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Identification of the building parameters that influence heating and cooling energy loads for apartment buildings in hot-humid climates

机译:识别影响湿热气候下公寓建筑供热和制冷能量负荷的建筑参数

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摘要

Identifying the building parameters that significantly impact energy performance is an important step for enabling the reduction of the heating and cooling energy loads of apartment buildings in the design stage. Implementing passive design techniques for these buildings is not a simple task in most dense cities; their energy performance usually depends on uncertainties in the local climate and many building parameters, such as window size, zone height, and features of materials. For this paper, a sensitivity analysis was performed to determine the most significant parameters for buildings in hot-humid climates by considering the design of an existing apartment building in Izmir, Turkey. The Monte Carlo method is selected for sensitivity and uncertainty analyses with the Latin hypercube sampling (LHC) technique. The results show that the sensitivity of parameters in apartment buildings varies based on the purpose of the energy loads and locations in the building, such as the ground, intermediate, and top floors. In addition, the total window area, the heat transfer coefficient (U) and the solar heat gain coefficient (SHGC) of the glazing based on the orientation have the most considerable influence on the energy performance of apartment buildings in hot-humid climates.
机译:识别对能源性能有重大影响的建筑参数是在设计阶段降低公寓建筑的供暖和制冷能耗的重要一步。在大多数人口稠密的城市中,为这些建筑物实施无源设计技术并非易事。它们的能源性能通常取决于当地气候的不确定性以及许多建筑参数,例如窗户尺寸,区域高度和材料特性。在本文中,通过考虑土耳其伊兹密尔现有公寓建筑的设计,进行了敏感性分析,以确定建筑物在炎热潮湿气候中的最重要参数。选择蒙特卡洛方法进行拉丁超立方体采样(LHC)技术的敏感性和不确定性分析。结果表明,公寓建筑物中参数的敏感度根据建筑物中的能量负荷和位置(例如地面,中层和顶层)的目的而变化。另外,基于定向的玻璃的总窗户面积,传热系数(U)和太阳热增益系数(SHGC)对湿热气候下的公寓建筑的能源性能影响最大。

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