• 대기
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• 제15권3호
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• pp.179-186
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• 2005

Due to several difficulties, a number of Automatic Weather Systems (AWS) operated by Korea Meteorological Administration (KMA) are located on the rooftop so that the forming of standard observation environment to obtain the accuracy is needed. Therefore, the air temperature of AWSs on the synthetic lawn and the concrete of the rooftop is compared with the standard observation temperature. The hourly mean temperature is obtained by monthly and hourly mean value and the difference of temperature is calculated according to the location, the weather phenomenon, and cloud amount. The maximum and the minimum temperatures are compared by the conditions, such as cloud amount, the existence of precipitation or not. Consequently, the temperature on the synthetic lawn is higher than it on the concrete so that it is difficult to obtain same effect from ASOS, on the contrary the installation of AWS on the synthetic lawn seem to be inadequate due to heat or cold source of the building.

• 한국태양에너지학회 논문집
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• 제33권6호
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• pp.77-84
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• 2013

Degree-day method is very simple but essential index to estimate heating and cooling energy demand in buildings. It has been neglected, however, for the simplicity so it is difficult to find any DB for south Korean cities. Even meteorological department of S. Korea doesn't report the data officially. In this study, current methods that are being used in many countries are investigated and used to calculate degree-days of 35 south Korean cities with 30 years(1981~2010) historical data. The calculation result indicates that the error among 4 major methods are dependent on how daily or hourly temperature are treated in the calculation and how balance point temperature is defined. The errors of the methods are no larger than 6% relative to hourly degree-day method.

• 한국농림기상학회지
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• 제4권2호
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• pp.95-102
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• 2002

관측밀도가 낮고 지형이 복잡한 산악지역을 대상으로 낮 시간대 기온의 경시변화를 기존의 방법으로 내삽할 경우 일사수광량의 불균일한 분포 때문에 심각한 추정오차가 발생할 수 있다. 이를 해결하기 위해 기존의 기온감율을 고려한 거리역산가중 내삽모형에 일사수광량 보정항을 추가하고 오차경감 정도를 평가하였다. 강원도 평창군 일대 14km$\times$22km 지역을 10m 해상도의 수치고도모형으로 표현하고, 각 격자점에 대해 태양과 지표면 사이의 기하학적 관계를 바탕으로 시간대별 실제 일사 수광량을 직달, 산란, 반사 등 성분별로 계산하였다. 수평면 일사량과의 편차를 산출한 다음 이 지역에서 경험적으로 얻은 일사-기온 변환당량을 적용하여 보정값을 얻었다. 기존의 방법에 의해 내삽된 기온값에 이 보정값을 적용하여 대상지역 전역의 기온분포도를 작성하였다. 대상 지역 내 경사향이 서로 다른 8개 지점에서 기온을 측정하여 기온분포도와 비교한 결과 추정오차가 크게 줄어들었음을 확인할 수 있었다.

• ETRI Journal
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• 제37권2호
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• pp.283-294
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• 2015

A model that precisely forecasts how much wind power is generated is critical for making decisions on power generation and infrastructure updates. Existing studies have estimated wind power from wind speed using forecasting models such as ANFIS, SMO, k-NN, and ANN. This study applies a projected clustering technique to identify wind power patterns of wind turbines; profiles the resulting characteristics; and defines hourly and daily power patterns using wind power data collected over a year-long period. A wind power pattern prediction stage uses a time interval feature that is essential for producing representative patterns through a projected clustering technique along with the existing temperature and wind direction from the classifier input. During this stage, this feature is applied to the wind speed, which is the most significant input of a forecasting model. As the test results show, nine hourly power patterns and seven daily power patterns are produced with respect to the Korean wind turbines used in this study. As a result of forecasting the hourly and daily power patterns using the temperature, wind direction, and time interval features for the wind speed, the ANFIS and SMO models show an excellent performance.

• 대한건축학회논문집:구조계
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• 제34권10호
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• pp.37-44
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• 2018

In this study, the effects of considering hourly metabolic rate variations for predicted mean vote (PMV) control on the heating and cooling energy and greenhouse gas emission were investigated. The case adopting PMV control taking the hourly metabolic rate into account was comparatively analyzed against the conventional dry-bulb air temperature control, using a detailed simulation technique. Under the assumption that all the apartments in Korea adopt the PMV control incorporating real-time metabolic rate measurements, nationwide reductions of primary energy and greenhouse gas emission were analyzed. As a result, PMV control considering hourly metabolic rate variations is expected to reduce national primary energy by 6.2% compared to conventional dry-bulb air temperature control, corresponding to reduction of 10,342 GWh. In addition, it turned out that 6.6% of tCO2 emission can be reduced by adopting PMV control, corresponding to nationwide reduction of greenhouse gas emission by approximately 1,720,000 tCO2.

• 한국산학기술학회논문지
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• 제17권2호
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• pp.87-95
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• 2016

본 연구에서는 국내 도시가스 수요 데이터를 분석하여 시간대별 도시가스 수요의 특성을 파악하고 정확한 시간대별 도시가스 수요 예측을 위해 다중회귀모형(multiple regression model)을 개발하였다. 시간대별 도시가스 수요를 정확하게 예측하는 것은 공급자의 비용 절감뿐만 아니라 안정적인 배관망 관리 측면에서도 매우 중요하다. 수요 예측 오류로 인해 가스 공급이 부족한 상황이 발생하면 부족한 공급량을 빠른 시간내에 보충하기 위해 가스 배관망의 압력을 급격히 증가시켜야 하는 응급 상황이 전개될 수 있다. 반면, 시간대별 가스 생산량이 실제 수요보다 많은 경우에는 과다한 저장 시설 운용 및 불필요한 생산 비용이 발생하는 문제가 있다. 과거 시간대별 도시가스 수요 데이터를 분석한 결과 시간대별 도시 가스 수요는 직전 시간대(즉, 24시간 전) 수요와 매우 높은 상관관계를 보이며 24시간 수요 패턴은 1주일전 동일 요일(즉, 168시간전)의 24시간 수요 패턴과 매우 높은 상관관계가 있음을 확인하였다. 또한, 외기 온도가 도시가스 수요에 영향을 주는 특수한 조건을 파악하였다. 즉, 시간대별 도시가스 수요와 시간대별 외기 온도는 평균적으로 0.853의 높은 상관계수 절대값을 보여주며, 상관관계 분석시 같은 요일에 속한 데이터만 분석하면 상관계수의 절대값은 최저 0.861 및 최고 0.965까지 증가한다. 이상의 분석 결과를 바탕으로 본 연구에서는 24시간 전 수요와 168시간 전 수요를 독립변수로 고려한 다중회귀모형 및 외기 온도를 추가한 두 번째 다중회귀모형을 제안하며, 제안한 예측모형의 성능을 확인하기 위해 2009년부터 2013년까지 5년간의 시간대별 수요 예측 결과를 평가하였다. 본 연구에서 제안한 24시간 전 수요와 168시간 전 수요를 독립변수로 고려한 다중회귀모형의 경우 과거 5년간의 수요 예측 오차율의 절대값 평균(mean absolute percentage error)은 4.5% 수준이며, 외기 온도를 추가한 모형의 경우 오차율의 절대값 평균은 5.13%임을 확인하였다.

• 한국건축친환경설비학회 논문집
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• 제12권6호
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• pp.579-590
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• 2018

Anomaly detection on building energy consumption has been regarded as an effective tool to reduce energy saving on building operation and maintenance. However, it requires energy model and FDD expert for quantitative model approach or large amount of training data for qualitative/history data approach. Both method needs additional time and labors. This study propose a machine learning and data science approach to define faulty conditions on hourly building energy consumption with reducing data amount and input requirement. It suggests an application of Support Vector Data Description (SVDD) method on training normal condition of hourly building energy consumption incorporated with hourly outdoor air temperature and time integer in a week, 168 data points and identifying hourly abnormal condition in the next day. The result shows the developed model has a better performance when the ${\nu}$ (probability of error in the training set) is 0.05 and ${\gamma}$ (radius of hyper plane) 0.2. The model accuracy to identify anomaly operation ranges from 70% (10% increase anomaly) to 95% (20% decrease anomaly) for daily total (24 hours) and from 80% (10% decrease anomaly) to 10%(15% increase anomaly) for occupied hours, respectively.

• 한국태양에너지학회 논문집
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• 제32권3호
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• pp.123-128
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• 2012

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design. The purpose of our work is to predict the surface temperature on inclined surfaces based on ISO-TRY typical weather data. To reach this goal, three studies were performed. They consisted of quantifying the accuracy of various well-known three models. The first type of models calculated diffuse horizontal irradiations from global ones and the second type models computed global irradiations on inclined planes from diffuse and global components on a horizontal surface. The third type of model calculated long-wave radiation and surface temperature from ISO-TRY typical weather data. The proposed model can provide an alternative to building designers in estimating the surface temperature and solar irradiation on inclined surfaces where only the typical meteorological data are available.

• 생물환경조절학회지
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• 제23권3호
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• pp.192-198
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• 2014

To establish the design criteria for seasonal heating load calculation in greenhouses, standard weather data are required. However, they are being provided only at seven regions in Korea. So, instead of using standard weather data, in order to find the method to build design weather data for seasonal heating load calculation, heating degree-hour and heating degree-day were analyzed and compared by methods of fundamental equation, Mihara's equation and modified Mihara's equation using normal and thirty years from 1981 to 2010 hourly weather data provided by KMA and standard weather data provided by KSES. Average heating degree-hours calculated by fundamental equation using thirty years hourly weather data showed a good agreement with them using standard weather data. The 24 times of heating degree-day showed relatively big differences with heating degree-hour at the low setting temperature. Therefore, the heating degree-hour was considered more appropriate method to estimate the seasonal heating load. And to conclude, in regions which are not available standard weather data, we suggest that design weather data should be analyzed using thirty years hourly weather data. Average of heating degree-hours derived from every year hourly weather data during the whole period can be established as environmental design standards, and also minimum and maximum of them can be used as reference data for energy estimation.

• Ocean and Polar Research
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• 제31권1호
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• pp.63-70
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• 2009

Eutrophicated water fed through Mankyeong River and Dongjin River into the new Saemankeum Lakemight seriously affect the water quality and phytoplankton community in the lake. To obtain control reference data for the later studies on environmental changes due to the construction of the Saemankeum Sea Wall, we performed a monthly investigation on the physico-chemical properties of the water and phytoplankton community at 3 stations in the Mankyeong River Estuary over 14 months starting from September 1999. Water temperature ranged from $0.3{\sim}32.9^{\circ}C$ due to the typical seasonal variations in temperate on the coasts and salinity exhibited a wide annual range of $0.2{\sim}33.7$ psu along with regular and huge hourly variations according to tidal cycles. Inorganic nutrients were supplied from rivers to the monitoring station and the whole lake. The average concentration of total-N, $6.99\;mg{\cdot}l^{-1}$, was higher than the water quality for agricultural use with peak values occurring in winter. Species composition showed a seasonal succession pattern, where a high diversity was observedin summer and autumn and vice versa in winter. Hourly variations of water properties in the "Mankyeong bridge" Station were quite regular and well in accordance with the daily tidal cycles. The different degree of sea water intrusion during the flood tide at each of the 3 stations exhibited a different range and variation pattern of water temperature and salinity throughout a day. Hourly changes in species composition were in harmony with the daily tidal cycles, resulting in extremely variable spatio-temporal variation.