Technological advancements, such as smart appliances, have enabled residential buildings to become a true Cyber-Physical System (CPS), where the devices correspond to the physical system and the smart computation and control mechanisms define the cyber part. An important aspect of these residential cyber-physical systems is their large portion of the overall energy consumption in the electric grid. Researchers have proposed several methods to address the issue, targeting to reduce both the consumption and the cost associated with it, either individually or simultaneously. These methods include using renewable energy sources, energy storage devices, efficient control methods to maximize the benefits of these resources, and smart appliance rescheduling. However, a residential CPS, different than a common CPS, has a lot of direct human interaction within the system. Although the previous residential energy management methods are effective, they do not consider the inherent and dominant human factor. This paper develops a human-behavior-centric smart appliance rescheduling method for a residential neighborhood. We first show an accurate representation of the relationship between the activities of the household members and the power demand of the house. We use this model to efficiently generate several power profiles based on different household characteristics. Then, we formally model how flexible users are when rescheduling appliances. In contrast to previous studies, our work is able to capture the intrinsic human behavior related decisions and actions when automating the residential energy consumption. Our results show 16 percent energy savings and 22 percent reduction in peak power relative to the case without appliance rescheduling while accurately representing and meeting human-related constraints. We also demonstrate that ignoring human preferences can lead to up to more than 90 percent violation of user deadlines.

中文翻译：

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住宅网络物理系统中的人类行为感知能源管理

智能电器等技术进步使住宅建筑成为真正的网络物理系统 (CPS)，其中设备对应于物理系统，智能计算和控制机制定义了网络部分。这些住宅网络物理系统的一个重要方面是它们在电网总能耗中的很大一部分。研究人员提出了几种方法来解决这个问题，旨在单独或同时减少消耗和与之相关的成本。这些方法包括使用可再生能源、储能设备、有效控制方法以最大限度地利用这些资源，以及智能家电重新调度。但是，住宅 CPS 与普通 CPS 不同，在系统内有很多直接的人际互动。以前的住宅能源管理方法虽然有效，但没有考虑内在和主导的人为因素。本文开发了一种以人为中心的住宅小区智能家电重新调度方法。我们首先展示了家庭成员活动与房屋电力需求之间关系的准确表示。我们使用该模型根据不同的家庭特征有效地生成多个电力配置文件。然后，我们正式建模用户在重新安排设备时的灵活性。与之前的研究相比，我们的工作能够在自动化住宅能源消耗时捕获与人类行为相关的内在行为。我们的结果显示，与没有重新安排设备的情况相比，节能 16%，峰值功率降低 22%，同时准确地表示和满足与人类相关的限制。我们还证明，忽视人类偏好可能导致超过 90% 的用户违反截止日期。