• 한국환경과학회지
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• 제23권1호
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• pp.25-37
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• 2014

In the present study, we analyzed precipitation patterns and diurnal variation trends of hourly precipitation intensity due to climate change. To that end, we used the hourly precipitation data obtained from 26 weather stations around South Korea, especially Busan, from 1970 to 2009. The results showed that the hourly precipitation was concentrated on a specific time of day. In particular, the results showed the so-called "morning shift" phenomenon, which is an increase in the frequency and intensity of hourly precipitation during the morning. The morning shift phenomenon was even more pronounced when a higher level of hourly precipitation intensity occurred throughout the day. Furthermore, in many regions of Korea, including Busan, this morning shift phenomenon became more prevalent as climate change progressed.

• 전기학회논문지
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• 제65권7호
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• pp.1144-1150
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• 2016

Short-term load forecasting is essential to the electricity pricing and stable power system operations. The conventional weekday 24-hour load forecasting algorithms consider the temperature model to forecast maximum load and minimum load. But 24-hour load pattern forecasting models do not consider temperature effects, because hourly temperature forecasts were not present until the latest date. Recently, 3 hour temperature forecast is announced, therefore hourly temperature forecasts can be produced by mathematical techniques such as various interpolation methods. In this paper, a new 24-hour load pattern forecasting method is proposed by using similar day search considering the hourly temperature. The proposed method searches similar day input data based on the anomalous weather features such as continuous temperature drop or rise, which can enhance 24-hour load pattern forecasting performance, because it uses the past days having similar hourly temperature features as input data. In order to verify the effectiveness of the proposed method, it was applied to the case study. The case study results show high accuracy of 24-hour load pattern forecasting.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.260-260
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• 2016

Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil loss equation (USLE) is a popular model which has been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. Value of R factor depends upon Energy (E) and maximum rainfall intensity of specific period ($I30_{max}$) of that rainfall event and thus can be calculated using higher temporal resolution rainfall data such as 10 minute interval. But 10 minute interval rainfall data may not be available in every part of the world. In that case we can use hourly rainfall data to compute this R factor. Maximum 60 minute rainfall ($I60_{max}$) can be used instead of maximum 30 minute rainfall ($I30_{max}$) as suggested by USLE manual. But the value of Average annual R factor computed using hourly rainfall data needs some correction factor so that it can be used in USLE model. The objective of our study are to derive relation between averages annual R factor values using 10 minute interval and hourly rainfall data and to determine correction coefficient for R factor using hourly Rainfall data.75 weather stations of Korea were selected for our study. Ten minute interval rainfall data for these stations were obtained from Korea Meteorological Administration (KMA) and these data were changed to hourly rainfall data. R factor and $I60_{max}$ obtained from hourly rainfall data were compared with R factor and $I30_{max}$ obtained from 10 minute interval data. Linear relation between Average annual R factor obtained from 10 minute interval rainfall and from hourly data was derived with $R^2=0.69$. Correction coefficient was developed for the R factor calculated using hourly rainfall data.. Similarly, the relation was obtained between event wise $I30_{max}$ and $I60_{max}$ with higher $R^2$ value of 0.91. Thus $I30_{max}$ can be estimated from I60max with higher accuracy and thus the hourly rainfall data can be used to determine R factor more precisely by multiplying Energy of each rainfall event with this corrected $I60_{max}$.

• 대한토목학회논문집
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• 제33권6호
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• pp.2427-2435
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• 2013

설계시간계수는 1950년대 FHWA에서 최초로 제안하였던 개념으로 1년(8,760시간) 중 상위 30번째 순위의 시간교통량을 기반으로 한다. 과거, 모든 시간대의 교통량 조사가 힘들었던 시기에 사용되었던 방식으로 다소의 문제점에도 불구하고 현재까지 사용되고 있다. 합리적인 설계를 위해서는 이론적 근거에 바탕을 둔 설계시간계수 도출이 필요하다. 본 연구는 현재까지 고수되고 있는 30번째 순위가 과연 옳은 것인가에 중점을 두고 있으며, 이를 해결하기 위해 8,760 시간교통량 순위곡선에서 변곡점을 탐색할 수 있는 기법을 제안하였다. 그리고 충청권 일반국도를 대상으로 제안 방법론을 적용하여 분석대상지점의 설계시간계수를 산정하였으며, 기존 지침의 내용과 비교하였다. 설계시간순위는 43~694순위로 일반적으로 사용되는 30순위보다 모두 하위 순위에서 발생되고 있었던바, 30순위 교통량을 사용할 경우 약간의 과다설계가 이루어 질수 있음이 확인되었다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2006년도 춘계 학술발표회 논문집
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• pp.12-19
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• 2006

Landslide model experiments considering hourly rainfall were performed to investigate and predict the run out distance induced by landslides. The model flume and the rainfall simulator were designed and produced. The model flume was designed in consideration of the landslide characteristics of Korea. The landslides in Korea were mainly occurred in the interface between soil layer and rock layer. The rainfall simulator was produced for controlling hourly rainfall ranged from 100mm/hr to 1,000mm/hr. Jumnunjin standard sand as slope soils was placed on the model flume. The model experiments were performed with changing the hourly rainfall ranged from 150mm/hr to 250mm/hr. In this experiments, the inclination of slope was 25o and the relative density of slope soils was 35%. As a result of experiments, the pore water pressure is rapidly increased at landslide occurring time, and the scale of landslide is increased with increasing in hourly rainfall. The spreading range of run out distance is occurred with pan type, and the spreading width and length are rapidly increased in its early stage and slowly increased after early stage. Also, The increasing velocity of run out distance of debris is influenced by hourly rainfall.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1251-1260
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• 2013

This paper presents the optimal scheduling of hourly consumption in a residential community (community, neighborhood, etc.) based on real-time electricity price. The residential community encompasses individual residential loads, communal (shared) loads, and local generation. Community-aggregated loads, which include residential and communal loads, are modeled as fixed, adjustable, shiftable, and storage loads. The objective of the optimal load scheduling problem is to minimize the community-aggregated electricity payment considering the convenience of individual residents and hourly community load characteristics. Limitations are included on the hourly utility load (defined as community-aggregated load minus the local generation) that is imported from the utility grid. Lagrangian relaxation (LR) is applied to decouple the utility constraint and provide tractable subproblems. The decomposed subproblems are formulated as mixed-integer programming (MIP) problems. The proposed model would be used by community master controllers to optimize the utility load schedule and minimize the community-aggregated electricity payment. Illustrative optimal load scheduling examples of a single resident as well as an aggregated community including 200 residents are presented to show the efficiency of the proposed method based on real-time electricity price.

• 한국태양에너지학회 논문집
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• 제38권1호
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• pp.1-11
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• 2018

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

• 태양에너지
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• 제12권2호
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• pp.1-8
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• 1992

본 연구는 동계 외기온 데이타의 시각별 변동특성을 파악하기 위하여 연변동 성분 및 기간변동 성분을 제거한 일변동 성분의 매 시각별 외기온 데이타에 대해서 일교차의 발생요인에 대해서 분석하였다. 또한 동계시각별 외기온의 주파수 특성에 대해서 검토하였으며 외기온 데이타의 수식화의 가능성을 제시하였다.

• 전기학회논문지
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• 제63권4호
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• pp.451-454
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• 2014

Short-term load forecasting(STLF) for electric power demand is essential for stable power system operation and efficient power market operation. We improved STLF method by using hourly temperature as an input data. In order to using hourly temperature to STLF algorithm, we calculated temperature-electric power demand sensitivity through past actual data and combined this sensitivity to exponential smoothing method which is one of the STLF method. The proposed method is verified by case study for a week. The result of case study shows that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.

• Asian-Australasian Journal of Animal Sciences
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• 제4권2호
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• pp.165-168
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• 1991

The maternal weigh-suckle-weigh (WSW) method for estimating milk production of sows was further evaluated by comparing this to the traditional WSW method. Twenty one estimates of hourly milk production were obtained by both methods. Total hourly milk production between the two methods was not significantly different (292.4 vs 303.3 g/h, p > 0.05). Hourly milk production determined by the maternal WSW method was highly correlated with hourly milk production estimates using the traditional WSW method ($R_2$ = 0.94, p < 0.001). When corrections for metabolic and salivary losses were made, the milk production figures for the maternal WSW method were approximately 27% less than those estimated by the traditional WSW method.