Modelling urban-scale occupant behaviour, mobility, and energy in buildings: A survey
Modelling urban-scale occupant behaviour, mobility, and energy in buildings: A survey
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DOI：
10.1016/j.buildenv.2020.106964
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发表时间：
2020-06
影响因子：
7.4
通讯作者：
F. Salim;B. Dong;M. Ouf;Qi Wang;I. Pigliautile;Xuyuan Kang;T. Hong;Wenbo Wu;Yapan Liu
中科院分区：
文献类型：
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作者：
F. Salim;B. Dong;M. Ouf;Qi Wang;I. Pigliautile;Xuyuan Kang;T. Hong;Wenbo Wu;Yapan Liu
城市传感、物联网和大数据在城市中的扩散为更深入地了解城市规模的居住者行为和能源使用模式提供了前所未有的机会。这使得数据驱动的建筑和能源模型能够捕捉城市动态，特别是传统模型中通常不考虑的固有居住者和能源使用行为特征。虽然有相关的审查，没有调查城市数据用于模拟居住者的行为和能源使用在多个尺度，从建筑物到社区到城市。本文旨在通过对文献中报道的作品进行批判性总结和分析来填补这一空白。我们提出了不同来源的以居住者为中心的城市数据是有用的数据驱动的建模和分类的应用范围和最近的数据驱动的建模技术的城市行为和能源建模，沿着与传统的随机和基于模拟的方法。最后，我们提出了一套建议，为未来的方向，在数据驱动的建模居住者的行为和能源在城市规模的建筑物。
The proliferation of urban sensing, IoT, and big data in cities provides unprecedented opportunities for a deeper understanding of occupant behaviour and energy usage patterns at the urban scale. This enables data-driven building and energy models to capture the urban dynamics, specifically the intrinsic occupant and energy use behavioural profiles that are not usually considered in traditional models. Although there are related reviews, none investigated urban data for use in modelling occupant behaviour and energy use at multiple scales, from buildings to neighbourhood to city. This survey paper aims to fill this gap by providing a critical summary and analysis of the works reported in the literature. We present the different sources of occupant-centric urban data that are useful for data-driven modelling and categorise the range of applications and recent data-driven modelling techniques for urban behaviour and energy modelling, along with the traditional stochastic and simulation-based approaches. Finally, we present a set of recommendations for future directions in data-driven modelling of occupant behaviour and energy in buildings at the urban scale.