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ÀúÀÚ¸í À¯È£Ãµ½Äº°ÀúÀÚ(Yoo, Ho-Chun) ; ¹Ú¼ÒÈñ(ParkSo-Hee)
¹ßÇà»ç ´ëÇѰÇÃàÇÐȸ
¼ö·Ï»çÇ× ´ëÇѰÇÃàÇÐȸ³í¹®Áý °èȹ°è, v.30 n.3 (2014-03)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(215) ÃÑÆäÀÌÁö(8)
ISSN 12269093
ÁÖÁ¦ºÐ·ù ȯ°æ¹×¼³ºñ
ÁÖÁ¦¾î Ç¥Áرâ»óµ¥ÀÌÅÍ ; Sandia ¹æ¹ý ; Pissimanis ¹æ¹ý ; IWEC ¹æ¹ý ; ISO 15927-4 ¹æ¹ý ; CIBSE TRY ¹æ¹ý ; Typical Weather Data ; Sandia Method ; Pissimanis Method ; IWEC Method ; ISO TRY Method ; CIBSE TRY Method
¿ä¾à2 This paper explored accurately and objectively typical meteorological data essential to the analysis of building energy to build typical data for the low-energy building. To do this, the paper proceeded with the following steps: selecting 5 calculation models of typical meteorological data, which are generally used by authorized institutions and many researchers at Seoul in Korea; preparing regional typical meteorological data displaying the results recorded for 20 years; making a comparative analysis of the characteristics of typical meteorological data by regional & estimating model and the study model setting the effect of building energy for business building. This paper found that there was a direct correlation between the average actual data recorded for 20 years and 5 calculation models, and there was not much difference in calculation models by assessing typical meteorological data and the significance level. In addition, through the comparison between typical meteorological data and cooling & heating load of every single year for 20 years, this paper illustrated that the dry-bulb temperature has a significant impact on energy analysis program. Such impact is considered to be a very important indicator for predicting the results of analysis through dry-bulb temperature and cooling & heating degree days.
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