Energy efficient HVAC control for an IPS-enabled large space in commercial buildings through dynamic spatial occupancy distribution

Energy efficient HVAC control for an IPS-enabled large space in commercial buildings through dynamic spatial occupancy distribution
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通过动态空间占用分布实现商业建筑中IPS启用的大空间的节能HVAC控制

DOI:
10.1016/j.apenergy.2017.06.060
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发表时间:
2017-12
期刊:
影响因子:
11.2
通讯作者:
Wei Wang;Jiayu Chen;G. Huang;Yujie Lu
Wei Wang;Jiayu Chen;G. Huang;Yujie Lu
中科院分区:
工程技术1区
文献类型:
--
作者:
Wei Wang;Jiayu Chen;G. Huang;Yujie Lu

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由于商业和住宅建筑已成为各行业最大的能源消耗者,建筑节能近年来越来越受到人们的关注。许多研究表明,占用检测对于提高建筑能源效率至关重要,因为它的前提是在提供足够服务的同时避免不必要的浪费。在本文中,我们提出集成支持 iBeacon 的室内定位系统 (IPS) 和可变风量 (VAV) 供暖、通风和空调 (HVAC) 系统,以基于高分辨率占用检测来优化系统控制并节省能源。所提出的系统旨在将热服务与居住者的空间分布相匹配,并将占用率重新定义为动态空间占用分布(DSOD)占用矩阵。为此,本文提出通过将大型室内空间划分为区域和斑块来测量空间占用率,并使用特征尺度的人工神经网络算法来映射空间 IPS 信号模式。在获得详细的空间分布后,我们还开发了基于占用分布的通风控制机制。为了验证所提出的控制机制,我们通过现场实验和计算流体动力学(CFD)模拟将其与其他传统控制器进行了比较。结果表明,如果正确实施所提出的方法,可以实现 20% 的节能潜力。
Since commercial and residential buildings have become the largest energy consumers across all sectors, building energy efficiency has attracted increasing attention in recent years. Many studies suggest occupancy detection is critical in promoting building energy efficiency because it is premised on the idea of avoiding unnecessary waste while providing sufficient service. In this paper, we propose the integration of an iBeacon-enabled indoor positioning system (IPS) and a Variable Air Volume (VAV) heating, ventilation, and air-conditioning (HVAC) system to optimize system control and save energy based on high-resolution occupancy detection. The proposed system aims to match thermal service with the spatial distribution of occupants and redefine occupancy as a dynamic spatial occupancy distribution (DSOD) occupancy matrix. For this reason, this paper proposes measuring spatial occupancy by meshing large indoor spaces into zones and patches, and uses a feature-scaled artificial neural network algorithm to map the spatial IPS signal patterns. After acquiring the detailed spatial distribution, we also developed a ventilation control mechanism based on occupancy distribution. To validate the proposed control mechanism, we compared it with other traditional controllers in an on-site experiment and through a computational fluid dynamics (CFD) simulation. The results suggest that a 20% energy saving potential can be realized when the proposed approach is properly implemented.