Towards an Occupancy-Enhanced Building HVAC Control Strategy Using Wi-Fi Probe Request Information
Towards an Occupancy-Enhanced Building HVAC Control Strategy Using Wi-Fi Probe Request Information
复制标题
使用 Wi-Fi 探针实现提高占用率的建筑 HVAC 控制策略 请求信息
DOI：
10.1061/9780784480847.003
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Qian, Zhen
中科院分区：
文献类型：
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作者：
Li, Xuan;Liu, Xuesong;Qian, Zhen
在美国，2011年，建筑物的暖通空调(HVAC)系统占总能耗的近20%。为了提高暖通空调系统的效率和节约能源，研究人员致力于建立模型来优化暖通空调系统的控制进度和控制策略。这样的模型不仅可以大大减少总能耗，还可以保持舒适的室内环境。然而，作为控制模型最重要的内在因素之一，由于可扩展性、成本效益和实时一致性等占有率检测技术的困难，实时占有率统计在以往的研究中很少被应用。因此，本文的研究提出了一种利用通过Wi-Fi网络收集的经过处理的探测请求日志数据集进行占用率估计和暖通空调系统控制的方法。首先讨论了不同的暖通空调系统优化策略对职业信息的要求。此外，还对占有率检测方法进行了探讨和比较，以说明基于WiFi的方法符合暖通空调控制的要求。最后，通过一个实际案例研究了基于WiFi的占有率检测和预测方法，并提出了一个基于占有率的预测暖通空调优化的集成框架。
In the U.S, 2011, heating, ventilation, and air conditioning (HVAC) systems in buildings took nearly 20% of total energy consumption. To improve the efficiency of HVAC system and save energy, researchers have exerted great effort in developing models to optimize control schedule and strategies of HVAC systems. Such models not only can greatly reduce gross energy usage, but also maintain a comfort indoor environment. As one of the most important intrinsic factors for control models, however, real-time occupancy statistics has been rarely applied in previous studies, due to the difficulties in occupancy detection techniques including scalability, cost effectiveness and real-time consistency. Thus, the study discussed in this paper proposes an approach that utilizes processed probe request log dataset collected through Wi-Fi network for occupancy estimation and HVAC system control. The authors first discuss the requirements for the occupation information used in different optimization strategies for HVAC systems. In addition, occupancy detection approaches are explored and compared to illustrate that the WiFi-based approach fit the requirements of HVAC controls. Finally, WiFi-based occupancy detection and prediction approaches are investigated using a real-world case study, and an integrated framework for occupancy-based predictive HVAC optimization is proposed for future application.