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

1
Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
2
Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao-Tong University, Shanghai 200240, China
*
Author to whom correspondence should be addressed.
Future Internet 2019, 11(4), 88; https://doi.org/10.3390/fi11040088
Received: 6 March 2019 / Revised: 21 March 2019 / Accepted: 29 March 2019 / Published: 2 April 2019
(This article belongs to the Section Smart System infrastructures and Cybersecurity)
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Abstract

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. View Full-Text
Keywords: energy saving; electric appliance utility function; prospect theory; energy-saving cost energy saving; electric appliance utility function; prospect theory; energy-saving cost
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Lin, G.; Yang, Y.; Pan, F.; Zhang, S.; Wang, F.; Fan, S. An Optimal Energy-Saving Strategy for Home Energy Management Systems with Bounded Customer Rationality. Future Internet 2019, 11, 88.

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