A method for the identification and modelling of realistic domestic occupancy sequences for building energy demand simulations and peer comparison
A method for the identification and modelling of realistic domestic occupancy sequences for building energy demand simulations and peer comparison
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DOI：
10.1016/j.buildenv.2014.01.021
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发表时间：
2014-05-01
影响因子：
7.4
通讯作者：
Descamps, F.
中科院分区：
文献类型：
--
作者：
Aerts, D.;Minnen, J.;Descamps, F.
用户行为在住宅建筑的能源需求中起着关键作用，当接近零能耗住宅时，其重要性只会增加。然而，关于用户如何与其家庭互动的详细信息却很少。由于缺乏信息，用户行为往往是通过一个标准的用户模式包括在建筑性能模拟。为了获得更准确的能源需求模拟，需要用户模式，捕捉行为的广泛变化，而不会使模拟过于复杂。为此，我们开发了一个概率模型，该模型生成包括三种可能状态的现实占用序列：（1）在家和清醒，（2）睡眠或（3）缺席。本文报告的方法来构建这个占用模型的基础上，2005年比利时的时间使用调查。使用层次聚类，我们能够确定七个典型的占用模式。基于这种方法的个体占用序列的建模能够包括与建筑模拟相关的高度差异化但现实的行为，并且可以用于基于同行比较的个性化反馈。该模型的校准数据可供下载[1]。(C)2014爱思唯尔有限公司版权所有。
User behaviour plays a key role in the energy demand of residential buildings, and its importance will only increase when moving towards nearly Zero-Energy homes. However, little detailed information is available on how users interact with their homes. Due to the lack of information, user behaviour is often included in building performance simulations through one standard user pattern. To obtain more accurate energy demand simulations, user patterns are needed that capture the wide variations in behaviour without making simulations overly complicated. To this end, we developed a probabilistic model which generates realistic occupancy sequences that include three possible states: (1) at home and awake, (2) sleeping or (3) absent. This paper reports on the methodology used to construct this occupancy model based on the 2005 Belgian time-use survey. Using hierarchical clustering, we were able to identify seven typical occupancy patterns. The modelling of individual occupancy sequences based on this method enables to include highly differentiated yet realistic behaviour that is relevant to building simulations and can be used for individualised feedback based on peer comparison. The model's calibration data is available for download [1]. (C) 2014 Elsevier Ltd. All rights reserved.