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An Optimal Energy-Saving Strategy for Home Energy Management Systems with Bounded Customer Rationality

机译:具有有限客户理性的家庭能源管理系统的最佳节能策略

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摘要

With the development of techniques, such as the Internet of Things (IoT) and edge computing, home energy management systems (HEMS) have been widely implemented to improve the electric energy efficiency of customers. In order to automatically optimize electric appliances’ operation schedules, this paper considers how to quantitatively evaluate a customer’s comfort satisfaction in energy-saving programs, and how to formulate the optimal energy-saving model based on this satisfaction evaluation. First, the paper categorizes the utility functions of current electric appliances into two types; time-sensitive utilities and temperature-sensitive utilities, which cover nearly all kinds of electric appliances in HEMS. Furthermore, considering the bounded rationality of customers, a novel concept called the energy-saving cost is defined by incorporating prospect theory in behavioral economics into general utility functions. The proposed energy-saving cost depicts the comfort loss risk for customers when their HEMS schedules the operation status of appliances, which is able to be set by residents as a coefficient in the automatic energy-saving program. An optimization model is formulated based on minimizing energy consumption. Because the energy-saving cost has already been evaluated in the context of the satisfaction of customers, the formulation of the optimization program is very simple and has high computational efficiency. The case study included in this paper is first performed on a general simulation system. Then, a case study is set up based on real field tests from a pilot project in Guangdong province, China, in which air-conditioners, lighting, and some other popular electric appliances were included. The total energy-saving rate reached 65.5% after the proposed energy-saving program was deployed in our project. The benchmark test shows our optimal strategy is able to considerably save electrical energy for residents while ensuring customers’ comfort satisfaction is maintained.
机译:随着诸如物联网(IoT)和边缘计算等技术的发展,家庭能源管理系统(HEMS)已被广泛实施以提高客户的电能效率。为了自动优化电器的运行时间表,本文考虑了如何在节能计划中定量评估客户的舒适度满意度,以及如何基于此满意度评估公式来制定最佳的节能模型。首先,本文将当前电器的效用功能分为两类:时间敏感型实用程序和温度敏感型实用程序,几乎涵盖了HEMS中的所有各种电器。此外,考虑到客户的有限理性,通过将行为经济学中的前景理论纳入通用效用函数中,定义了一个称为节能成本的新概念。拟议的节能成本描述了当客户的HEMS计划设备的运行状态时,其舒适度损失的风险,居民可以将其设置为自动节能程序中的系数。基于最小化能耗制定了优化模型。由于已经在客户满意度的背景下评估了节能成本,因此优化程序的制定非常简单,并且具有很高的计算效率。本文中包含的案例研究首先在通用仿真系统上执行。然后,基于来自中国广东省的一个试点项目的现场测试,建立了一个案例研究,其中包括了空调,照明和其他一些流行的电器。在本项目中实施了拟议的节能方案后,总节能率达到了65.5%。基准测试表明,我们的最佳策略能够为居民节省大量电能,同时确保维持客户的舒适感。

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