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Improving Energy Efficiency and Thermal Comfort of Smart Buildings with HVAC Systems in the Presence of Sensor Faults

机译:在传感器故障存在下,提高HVAC系统的智能建筑能效和热舒适性

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The smart building, as an application of the cyber-physical systems (CPSs), plays an important role in everyday lives of people. Thermal comfort and energy efficiency are primary goals for HVAC systems in smart buildings. Since the controllers of the HVACs heavily rely on data of sensors that are deployed in the buildings, temporary or permanent sensor faults may lead to increased energy consumption or decreased thermal comfort far below expectations. In this paper, we examine sensor data faults observed in the real-world sensor deployments, and their effects on thermal comfort and energy efficiency in multi-room buildings. The read-back and nearest neighbor monitoring approaches are proposed considering temporal and spatial correlations between data of sensors to mitigate the faults of interest. We adopt a model-based design methodology for the multi-room building as a CPS application and develop reusable system models in the MATLAB/Simulink environment. We conclude that the aforementioned faults may significantly reduce energy efficiency and thermal comfort unless mitigated. The proposed approaches improved thermal comfort by up to 75% for the room where the faulty sensor was deployed and reduced total energy consumption by up to 38%.
机译:智能建筑,作为网络物理系统(CPSS)的应用,在人们的日常生活中起着重要作用。热舒适度和能量效率是智能建筑中HVAC系统的主要目标。由于HVACS的控制器严重依赖于在建筑物中部署的传感器数据,因此临时或永久传感器故障可能导致能耗增加或降低远低于预期的热舒适度。在本文中,我们研究了在现实世界传感器部署中观察到的传感器数据故障,以及它们对多房屋建筑中热舒适度和能效的影响。考虑传感器数据之间的时间和空间相关性,提出了回读和最接近的邻近的监视方法来减轻感兴趣的故障。我们采用基于模型的设计方法,用于多房间建筑物作为CPS应用,并在Matlab / Simulink环境中开发可重用的系统模型。我们得出结论,除非减轻,否则上述故障可能会显着降低能量效率和热舒适度。该拟议的方法在将故障传感器部署并降低到高达38%的情况下,将热舒适度高达75%。

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