cross section, the variation of wind speed along the western boundary of Seoul is simpler in a large domain with the highest horizontal resolution as compared to a small domain with the same resolution. A strong convergence of the sea breeze due to precise topography leads to the simplification of the wind pattern. The same tendency was shown in the average vertical profiles of the wind speed. The difference in the simulated wind pattern of two different domains is greater during the night than in the daytime because of atmospheric stability and topographically induced mesoscale forcing.

Setting the scene: CFD and symposium overview

  • Murakami, Shuzo
    • Wind and Structures
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    • 제5권2_3_4호
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    • pp.83-88
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    • 2002
  • The present situation of CWE(Computational Wind Engineering) and the papers presented to the CWE 2000 Symposium are reviewed from the following viewpoints; 1) topics treated, 2) utilization of commercial code (software), 3) incompleteness of CWE, 4) remaining research subjects, 5) prediction accuracy, 6) new fields of CWE application, etc. Firstly, new tendencies within CWE applications are indicated. Next, the over-attention being given to the application field and the lack of attention to fundamental problems, including prediction error analysis, are pointed out. Lastly, the future trends of CFD (Computational Fluid Dynamics) applications to wind engineering design are discussed.

완전 비축유동에 있는 수평축 풍력터빈의 성능예측 (Performance Prediction of the Horizontal Axis Wind Turbine in the Fully Non-Axial Flow)

  • 유능수
    • 산업기술연구
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    • 제14권
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    • pp.39-48
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    • 1994
  • Up to the present the study on the performance prediction of HAWT was perfomed mainly by assuming the axial flow. So in this paper we aimed at the fully non-axial flow of HAWT. For this purpose, we defined the wind turbine pitch angle in addition to the yaw angle to specify the arbitrary wind direction. And we adopted the Glauert method as the basic analysis method then modified this method suitably for our goal. By comparing the computational results obtained by this modified new Glaurert method with the experimental results, it was proved that our method was a very efficient method.

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SVM방법을 이용한 풍력발전기 고장 예측 및 발전수익 평가 (Fault prediction of wind turbine and Generation benefit evaluation by using the SVM method)

  • 신준현;이윤성;김성열;김진오
    • 조명전기설비학회논문지
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    • 제28권5호
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    • pp.60-67
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    • 2014
  • Wind power is one of the fastest growing renewable energy sources. The blades length and tower height of wind turbine have been growing steadily in the last 10 years in order to increase the output amount of wind power energy. The amount of wind turbine energy is increased by increasing the capacity of wind turbine, but the costs of preventive, corrective and replacement maintenance are also increased accordingly. Recently, Condition Monitoring System that can repair the fault diagnose and repair of wind turbine in the real-time. However, these system have a problem that cannot predict and diagnose of the fault. In this paper, wind turbine predict methodology is proposed by using the SVM method. In the case study, correlation analysis between wind turbine fault and external environmental factors is performed by using the SVM method.

Field measurement results of Tsing Ma suspension Bridge during Typhoon Victor

  • Xu, Y.L.;Zhu, L.D.;Wong, K.Y.;Chan, K.W.Y.
    • Structural Engineering and Mechanics
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    • 제10권6호
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    • pp.545-559
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    • 2000
  • A Wind and Structural Health Monitoring System (WASHMS) has been installed in the Tsing Ma suspension Bridge in Hong Kong with one of the objectives being the verification of analytical processes used in wind-resistant design. On 2 August 1997, Typhoon Victor just crossed over the Bridge and the WASHMS timely recorded both wind and structural response. The measurement data are analysed in this paper to obtain the mean wind speed, mean wind direction, mean wind inclination, turbulence intensity, integral scale, gust factor, wind spectrum, and the acceleration response and natural frequency of the Bridge. It is found that some features of wind structure and bridge response are difficult to be considered in the currently used analytical process for predicting buffeting response of long suspension bridges, for the Bridge is surrounded by a complex topography and the wind direction of Typhoon Victor changes during its crossing. It seems to be necessary to improve the prediction model so that a reasonable comparison can be performed between the measurement and prediction for long suspension bridges in typhoon prone regions.

한반도 바람자원의 시공간적 분포 (Spatial and temporal distribution of Wind Resources over Korea)

  • 김도우;변희룡
    • 대기
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    • 제18권3호
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    • pp.171-182
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    • 2008
  • In this study, we analyzed the spatial and temporal distribution of wind resources over Korea based on hourly observational data recorded over a period of 5 years from 457 stations belonging to Korea Meteorological Administration (KMA). The surface and 850 hPa wind data obtained from the Korea Local Analysis and Prediction System (KLAPS) and the Regional Data Assimilation and Prediction System (RDAPS) over a period of 1 year are used as supplementary data sources. Wind speed is generally high over seashores, mountains, and islands. In 62 (13.5%) stations, mean wind speeds for 5 years are greater than $3ms^{-1}$. The effects of seasonal wind, land-sea breeze, and mountain-valley winds on wind resources over Korea are evaluated as follows: First, wind is weak during summer, particularly over the Sobaek Mountains. However, over the coastal region of the Gyeongnam-province, strong southwesterly winds are observed during summer owing to monsoon currents. Second, the wind speed decreases during night-time, particularly over the west coast, where the direction of the land breeze is opposite to that of the large-scale westerlies. Third, winds are not always strong over seashores and highly elevated areas. The wind speed is weaker over the seashore of the Gyeonggi-province than over the other seashores. High wind speed has been observed only at 5 stations out of the 22 high-altitude stations. Detailed information on the wind resources conditions at the 21 stations (15 inland stations and 6 island stations) with high wind speed in Korea, such as the mean wind speed, frequency of wind speed available (WSA) for electricity generation, shape and scale parameters of Weibull distribution, constancy of wind direction, and wind power density (WPD), have also been provided. Among total stations in Korea, the best possible wind resources for electricity generation are available at Gosan in Jeju Island (mean wind speed: $7.77ms^{-1}$, WSA: 92.6%, WPD: $683.9Wm^{-2}$) and at Mt. Gudeok in Busan (mean wind speed: $5.66ms^{-1}$, WSA: 91.0%, WPD: $215.7Wm^{-2}$).

예측모델에 따른 태양광발전시스템의 하절기 모듈온도 예측 및 정확도 분석 (Prediction and Accuracy Analysis of Photovoltaic Module Temperature based on Predictive Models in Summer)

  • 이예지;김용식
    • 한국태양에너지학회 논문집
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    • 제37권1호
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    • pp.25-38
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    • 2017
  • Climate change and environmental pollution are becoming serious due to the use of fossil energy. For this reason, renewable energy systems are increasing, especially photovoltaic systems being more popular. The photovoltaic system has characteristics that are affected by ambient weather conditions such as insolation, outside temperature, wind speed. Particularly, it has been confirmed that the performance of the photovoltaic system decreases as the module temperature increases. In order to grasp the influence of the module temperature in advance, several researchers have proposed the prediction models on the module temperature. In this paper, we predicted the module temperature using the aforementioned prediction model on the basis of the weather conditions in Incheon, South Korea during July and August. The influence of weather conditions (i.e. insolation, outside temperature, and wind speed) on the accuracy of the prediction models was also evaluated using the standard statistical metrics such as RMSE, MAD, and MAPE. The results show that the prediction accuracy is reduced by 3.9 times and 1.9 times as the insolation and outside temperature increased respectively. On the other hand, the accuracy increased by 6.3 times as the wind speed increased.

Very Short-Term Wind Power Ensemble Forecasting without Numerical Weather Prediction through the Predictor Design

  • Lee, Duehee;Park, Yong-Gi;Park, Jong-Bae;Roh, Jae Hyung
    • Journal of Electrical Engineering and Technology
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    • 제12권6호
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    • pp.2177-2186
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    • 2017
  • The goal of this paper is to provide the specific forecasting steps and to explain how to design the forecasting architecture and training data sets to forecast very short-term wind power when the numerical weather prediction (NWP) is unavailable, and when the sampling periods of the wind power and training data are different. We forecast the very short-term wind power every 15 minutes starting two hours after receiving the most recent measurements up to 40 hours for a total of 38 hours, without using the NWP data but using the historical weather data. Generally, the NWP works as a predictor and can be converted to wind power forecasts through machine learning-based forecasting algorithms. Without the NWP, we can still build the predictor by shifting the historical weather data and apply the machine learning-based algorithms to the shifted weather data. In this process, the sampling intervals of the weather and wind power data are unified. To verify our approaches, we participated in the 2017 wind power forecasting competition held by the European Energy Market conference and ranked sixth. We have shown that the wind power can be accurately forecasted through the data shifting although the NWP is unavailable.