Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming

Xiangyu Kong, Siqiong Zhang, Bowei Sun, Qun Yang, Shupeng Li and Shijian Zhu
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Xiangyu Kong: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Siqiong Zhang: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Bowei Sun: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Qun Yang: State Grid Liaoning Electric Power Company, Dalian 110006, China
Shupeng Li: Tianjin Electric Power Research Institute, State Grid Tianjin Electric Power Company, Tianjin 300384, China
Shijian Zhu: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China

Energies, 2020, vol. 13, issue 11, 1-27

Abstract: With the development of smart devices and information technology, it is possible for users to optimize their usage of electrical equipment through the home energy management system (HEMS). To solve the problems of daily optimal scheduling and emergency demand response (DR) in an uncertain environment, this paper provides an opportunity constraint programming model for the random variables contained in the constraint conditions. Considering the probability distribution of the random variables, a home energy management method for DR based on chance-constrained programming is proposed. Different confidence levels are set to reflect the influence mechanism of random variables on constraint conditions. An improved particle swarm optimization algorithm is used to solve the problem. Finally, the demand response characteristics in daily and emergency situations are analyzed by simulation examples, and the effectiveness of the method is verified.

Keywords: demand response; energy management; control strategy; chance-constrained programming; particle swarm optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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