• Title/Summary/Keyword: Reference wind speed

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Comparison of Solar Power Generation Forecasting Performance in Daejeon and Busan Based on Preprocessing Methods and Artificial Intelligence Techniques: Using Meteorological Observation and Forecast Data (전처리 방법과 인공지능 모델 차이에 따른 대전과 부산의 태양광 발전량 예측성능 비교: 기상관측자료와 예보자료를 이용하여)

  • Chae-Yeon Shim;Gyeong-Min Baek;Hyun-Su Park;Jong-Yeon Park
    • Atmosphere
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    • v.34 no.2
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    • pp.177-185
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    • 2024
  • As increasing global interest in renewable energy due to the ongoing climate crisis, there is a growing need for efficient technologies to manage such resources. This study focuses on the predictive skill of daily solar power generation using weather observation and forecast data. Meteorological data from the Korea Meteorological Administration and solar power generation data from the Korea Power Exchange were utilized for the period from January 2017 to May 2023, considering both inland (Daejeon) and coastal (Busan) regions. Temperature, wind speed, relative humidity, and precipitation were selected as relevant meteorological variables for solar power prediction. All data was preprocessed by removing their systematic components to use only their residuals and the residual of solar data were further processed with weighted adjustments for homoscedasticity. Four models, MLR (Multiple Linear Regression), RF (Random Forest), DNN (Deep Neural Network), and RNN (Recurrent Neural Network), were employed for solar power prediction and their performances were evaluated based on predicted values utilizing observed meteorological data (used as a reference), 1-day-ahead forecast data (referred to as fore1), and 2-day-ahead forecast data (fore2). DNN-based prediction model exhibits superior performance in both regions, with RNN performing the least effectively. However, MLR and RF demonstrate competitive performance comparable to DNN. The disparities in the performance of the four different models are less pronounced than anticipated, underscoring the pivotal role of fitting models using residuals. This emphasizes that the utilized preprocessing approach, specifically leveraging residuals, is poised to play a crucial role in the future of solar power generation forecasting.

Behavior Analysis and Control of a Moored Training Ship in an Exclusive Wharf (전용부두 계류중인 실습선의 선체거동 해석 및 제어에 관한 연구)

  • Cho, Ik-Soon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.2
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    • pp.139-145
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    • 2017
  • Recently, gusts, typhoon and tsunamis have been occurring more frequently around the world. In such an emergency situation, a moored vessel can be used to predict and analyze other vessel behavior, but if the mooring system is destroyed, marine casualties can occur. Therefore, it is necessary to determine quantitatively whether a vessel should be kept in the harbour or evacuate. In this study, moored ship safety in an exclusive wharf according to swell effects on motion and mooring load have been investigated using numerical simulations. The maximum tension exerted on mooring lines exceeded the Safety Working Load for intervals 12 and 15 seconds. The maximum bollard force also exceeded 35 tons (allowable force) in all evaluation cases. The surge motion criteria result for safe working conditions exceeded 3 meters more than the wave period 12 seconds with a wind speed of 25 knots. As a result, a risk rating matrix (risk category- very high risk, high risk and moderate risk) was developed with reference to major external forces such as wind force, wave height and wave periods to provide criteria for determining the control of capabilities of mooring systems to prevent accidents.

A Study on the Additional Installation of Coastal Wave Buoys in Smooth Water Areas to Prevent Marine Accidents (해양사고 예방을 위한 평수구역 내 파고부이 추가설치 검토)

  • Min-Kyoon Kang;Dong-Il Seol
    • Journal of Navigation and Port Research
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    • v.47 no.6
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    • pp.350-357
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    • 2023
  • Marine accidents frequently occur due to the unreasonable operation of ships excluded from ship departure control during marine special weather warnings within smooth water areas. Coastal wave buoys installed in smooth water areas are major reference indicators for ship departure control and can be seen as being directly connected to the safety of ships navigating smooth water areas and the coast. In this study, the location appropriateness of currently operating coastal wave buoys and additional installation in the smooth water areas were assessed by analyzing coastal marine accidents over the past 30 years (1991-2020), the main wind direction and wind speed of each major trading port, and the GICOMS ship track data in 2018. The study results showed that an additional coastal wave buoy should be installed at each of the major trading ports(Inchon Port, Pohang Port, Ulsan Port, and Busan Port) and that the location of the coastal wave buoy needs to be moved in the case of Busan Port. Based on various data analysis in this study, the suggestion for an additional installation and movement of the coastal wave buoy presented in this study is expected to contribute to improving the reliability of ship departure control and resolving safety blind spots.

Improvements for Atmospheric Motion Vectors Algorithm Using First Guess by Optical Flow Method (옵티컬 플로우 방법으로 계산된 초기 바람 추정치에 따른 대기운동벡터 알고리즘 개선 연구)

  • Oh, Yurim;Park, Hyungmin;Kim, Jae Hwan;Kim, Somyoung
    • Korean Journal of Remote Sensing
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    • v.36 no.5_1
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    • pp.763-774
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    • 2020
  • Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

Evaluation of Meteorological Elements Used for Reference Evapotranspiration Calculation of FAO Penman-Monteith Model (FAO Penman-Monteith 모형의 증발산량 산정에 이용되는 기상요소의 평가)

  • Hur, Seung-Oh;Jung, Kang-Ho;Ha, Sang-Keun;Kim, Jeong-Gyu
    • Korean Journal of Soil Science and Fertilizer
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    • v.39 no.5
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    • pp.274-279
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    • 2006
  • The exact estimation of crop evapotranspiration containing reference or potential evapotranspiration is necessary for decision of crop water requirements. This study was carried out for the evaluation and application of various meteorological elements used for the calculation of reference evapotranspiration (RET) by FAO Penman-Monteith (PM) model. Meteorological elements including temperature, net radiation, soil heat flux, albedo, relative humidity, wind speed measured by meteorological instruments are required for RET calculation by FAO PM model. The average of albedo measured for crop growing period was 0.20, ranging from 0.12 to 0.23, and was slightly lower than 0.23. Determinant coefficients by measured albedo and green grass albedo were 0.97, 0.95 and standard errors were 0.74, 0.80 respectively. Usefulness of deductive regression models was admitted. To assess an influence of soil heat flux (G) on FAO PM, RET with G=0 was compared with RETs using G at 5cm soil depth ($G_{5cm}$) and G at surface ($G_{0cm}$). As the results, RET estimated by G=0 was well agreed with RET calculated by measured G. Therefore, estimated net radiation, G=0 and albedo of green grass could be used for RET calculation by FAO PM.

Estimation of Reference Crop Evapotranspiration Using Backpropagation Neural Network Model (역전파 신경망 모델을 이용한 기준 작물 증발산량 산정)

  • Kim, Minyoung;Choi, Yonghun;O'Shaughnessy, Susan;Colaizzi, Paul;Kim, Youngjin;Jeon, Jonggil;Lee, Sangbong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.6
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    • pp.111-121
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    • 2019
  • Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

Calibration of Hargreaves Equation Coefficient for Estimating Reference Evapotranspiration in Korea (우리나라 기준증발산량 추정을 위한 Hargreaves 공식의 계수 보정)

  • Hwang, Seon-ah;Han, Kyung-hwa;Zhang, Yong-seon;Cho, Hee-rae;Ok, Jung-hun;Kim, Dong-Jin;Kim, Gi-sun;Jung, Kang-ho
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.4
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    • pp.238-249
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    • 2019
  • The evapotranspiration is estimated based on weather factors such as temperature, wind speed and humidity, and the Hargreaves equation is a simple equation for calculating evapotranspiration using temperature data. However, the Hargreaves equation tends to be underestimated in areas with wind speeds above 3 m s-1 and overestimated in areas with high relative humidity. The study was conducted to determine Hargreaves equation coefficient in 82 regions in Korea by comparing evapotranspiration determined by modified Hargreaves equation and the Penman-Monteith equation for the time period of 2008~2018. The modified Hargreaves coefficients for 50 inland areas were estimated to be 0.00173~0.00232(average 0.00196), which is similar to or lower than the default value 0.0023. On the other hand, there are 32 coastal areas, and the modified coefficients ranged from 0.00185 to 0.00303(average 0.00234). The east coastal area was estimated to be similar to or higher than the default value, while the west and south coastal areas showed large deviations by area. As results of estimating the evapotranspiration by the modified Hargreaves coefficient, root mean square error(RMSE) is reduced from 0.634~1.394(average 0.857) to 0.466~1.328(average 0.701), and Nash-Sutcliffe Coefficient(NSC) increased from -0.159~0.837(average 0.647) to -0.053~0.910(average 0.755) compared with original Hargreaves equation. Therefore, we confirmed that the Hargreaves equation can be overestimated or underestimated compared to the Penman-Monteith equation, and expected that it will be able to calculate the high accuracy evapotranspiration using the modified Hargreaves equation. This study will contribute to water resources planning, irrigation schedule, and environmental management.

The Gradient Variation of Thermal Environments on the Park Woodland Edge in Summer - A Study of Hadongsongrim and Hamyangsangrim - (여름철 공원 수림지 가장자리의 온열환경 기울기 변화 - 하동송림과 함양상림을 대상으로 -)

  • Ryu, Nam-Hyong;Lee, Chun-Seok
    • Journal of the Korean Institute of Landscape Architecture
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    • v.43 no.6
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    • pp.73-85
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    • 2015
  • This study investigated the extent and magnitude of the woodland edge effects on users' thermal environments according to distance from woodland border. A series of experiments to measure air temperature, relative humidity, wind velocity, MRT and UTCI were conducted over six days between July 31 and August 5, 2015, which corresponded with extremely hot weather, at the south-facing edge of Hadongsongrim(pure Pinus densiflora stands, tree age: $100{\pm}33yr$, tree height: $12.8{\pm}2.7m$, canopy closure: 75%, N $35^{\circ}03^{\prime}34.7^{{\prime}{\prime}}$, E $127^{\circ}44^{\prime}43.3^{{\prime}{\prime}}$, elevation 7~10m) and east-facing edge of Hamyangsangrim (Quercus serrata-Carpinus tschonoskii community, tree age: 102~125yr/58~123yr, tree height: tree layer $18.6{\pm}2.3m/subtree$ layer $5.9{\pm}3.2m/shrub$ layer $0.5{\pm}0.5m$, herbaceous layer coverage ratio 60%, canopy closure: 96%, N $35^{\circ}31^{\prime}28.1^{{\prime}{\prime}}$, E $127^{\circ}43^{\prime}09.8^{{\prime}{\prime}}$, elevation 170~180m) in rural villages of Hadong and Hamyang, Korea. The minus result value of depth means woodland's outside. The depth of edge influence(DEI) on the maximum air temperature, minimum relative humidity and wind speed at maximum air temperature time during the daytime(10:00~17:00) were detected to be $12.7{\pm}4.9$, $15.8{\pm}9.8$ and $23.8{\pm}26.2m$, respectively, in the mature evergreen conifer woodland of Hadongsongrim. These were detected to be $3.7{\pm}2.2$, $4.9{\pm}4.4$ and $2.6{\pm}7.8m$, respectively, in the deciduous broadleaf woodland of Hamyansangrim. The DEI on the maximum 10 minutes average MRT, UTCI from the three-dimensional environment absorbed by the human-biometeorological reference person during the daytime(10:00~17:00) were detected to be $7.1{\pm}1.7$ and $4.3{\pm}4.6m$, respectively, in the relatively sparse woodland of Hadongsongrim. These were detected to be $5.8{\pm}4.9$ and $3.5{\pm}4.1m$, respectively, in the dense and closed woodland of Hadongsongrim. Edge effects on the thermal environments of air temperature, relative humidity, wind speed, MRT and UTCI in the sparse woodland of Hadongsongrim were less pronounced than those recorded in densed and closed woodland of Hamyansangrim. The gradient variation was less steep for maximum 10 minutes average UTCI with at least $4.3{\pm}4.6m$(Hadongsongrim) and $3.5{\pm}4.1m$(Hamyansangrim) being required to stabilize the UTCI at mature woodlands. Therefore it is suggested that the woodlands buffer widths based on the UTCI values should be 3.5~7.6 m(Hamyansangrim) and 4.3~8.9(Hadongsongrim) m on each side of mature woodlands for users' thermal comfort environments. The woodland edge structure should be multi-layered canopies and closed edge for the buffer effect of woodland edge on woodland users' thermal comfort.

Analysis of Building Energy by the Typical Meteorological Data (표준기상데이터(부산지역) 적용에 따른 건축물에너지 분석)

  • Park, So-Hee;Yoo, Ho-Chun
    • 한국태양에너지학회:학술대회논문집
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    • 2008.11a
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    • pp.202-207
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    • 2008
  • Measures for coping with energy shortage are being sought all over the world. Following such a phenomenon, effort to use less energy in the design of buildings and equipment are being conducted. In particular, a program to evaluate the performance of a building comes into the spotlight. However. indispensable standard wether data to estimate the exact energy consumption of a building is currently unprepared. Thus, after appling standard weather data for four weather factors which were used in previous researches to Visual DOE 4.0, we compared it with the result of the existing data and evaluated them. For the monthly cooling and heating load of our target building, we used revised data for June, July, August, and September during which cooling load is applied. When not the existing data but the revised data was used, the research shows that an average of 14.9% increased in June, August, and September except for July. Also, in a case of heating load, the result by the revised data shows a reduction of an average of 11.9% from October to April during which heating load is applied. In particular, the heating loads of all months for which the revised data was used were more low than those of the existing data. In the maximum cooling and heating load according to load factors, the loads by residents and illumination for which the revised data was used were the same as those of the existing data, but the maximum cooling loads used by the two data have a difference in structures such as walls and roofs. Through the above results, the research cannot clearly grasp which weather data influences the cooling and heating load of a building. However, in the maximum loads by the change of weather data in four factors (dry-bulb temperature, web-bulb temperature, cloud amount, and wind speed) among 14 weather factors, the research shows that 5.95% in cooling load and 27.56% in heating load increased, and these results cannot be ignored. In order to make weather data for Performing energy performance evaluation for future buildings, the flow of weather data for the Present and past should be obviously grasped.

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Assessing the Performance of CMIP5 GCMs for Various Climatic Elements and Indicators over the Southeast US (다양한 기후요소와 지표에 대한 CMIP5 GCMs 모델 성능 평가 -미국 남동부 지역을 대상으로-)

  • Hwang, Syewoon
    • Journal of Korea Water Resources Association
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    • v.47 no.11
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    • pp.1039-1050
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    • 2014
  • The goal of this study is to demonstrate the diversity of model performance for various climatic elements and indicators. We evaluated the skills of the most advanced 17 General Circulation Models (GCMs) i.e., CMIP5 (Climate Model Inter-comparison project, phase 5) climate models in reproducing retrospective climatology from 1950 to 2000 over the Southeast US for the key climatic elements important in the hydrological and agricultural perspectives (i.e., precipitation, maximum and minimum temperature, and wind speed). The biases of raw CMIP5 GCMs were estimated for 16 different climatic indicators that imply mean climatology, temporal variability, extreme frequency, etc. using a grid-based observational dataset as reference. Based on the error (RMSE) and correlation (R) of GCM outputs, the error-based GCM ranks were assigned on average over the indicators. Overall, the GCMs showed much better accuracy in representing mean climatology of temperature comparing to other elements whereas few GCM showed acceptable skills for precipitation. It was also found that the model skills and ranks would be substantially different by the climatic elements, error statistics applied for evaluation, and indicators as well. This study presents significance of GCM uncertainty and the needs of considering rational strategies for climate model evaluation and selection.