Analysis of Building Energy by the Typical Meteorological Data

표준기상데이터(부산지역) 적용에 따른 건축물에너지 분석

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.