Identification of key factors for uncertainty in the prediction of the thermal performance of an office building under climate change
Identification of key factors for uncertainty in the prediction of the thermal performance of an office building under climate change
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DOI：
10.1007/s12273-009-9116-1
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发表时间：
2009-09
影响因子：
5.5
通讯作者：
P. Wilde;W. Tian
中科院分区：
文献类型：
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作者：
P. Wilde;W. Tian
人们越来越关注气候变化对建筑物热性能的潜在影响。建筑物模拟非常适合预测未来建筑物的行为，并量化主要建筑功能的风险，如居住者生产力，居住者健康或能源使用。然而，在与气候变化有关的时间尺度上，不同的因素给预测带来了不确定性：除了气候条件预测的不确定性外，还需要考虑使用的变化、电子设备和照明的趋势以及建筑物翻新/改造和HVAC（供暖、通风和空调）系统升级等因素。本文介绍了二维蒙特卡罗分析的应用，一个EnergyPlus模型的办公楼，以确定关键因素的不确定性预测的过热和能源使用的时间跨度为2020年，2050年和2080年。该办公室采用混合模式通风和间接蒸发冷却，并使用UKCIP 02气候变化情景进行研究。结果表明，对于预测的热能的不确定性，占主导地位的输入因素是渗透，照明增益和设备增益。对于冷却能量和过热，2020年和2050年的主导因素是照明增益和设备增益，但气候预测将成为2080年的一个主导因素。这些因素将成为通过专家小组会议进一步研究的主题，这些专家小组会议将用于获得更高分辨率的关键建筑物模拟输入。
There is growing concern about the potential impact of climate change on the thermal performance of buildings. Building simulation is well-suited to predict the behaviour of buildings in the future, and to quantify the risks for prime building functions like occupant productivity, occupant health, or energy use. However, on the time scales that are involved with climate change, different factors introduce uncertainties into the predictions: apart from uncertainties in the climate conditions forecast, factors like change of use, trends in electronic equipment and lighting, as well as building refurbishment / renovation and HVAC (heating, ventilation, and air conditioning) system upgrades need to be taken into account. This article presents the application of two-dimensional Monte Carlo analysis to an EnergyPlus model of an office building to identify the key factors for uncertainty in the prediction of overheating and energy use for the time horizons of 2020, 2050 and 2080. The office has mixed-mode ventilation and indirect evaporative cooling, and is studied using the UKCIP02 climate change scenarios. The results show that regarding the uncertainty in predicted heating energy, the dominant input factors are infiltration, lighting gain and equipment gain. For cooling energy and overheating the dominant factors for 2020 and 2050 are lighting gain and equipment gain, but with climate prediction becoming the one dominant factor for 2080. These factors will be the subject of further research by means of expert panel sessions, which will be used to gain a higher resolution of critical building simulation input.