Study on Solar Radiation Models in South Korea for Improving Office Building Energy Performance Analysis

Study on Solar Radiation Models in South Korea for Improving Office Building Energy Performance Analysis
复制标题

DOI:
10.3390/su8060589
复制
发表时间:
2016-06-01
期刊:
影响因子:
3.9
通讯作者:
Jeong, WoonSeong
Jeong, WoonSeong
中科院分区:
环境科学与生态学3区
文献类型:
--
作者:
Kim, Kee Han;Oh, John Kie-Whan;Jeong, WoonSeong

文献摘要

被引文献

相似文献

天气文件中每小时的全球太阳辐射是使用模拟程序改进建筑能源性能分析的重要参数之一。然而,全球大多数气象站都没有配备太阳辐射传感器,因为它们往往难以管理。在韩国,92个气象站中只有22个配备了传感器,并且有大片区域没有配备任何传感器。因此,太阳辐射通常必须通过可靠的太阳模型来计算。因此,找到一个可以应用于韩国各种天气条件的可靠模型非常重要。在这项研究中,使用三种太阳模型计算了韩国东南部的太阳辐射:云层辐射模型(CRM)、张和黄模型(ZHM)和气象辐射模型(MRM)。然后将这些值与测量的太阳辐射数据进行比较。之后,将三个太阳模型计算出的太阳辐射数据用于具有不同窗户特性条件的办公楼的建筑能源模拟,以识别太阳辐射差异如何影响建筑能源性能。结果发现,应开发该地区的季节性太阳能模型,以改进建筑能源性能分析。
Hourly global solar radiation in a weather file is one of the significant parameters for improving building energy performance analyses using simulation programs. However, most weather stations worldwide are not equipped with solar radiation sensors because they tend to be difficult to manage. In South Korea, only twenty-two out of ninety-two weather stations are equipped with sensors, and there are large areas not equipped with any sensors. Thus, solar radiation must often be calculated by reliable solar models. Hence, it is important to find a reliable model that can be applied in the wide variety of weather conditions seen in South Korea. In this study, solar radiation in the southeastern part of South Korea was calculated using three solar models: cloud-cover radiation model (CRM), Zhang and Huang model (ZHM), and meteorological radiation model (MRM). These values were then compared to measured solar radiation data. After that, the calculated solar radiation data from the three solar models were used in a building energy simulation for an office building with various window characteristics conditions, in order to identify how solar radiation differences affect building energy performance. It was found that a seasonal solar model for the area should be developed to improve building energy performance analysis.