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Enhancing Non-intrusive Occupant Load Monitoring through Occupancy Matrix 利用占用矩阵加强非侵入式占用负荷监测
Pub Date : 2019-07-01 DOI: 10.18063/ieac.v2i1.1026
Hamed Nabizadeh Rafsanjani
It has been universally accepted that energy consumption in commercial buildings is highly related to occupant behaviors. Improving occupants’ energy-use behaviors is regarded as the most cost-effective approach to enhance overall energy saving in commercial built environments. However, effective behavior intervention pursuits rely on the availability of occupant-specific energy-use information, which is extremely expensive to capture with existing technologies. In this context, the author’s previous studies proposed the non-intrusive occupant load monitoring (NIOLM) approach that captures individual occupants’ energy-consuming information at their entry and departure events in an economically feasible manner. The NIOLM assigns energy-load variations (ev) of a building to individual occupants and relies on two variables: Time delay intervals and magnitudes of ev. This paper extends the existing NIOLM concept with the inclusion of a new variable, the occupancy matrix which manifests the information of present occupants at the moment of ev. An experiment has been conducted in an office space to validate the feasibility and accuracy of the proposed approach. Outcomes of this research could be a great help for studies on occupant energy-use behaviors intervention and simulation. 
人们普遍认为,商业建筑的能耗与居住者的行为密切相关。改善居住者的能源使用行为被认为是提高商业建筑环境整体节能的最具成本效益的途径。然而,有效的行为干预追求依赖于乘员特定能源使用信息的可用性,而利用现有技术获取这些信息是极其昂贵的。在此背景下,作者之前的研究提出了非侵入式乘员负荷监测(NIOLM)方法,该方法以经济可行的方式捕获每个乘员在进入和离开事件时的能耗信息。NIOLM将建筑物的能量负荷变化(ev)分配给每个居住者,并依赖于两个变量:时间延迟间隔和ev的大小。本文扩展了现有的NIOLM概念,加入了一个新的变量,即占用矩阵,它体现了当前占用者在ev时刻的信息。在一个办公空间中进行了实验,以验证所提出方法的可行性和准确性。本研究结果可为居住者能源使用行为干预与模拟研究提供参考。
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Information Engineering and Applied Computing
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