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

Guoying Lin, Yuyao Yang, Feng Pan, Sijian Zhang, Fen Wang and Shuai Fan
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Guoying Lin: Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
Yuyao Yang: Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
Feng Pan: Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
Sijian Zhang: Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
Fen Wang: Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao-Tong University, Shanghai 200240, China
Shuai Fan: Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao-Tong University, Shanghai 200240, China

Future Internet, 2019, vol. 11, issue 4, 1-16

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.

Keywords: energy saving; electric appliance utility function; prospect theory; energy-saving cost (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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