• Wind and Structures
• /
• 제36권2호
• /
• pp.121-131
• /
• 2023

Aiming at the problem that fatigue characteristics of metal roof rely on local physical tests and lacks the cyclic load sequence matching with regional climate, this paper proposed a method of constructing the fatigue load spectrum based on integration of wind load model, measured data of long-span metal roof and climate statistical data. According to the turbulence characteristics of wind, the wind load model is established from the aspects of turbulence intensity, power spectral density and wind pressure coefficient. Considering the influence of roof configuration on wind pressure distribution, the parameters are modified through fusing the measured data with least squares method to approximate the actual wind pressure load of the roof system. Furthermore, with regards to the wind climate characteristics of building location, Weibull model is adopted to analyze the regional meteorological data to obtain the probability density distribution of wind velocity used for calculating wind load, so as to establish the cyclic wind load sequence with the attributes of regional climate and building configuration. Finally, taking a workshop's metal roof as an example, the wind load spectrum is constructed according to this method, and the fatigue simulation and residual life prediction are implemented based on the experimental data. The forecasting result is lightly higher than the design standards, consistent with general principles of its conservative safety design scale, which shows that the presented method is validated for the fatigue characteristics study and health assessment of metal roof.

• 한국태양에너지학회 논문집
• /
• 제30권6호
• /
• pp.66-72
• /
• 2010

In this study, we analyzed the characteristics of wind speed and wind direction at different locations in Jeju area using past 10 years observed data and used them in our wind power forecasting model. Generally the strongest hourly wind speeds were observed during daytime(13KST~15KST) whilst the strongest monthly wind speeds were measured during January and February. The analysis with regards to the available wind speeds for power generation gave percentages of 83%, 67%, 65% and 59% of wind speeds over 4m/s for the locations Gosan, Sungsan, Jeju site and Seogwipo site, respectively. Consequently the most favorable periods for power generation in Jeju area are in the winter season and generally during daytime. The predicted wind speed from the forecast model was in average lower(0.7m/s) than the observed wind speed and the correlation coefficient was decreasing with longer prediction times(0.84 for 1h, 0.77 for 12h, 0.72 for 24h and 0.67 for 48h). For the 12hour prediction horizon prediction errors were about 22~23%, increased gradually up to 25~29% for 48 hours predictions.

• 한국항공운항학회지
• /
• 제29권4호
• /
• pp.88-95
• /
• 2021

In aviation meteorology, the low level wind shear is defined as a sudden change of head windbelow 1600 feet that can affect the departing and landing of the aircraft. Jeju International Airport is an area where low level wind shear is frequently occurred by Mt. Halla. Forecasting of such wind shear would be useful in providing early warnings to aircraft. In this study, we investigated the performance of statistical downscaling model, called Korea Meteorological Administration Post-processing (KMAP) with a 100 m resolution in forecasting wind shear by the complex terrain. The wind shear forecasts was produced by calculating the wind differences between stations aligned with the runways. Two typical wind shear cases caused by complex terrain are validated by comparing to Low Level Wind Shear Alert System (LLWAS). This has been shown to have a good performance for describing air currents caused by terrain.

• Journal of the Korean Data and Information Science Society
• /
• 제24권3호
• /
• pp.585-592
• /
• 2013

최근 신재생에너지와 대체에너지의 필요성이 증가함에 따라 환경오염과 온실효과를 초래하지 않는 풍력에너지 개발에 많은 연구와 투자가 이루어지고 있다. 풍력에너지는 무공해 에너지이며 자원양이 무한대이고 바람이 부는 곳이라면 어디에서든지 전력생산이 가능하다. 그러나 풍력에너지는 바람에 크게 의존하며 불규칙적인 특성이 있어 효율적인 풍력발전이 어렵다는 단점이 있다. 이러한 이유로 풍력발전에 있어서 정확한 풍력발전량 예측은 매우 중요한 요소이다. 본 연구에서는 이러한 풍력발전량의 효율적인 예측을 위해 군산 풍력단지의 자료를 이용해 시계열모형인 ARMA모형과 데이터 마이닝 기법 중 신경망모형을 사용하여 풍력발전량을 예측하고 비교분석 하였다. 그 결과 신경망모형 적합결과가 ARMA모형 적합결과 보다 더 좋은 예측력을 나타내었다.

• Wind and Structures
• /
• 제30권4호
• /
• pp.393-403
• /
• 2020

One of the growing concerns of the wind energy production is wind ramp events. To improve the wind ramp event forecasts, the nonlinear Kalman filter bias correction method was applied to 24-h wind speed forecasts issued from the WRF model at 70-m height in Zhangbei wind farm, Hebei Province, China for a two-year period. The Kalman filter shows the remarkable ability of improving forecast skill for real-time wind speed forecasts by decreasing RMSE by 32% from 3.26 m s_-1 to 2.21 m s_-1, reducing BIAS almost to zero, and improving correlation from 0.58 to 0.82. The bias correction improves the forecast skill especially in wind speed intervals sensitive to wind power prediction. The fact shows that the Kalman filter is especially suitable for wind power prediction. Moreover, the bias correction method performs well under abrupt weather transition. As to the overall performance for improving the forecast skill of ramp events, the Kalman filter shows noticeable improvements based on POD and TSS. The bias correction increases the POD score of up-ramps from 0.27 to 0.39 and from 0.26 to 0.38 for down-ramps. After bias correction, the TSS score is significantly promoted from 0.12 to 0.26 for up-ramps and from 0.13 to 0.25 for down-ramps.

• 전기학회논문지
• /
• 제65권6호
• /
• pp.918-922
• /
• 2016

As the number of wind farms operating has increased, the interest of the central unit commitment and dispatch for wind power has increased as well. Wind power forecast is necessary for effective power system management and operation with high wind power penetrations. This paper presents the centralized wind power forecasting method, which is a forecast to combine all wind farms in the area into one, using time series models. Also, this paper proposes a prediction model modified with wind forecast error compensation. To demonstrate the improvement of wind power forecasting accuracy, the proposed method is compared with persistence model and new reference model which are commonly used as reference in wind power forecasting using Jeju Island data. The results of case studies are presented to show the effectiveness of the proposed wind power forecasting method.

• 대한기계학회논문집B
• /
• 제39권9호
• /
• pp.735-742
• /
• 2015

본 논문에서는 국지적 기상현상의 모사가 가능하고 AWS, 기상탑, 또는 위성자료의 입력이 필요치 않은 WRF 기상수치모델을 이용하여, 풍력단지의 풍황자원 예측정확도 및 적용타당성을 비교 검증하고자 한다. 풍력단지개발 예비타당성단계에서 요구되는 풍황자원 예측을 위한 WRF 모델의 적용타당성 검증을 위해, 기상탑 풍황측정자료와 WAsP에 의한 풍황자원 예측결과와의 비교 검증을 수행하였고 제주도 북서쪽에 위치한 평대와 우도사이트를 비교 검증용 사이트로 선정하였다. 연 월평균풍속, 와이블분포, 연간발전량 및 바람장미의 예측결과가 실측자료와 비교 검증되었고 WRF 모델의 풍황해석결과는 WAsP의 결과에 비해 높은 예측 정확도를 나타내었다. 풍력단지개발 예비타당성 평가를 위한 WRF 모델의 풍황자원 예측가능성이 최종적으로 확인되었다.

• 한국대기환경학회지
• /
• 제19권3호
• /
• pp.249-261
• /
• 2003

A three-dimensional mesoscale atmospheric dispersion modeling system consisting of the Lagrangian particle dispersion model (LPDM) and the meteorological mesoscale model (MM5) was employed to simulate the transport and dispersion of non-reactive pollutant during the nuclear spill event occurred from Sep. 31 to Oct. 3, 1999 in Tokaimura city, Japan. For the comparative analysis of numerical experiment, two more sets of foreign mesoscale modeling system; NCEP (National Centers for Environmental Prediction) and DWD (Deutscher Wetter Dienst) were also applied to address the applicability of air pollution dispersion predictions. We noticed that the simulated results of horizontal wind direction and wind velocity from three meteorological modeling showed remarkably different spatial variations, mainly due to the different horizontal resolutions. How-ever, the dispersion process by LPDM was well characterized by meteorological wind fields, and the time-dependent dilution factors ($\chi$/Q) were found to be qualitatively simulated in accordance with each mesocale meteorogical wind field, suggesting that LPDM has the potential for the use of the real time control at optimization of the urban air pollution provided detailed meteorological wind fields. This paper mainly pertains to the mesoscale modeling approaches, but the results imply that the resolution of meteorological model and the implementation of the relevant scale of air quality model lead to better prediction capabilities in local or urban scale air pollution modeling.

• 한국태양에너지학회 논문집
• /
• 제37권1호
• /
• pp.25-38
• /
• 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.

• 농업과학연구
• /
• 제47권2호
• /
• pp.381-394
• /
• 2020

Accelerated soil wind erosion still remains to date to cause severe economic and environmental impacts. Revised and updated models to quantitatively evaluate wind induced soil erosion have been made for specific factors in the wind erosion equation (WEQ) framework. Because of increasing quantities of accumulated data, the WEQ, the revised wind erosion equation (RWEQ), the wind erosion prediction system (WEPS), and other soil wind erosion models have been established. These soil wind erosion models provide essential knowledge about where and when wind erosion occurs although naturally, they are less accurate than the field-scale. The WEQ was a good empirical model for comparing the effects of various management practices on potential erosion before the RWEQ and the WEPS showed more realistic estimates of erosion using easily measured local soil and climatic variables as inputs. The significant relationship between the observed and predicted transport capacity and soil loss makes the RWEQ a suitable tool for a large scale prediction of the wind erosion potential. WEPS developed to replace the empirical WEQ can calculate soil loss on a daily basis, provide capability to handle nonuniform areas, and obtain predictions for specific areas of interest. However, the challenge of precisely estimating wind erosion at a specific regional scale still remains to date.