Adaptive Dynamic Programming Algorithm for Renewable Energy Scheduling and Battery Management

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 智能化团队

	Adaptive Dynamic Programming Algorithm for Renewable Energy Scheduling and Battery Management
	Boaro, Matteo 1; Fuselli, Danilo 1; De Angelis, Francesco 1; Liu, Derong 2; Wei, Qinglai2 ; Piazza, Francesco 1
刊名	COGNITIVE COMPUTATION
	2013-06-01
卷号	5 期号:2 页码:264-277
关键词	Adaptive dynamic programming Approximate dynamic programming Neural networks Energy scheduling Battery management
英文摘要	The employment of intelligent energy management systems likely allows reducing consumptions and thus saving money for consumers. The residential load demand must be met, and some advantages can be obtained if specific optimization policies are taken. With an efficient use of renewable sources and power imported from the grid, an intelligent and adaptive system which manages the battery is able to satisfy the load demand and minimize the entire energy cost related to the scenario under study. In this paper, an adaptive dynamic programming-based algorithm is presented to face dynamic situations, in which some conditions of the environment or habits of customer may vary with time, especially using renewable energy. Based on the idea of smart grid, we propose an intelligent management scheme for renewable resources combined with battery implemented with a faster and simpler scheme of dynamic programming, by considering only one critic network and some optimization policies in order to satisfy the load demand. Since this kind of problem is suitable to avoid the training of an action network, the training loop among the two neural networks is deleted and the training process is greatly simplified. Computer simulations confirm the effectiveness of this self-learning design in a typical residential scenario.
WOS标题词	Science & Technology ; Technology ; Life Sciences & Biomedicine
类目[WOS]	Computer Science, Artificial Intelligence ; Neurosciences
研究领域[WOS]	Computer Science ; Neurosciences & Neurology
关键词[WOS]	PARTICLE SWARM OPTIMIZATION ; TIME NONLINEAR-SYSTEMS ; STORAGE SYSTEM ; CRITIC DESIGNS ; WIND ; SMART
收录类别	SCI
语种	英语
WOS记录号	WOS:000318648900012
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/3828]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队
作者单位	1.Univ Politecn Marche, Dipartimento Ingn Informaz, I-60131 Ancona, Italy 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Boaro, Matteo,Fuselli, Danilo,De Angelis, Francesco,et al. Adaptive Dynamic Programming Algorithm for Renewable Energy Scheduling and Battery Management[J]. COGNITIVE COMPUTATION,2013,5(2):264-277.
APA	Boaro, Matteo,Fuselli, Danilo,De Angelis, Francesco,Liu, Derong,Wei, Qinglai,&Piazza, Francesco.(2013).Adaptive Dynamic Programming Algorithm for Renewable Energy Scheduling and Battery Management.COGNITIVE COMPUTATION,5(2),264-277.
MLA	Boaro, Matteo,et al."Adaptive Dynamic Programming Algorithm for Renewable Energy Scheduling and Battery Management".COGNITIVE COMPUTATION 5.2(2013):264-277.