Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids

doi:10.1109/TIE.2017.2650872

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 复杂系统智能机理与平行控制团队

	Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids
	Wei, Qinglai1,2 ; Liu, Derong 3; Lewis, Frank L.4; Liu, Yu5 ; Zhang, Jie1,6
发表期刊	IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
	2017-05-01
卷号	64 期号:5 页码:4110-4120
文章类型	Article
摘要	In this paper, a novel mixed iterative adaptive dynamic programming (ADP) algorithm is developed to solve the optimal battery energy management and control problem in smart residential microgrid systems. Based on the data of the load and electricity rate, two iterations are constructed, which are P-iteration and V-iteration, respectively. The V-iteration is implemented based on value iteration, which aims to obtain the iterative control law sequence in each period. The P-iteration is implemented based on policy iteration, which updates the iterative value function according to the iterative control law sequence. Properties of the developed mixed iterative ADP algorithm are analyzed. It is shown that the iterative value function is monotonically nonincreasing and converges to the solution of the Bellman equation. In each iteration, it is proven that the performance index function is finite under the iterative control law sequence. Finally, numerical results and comparisons are given to illustrate the performance of the developed algorithm.
关键词	Adaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Mixed Iteration Optimal Control Policy Iteration Smart Grid Value Iteration
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TIE.2017.2650872
关键词[WOS]	TIME NONLINEAR-SYSTEMS ; OPTIMAL TRACKING CONTROL ; NEURAL-NETWORK ; LEARNING ALGORITHM ; FEEDBACK-CONTROL ; STORAGE SYSTEM ; CONTROL SCHEME ; REINFORCEMENT ; MANAGEMENT ; DESIGN
收录类别	SCI
语种	英语
项目资助者	National Natural Science Foundation of China(61233001 ; Open Research Project from SKLMCCS(20150104) ; 61273140 ; 61374105 ; 61379099 ; 61304079 ; 61673054 ; 61533017 ; 71402178 ; 61533019 ; 71232006 ; U1501251)
WOS研究方向	Automation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS类目	Automation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS记录号	WOS:000399674000065
引用统计	被引频次：119[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/13637
专题	多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 4.Univ Texas Arlington, UTA Res Inst, Arlington, TX 76118 USA 5.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 6.Qingdao Acad Intelligent Ind, Qingdao 266000, Shandong, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wei, Qinglai,Liu, Derong,Lewis, Frank L.,et al. Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2017,64(5):4110-4120.
APA	Wei, Qinglai,Liu, Derong,Lewis, Frank L.,Liu, Yu,&Zhang, Jie.(2017).Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,64(5),4110-4120.
MLA	Wei, Qinglai,et al."Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 64.5(2017):4110-4120.

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