A novel energy management method for multiple residential energy systems with energy exchange

被引:0
|
作者
Li, Hongyang [1 ,2 ]
Wei, Qinglai [1 ,2 ,3 ]
机构
[1] Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Macau Univ Sci & Technol, Inst Syst Engn, Taipei 999078, Taiwan
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Energy management; Multiple residential energy systems; Energy optimization of batteries; Action-dependent heuristic dynamic; programming (ADHDP); BATTERY STORAGE; NETWORKS;
D O I
10.1016/j.neucom.2023.127185
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Energy saving and emission reduction are the worldwide outstanding problems in the development of economy and society, which lead to wide attention of residential energy management. This paper presents a novel energy management method for multiple residential energy systems with energy exchange based on action -dependent heuristic dynamic programming (ADHDP). The major contributions are displayed as follows: (1) a novel energy management model is established for multiple residential energy systems with real-time electricity price and time -varying residential loads; (2) a novel ADHDP based energy management method is presented to obtain the energy scheduling scheme of multiple residential energy systems; (3) the continuous control action of the overall system is transformed into discrete control space which avoids training the action network. First, the structure and system models of multiple residential energy systems are introduced, and the energy management problem is formulated. Then, a brief introduction of ADHDP method is provided. Based on this, an energy management method is presented and an effective discretization method of control action is developed for solving the presented energy management problem with less computational burden. Simulation results show that the presented method can reduce the energy cost effectively. Finally, the comparison results verify the superiorities over the traditional energy management methods.
引用
收藏
页数:9
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