Zhu Mingya, Pan Yiqun, Wu Zejun, Huang Zhizhong, Kosonen Risto
School of Mechanical Engineering, Tongji University, Shanghai, China.
Sino-German College of Applied Sciences, Tongji University, Shanghai, China.
Build Simul. 2023;16(3):461-481. doi: 10.1007/s12273-022-0948-2. Epub 2022 Nov 12.
As an important factor in the investigation of building energy consumption, occupant behavior (OB) has been widely studied on the building level. However so far, studies of OB modelling on the district scale remain limited. Indeed, district-scale OB modelling has been facing the challenges from the scarcity of district-scale data, modelling methods, as well as simulation application. This study initiates the extrapolation of occupancy modelling methodology from building level to district scale through proposing modelling methods of inter-building movements. The proposed modelling methods utilize multiple distribution fittings and Bayesian network to upscale the event description methods from inter-zone movement events at the building level to inter-building movement events at the district level. This study provides a framework on the application of the proposed modelling methods for a university campus in the suburbs of Shanghai, taking advantages of data sensing, monitoring and survey techniques. With the collected campus-scale occupancy data, this paper defines five patterns of inter-building movement. One pattern represents the dominated inter-building movement events for one kind of students in their daily campus life. Based on the quantitative descriptions for various inter-building movement events, this study performs the stochastic simulation for the campus district, using Markov chain models. The simulation results are then validated with the campus-scale occupancy measurement data. Furthermore, the impact of inter-building movement modelling methods on building energy demand is evaluated for the library building, taking the deterministic occupancy schedules suggested by current building design standard as a baseline.
作为建筑能耗调查中的一个重要因素，居住者行为（OB）已在建筑层面得到广泛研究。然而，迄今为止，在区域尺度上对居住者行为建模的研究仍然有限。事实上，区域尺度的居住者行为建模一直面临着来自区域尺度数据稀缺、建模方法以及模拟应用等方面的挑战。本研究通过提出楼间移动的建模方法，开启了从建筑层面到区域尺度的居住情况建模方法的外推。所提出的建模方法利用多种分布拟合和贝叶斯网络，将事件描述方法从建筑层面的区域间移动事件提升到区域层面的楼间移动事件。本研究以上海郊区某大学校园为例，利用数据传感、监测和调查技术，提供了一个应用所提出建模方法的框架。通过收集校园尺度的居住数据，本文定义了五种楼间移动模式。其中一种模式代表了某类学生在日常校园生活中占主导地位的楼间移动事件。基于对各种楼间移动事件的定量描述，本研究使用马尔可夫链模型对校园区域进行了随机模拟。然后，利用校园尺度的居住测量数据对模拟结果进行了验证。此外，以当前建筑设计标准建议的确定性居住时间表为基线，评估了楼间移动建模方法对图书馆建筑能源需求的影响。
