• Title/Summary/Keyword: Wind Speed Prediction

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Development of Wind Farm AEP Prediction Program Considering Directional Wake Effect (방향별 후류를 고려한 풍력발전단지 연간 에너지 생산량 예측 프로그램 개발 및 적용)

  • Yang, Kyoungboo;Cho, Kyungho;Huh, Jongchul
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.41 no.7
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    • pp.469-480
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    • 2017
  • For accurate AEP prediction in a wind farm, it is necessary to effectively calculate the wind speed reduction and the power loss due to the wake effect in each wind direction. In this study, a computer program for AEP prediction considering directional wake effect was developed. The results of the developed program were compared with the actual AEP of the wind farm and the calculation result of existing commercial software to confirm the accuracy of prediction. The applied equations are identical with those of commercial software based on existing theories, but there is a difference in the calculation process of the detection of the wake effect area in each wind direction. As a result, the developed program predicted to be less than 1% of difference to the actual capacity factor and showed more than 2% of better results compared with the existing commercial software.

Prediction of long-term wind speed and capacity factor using Measure-Correlate-Predict method (측정-상관-예측법을 이용한 장기간 풍속 및 설비이용률의 예측)

  • Ko, Kyung-Nam;Huh, Jong-Chul
    • Journal of the Korean Solar Energy Society
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    • v.32 no.6
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    • pp.37-43
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    • 2012
  • Long-term variations in wind speed and capacity factor(CF) on Seongsan wind farm of Jeju Island, South Korea were derived statistically. The selected areas for this study were Subji, having a year wind data at 30m above ground level, Sinsan, having 30-year wind data at 10m above ground level and Seongsan wind farm, where long-term CF was predicted. The Measure-Correlate-Predict module of WindPRO was used to predict long-tem wind characteristics at Seongsan wind farm. Eachyear's CF was derived from the estimated 30-year time series wind data by running WAsP module. As a result, for the 30-year CFs, Seongsan wind farm was estimated to have 8.3% for the coefficien to fvariation, CV, and-16.5% ~ 13.2% for the range of variation, RV. It was predicted that the annual CF at Seongsan wind farm varied within about ${\pm}4%$.

Study on the Available Power of a Wind Turbine for Wind Farm Control (풍력단지 제어를 위한 생산가능 출력에 대한 연구)

  • Oh, Yong Oon;Paek, In Su;Nam, Yoon Su;La, Yo Han
    • Journal of the Korean Solar Energy Society
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    • v.34 no.1
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    • pp.1-7
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    • 2014
  • A study on the available power of a wind turbine to be used for wind farm control was performed in this study, To accurately estimate the available power it is important to obtain a suitable wind which represents the three dimensional wind that the wind turbine rotor faces and also used to calculate the power. For this, two different models, the equivalent wind and the wind speed estimator were constructed and used for dynamic simulation using matlab simulink. From the comparison of the simulation result with that from a commercial code based on multi-body dynamics, it was found that using the hub height wind to estimate available power from a turbine results in high frequency components in the power prediction which is, in reality, filtered out by the rotor inertia. It was also found that the wind speed estimator yielded less error than the equivalent wind when compared with the result from the commercial code.

Improvement of Wave Height Mid-term Forecast for Maintenance Activities in Southwest Offshore Wind Farm (서남권 해상풍력단지 유지보수 활동을 위한 중기 파고 예보 개선)

  • Ji-Young Kim;Ho-Yeop Lee;In-Seon Suh;Da-Jeong Park;Keum-Seok Kang
    • Journal of Wind Energy
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    • v.14 no.3
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    • pp.25-33
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    • 2023
  • In order to secure the safety of increasing offshore activities such as offshore wind farm maintenance and fishing, IMPACT, a mid-term marine weather forecasting system, was established by predicting marine weather up to 7 days in advance. Forecast data from the Korea Hydrographic and Oceanographic Agency (KHOA), which provides the most reliable marine meteorological service in Korea, was used, but wind speed and wave height forecast errors increased as the leading forecast period increased, so improvement of the accuracy of the model results was needed. The Model Output Statistics (MOS) method, a post-correction method using statistical machine learning, was applied to improve the prediction accuracy of wave height, which is an important factor in forecasting the risk of marine activities. Compared with the observed data, the wave height prediction results by the model before correction for 6 to 7 days ahead showed an RMSE of 0.692 m and R of 0.591, and there was a tendency to underestimate high waves. After correction with the MOS technique, RMSE was 0.554 m and R was 0.732, confirming that accuracy was significantly improved.

ROTATING FLOW ANALYSIS AROUND A HAWT ROTOR BLADE USING RANS EQUATIONS (RANS 방정식을 이용한 HAWT 로터 블레이드의 회전 유동장 해석)

  • Kim, T.S.;Lee, C.;Son, C.H.;Joh, C.Y.
    • Journal of computational fluids engineering
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    • v.13 no.2
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    • pp.55-61
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    • 2008
  • The Reynolds-Averaged Navier-Stokes(RANS) analysis of the 3-D steady flow around the NREL Phase VI horizontal axis wind turbine(HAWT) rotor was performed. The CFD analysis results were compared with experimental data at several different wind speeds. The present CFD model shows good agreements with the experiments both at low wind speed which formed well-attache flow mostly on the upper surface of the blade, and at high wind speed which blade surface flow completely separated. However, some discrepancy occurs at the relatively high wind speeds where mixed attached and separated flow formed on the suction surface of the blade. It seems that the discrepancy is related to the onset of stall phenomena and consequently separation prediction capability of the current turbulence model. It is also found that strong span-wise flow occurs in stalled area due to the centrifugal force generated by rotation of the turbine rotor and it prevents abrupt reduction of normal force for higher wind speed than the designed value.

Assessment of Wind Energy Potentiality in Wolryong using Short-term Observation (단기관측에 의한 월령 연안지역 풍력에너지 잠재량 평가)

  • Jeong, Tae-Yoon;Lim, Hee-Chang
    • New & Renewable Energy
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    • v.5 no.4
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    • pp.11-18
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    • 2009
  • Wind energy resources are recently considered as an important power generation alternative in the future. The fact that the investment of wind turbine installation continues to increase has motivated a need to develop more widely applicable methodologies for evaluating the actual benefits of adding wind turbines to conventional generating systems. This study is aiming to estimate the future wind resources with various estimation methods. The wind power is calculated at the hub height 75m of 800KW and 1,500KW wind turbines in Wolryong site, Jeju island, South Korea. Three equations - logarithmic, profile, and power law methods are applied for the accurate prediction of wind profile. In addition, yearly wind power can be calculated by using Weibull & Rayleigh distribution. It is found that predicted wind speed is highly affected by friction velocity, atmospheric stability, and averaged roughness length. It is concluded that Rayleigh distribution provides greater power generation than the Weibull distribution, especially for low wind-speed condition.

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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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    • v.10 no.6
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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.

Sensitivity Study of the Initial Meteorological Fields on the PM10 Concentration Predictions Using CMAQ Modeling (CMAQ 모델링을 통한 초기 기상장에 대한 미세먼지 농도 예측 민감도 연구)

  • Jo, Yu-Jin;Lee, Hyo-Jung;Chang, Lim-Seok;Kim, Cheol-Hee
    • Journal of Korean Society for Atmospheric Environment
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    • v.33 no.6
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    • pp.554-569
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    • 2017
  • Sensitivity analysis on $PM_{10}$ forecasting simulations was carried out by using two different initial and boundary conditions of meteorological fields: NCEP/FNL (National Centers for Environmental Prediction/Final Analysis) reanlaysis data and NCEP/GFS (National Centers for Environmental Prediction/Global Forecast System) forecasting data, and the comparisons were made between two different simulations. The two results both yielded lower $PM_{10}$ concentrations than observations, with relatively lower biased results by NCEP/FNL than NCEP/GFS. We explored the detailed individual meteorological variables to associate with $PM_{10}$ prediction performance. With the results of NCEP/FNL outperforming GFS, our conclusion is that no particular significant bias was found in temperature fields between NCEP/FNL and NCEP/GFS data, while the overestimated wind speed by NCEP/GFS data influenced on the lower $PM_{10}$ concentrations simulation than NCEP/FNL, by decreasing the duration time of high-$PM_{10}$ loaded air mass over both coastal and metropolitan areas. These comparative characteristics of FNL against GFS data such as maximum 3~4 m/s weaker wind speed, $PM_{10}$ concentration control with the highest possible factor of 1.3~1.6, and one or two hour difference of peak time for each case in this study, were also reflected into the results of statistical analysis. It is implying that improving the surface wind speed fluctuation is an important controlling factor for the better prediction of $PM_{10}$ over Korean Peninsula.

A Proposal on Calculation Model to Predict Environmental Noise Prediction Emitted by High Speed Trains (고속철도 환경소음예측을 위한 계산 모델 제안)

  • Cho, Dae-Seung;Cho, Jun-Ho;Kim, Jin-Hyeong;Jang, Kang-Seok;Yoon, Jae-Won
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2011.10a
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    • pp.843-848
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    • 2011
  • Planning and construction of railway for high speed trains up to 400 km/h are recently driven in Korea. High speed train is one of the environment-friendly fastest mass transportation means but its noise generated by rolling, traction and aerodynamic mechanism can cause public complaints of residents nearby railways. To cost-effectively prevent the troublesome noise in a railway planning stage, the rational railway noise prediction method considering the characteristics of trains as well as railway structures should be required but it is difficult to find authentic methods for Korean high speed trains such as KTX and KTX-II. In this study, we propose a framework of our own railway noise prediction model emitted by Korean high speed trains over 250 km/h based on the recent research results carried out in EU countries. The model considers railway sound power level using several point sources distributed in heights as well as tracks, whose detail speed- and frequency-dependent emission characteristics of Korean high speed trains should be determined in near future by measurement or numerical analysis. The attenuation during propagation outdoors is calculated by the well-known ISO 9613-2 and auxiliary methods to consider undulated terrain and wind effect.

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A Study of Improvement of a Prediction Accuracy about Wind Resources based on Training Period of Bayesian Kalman Filter Technique (베이지안 칼만 필터 기법의 훈련 기간에 따른 풍력 자원 예측 정확도 향상성 연구)

  • Lee, Soon-Hwan
    • Journal of the Korean earth science society
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    • v.38 no.1
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    • pp.11-23
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    • 2017
  • The short term predictability of wind resources is an important factor in evaluating the economic feasibility of a wind power plant. As a method of improving the predictability, a Bayesian Kalman filter is applied as the model data postprocessing. At this time, a statistical training period is needed to evaluate the correlation between estimated model and observation data for several Kalman training periods. This study was quantitatively analyzes for the prediction characteristics according to different training periods. The prediction of the temperature and wind speed with 3-day short term Bayesian Kalman training at Taebaek area is more reasonable than that in applying the other training periods. In contrast, it may produce a good prediction result in Ieodo when applying the training period for more than six days. The prediction performance of a Bayesian Kalman filter is clearly improved in the case in which the Weather Research Forecast (WRF) model prediction performance is poor. On the other hand, the performance improvement of the WRF prediction is weak at the accurate point.