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Investigating the importance of future climate typology on estimating the energy performance of buildings in the EPFL campus

机译:调查对EPFL校园中建筑物能源绩效的对未来气候类型的重要性

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Climate changes induce warmer climate with stronger and more frequent extreme events. Due to the uncertain nature of climate, accurate simulation of future conditions is impossible and a major challenge is the selection of climate data in the impact assessment. This work compares application of three climate data sets in an energy simulation of the EPFL campus: i) Regional Climate Models (RCM data), ii) statically representative RCM data, and iii) morphed data. The energy behavior of the campus is analyzed, including its future thermal behavior, as well as its dynamic hourly variation due to the climatic data. The objective of this paper is to understand and quantify the energy transition, from 2010 to 2100, by focusing on the thermal behavior of buildings, as well as their energy demand for heating and cooling. Results explain the difference between three cases, underling the important impact related to a sound selection of the weather data.
机译:气候变化促使温暖的气候变得更强大,更频繁的极端事件。由于气候的不确定性质,准确模拟未来的条件是不可能的,一项重大挑战是在影响评估中选择气候数据。这项工作比较了ePFL校园的能量模拟中三个气候数据集的应用:i)区域气候模型(RCM数据),ii)静态代表性的RCM数据和III)变形数据。分析了校园的能量行为,包括其未来的热行为,以及由于气候数据导致的动态每小时变化。本文的目的是通过专注于建筑物的热行为,从2010年到2100,以及它们对加热和冷却的能量需求,了解和量化能源转型。结果解释了三种情况之间的差异,在与天气数据的声音选择相关的重要影响。

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