Action dependent heuristic dynamic programming for home energy resource scheduling

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

	Action dependent heuristic dynamic programming for home energy resource scheduling
	Fuselli, Danilo 1; De Angelis, Francesco 1; Boaro, Matteo 1; Squartini, Stefano 1; Wei, Qinglai3 ; Liu, Derong 2; Piazza, Francesco 1
发表期刊	INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
	2013-06-01
卷号	48 页码:148-160
文章类型	Article
摘要	Energy management in smart home environment is nowadays a crucial aspect on which technologies have been focusing on in order to save costs and minimize energy waste. This goal can be reached by means of an energy resource scheduling strategy provided by a suitable optimization technique. The proposed solution involves a class of Adaptive Critic Designs (ACDs) called Action Dependent Heuristic Dynamic Programming (ADHDP) that uses two neural networks, namely the Action and the Critic Network. This scheme is able to minimize a given Utility Function over a certain time horizon. In order to increase the performances of the ADHDP algorithm, suitable Particle Swarm Optimization (PSO) based procedures are used to pretrain the weights of the Action and the Critic networks. The results provided by PSO techniques and by a non-optimal baseline approach are also used as elements of comparison. Computer simulations have been carried out in different residential scenarios. An historical data set for solar irradiation has been used to simulate the behavior of a photovoltaic array to obtain renewable energy and the main grid is used to supply the load and charge the battery when necessary. The results confirm that the ADHDP is able to reduce the overall energy cost with respect to the baseline solution and the PSO techniques. Moreover, the validity of this method has also been shown in a more realistic context where only forecasted values of solar irradiation and electricity price can be used. (c) 2012 Elsevier Ltd. All rights reserved.
关键词	Adaptive Dynamic Programming Action Dependent Heuristic Dynamic Programming Particle Swarm Optimization Neural Networks Smart Grid Home Energy Management
WOS标题词	Science & Technology ; Technology
关键词[WOS]	PARTICLE SWARM OPTIMIZATION ; ADAPTIVE CRITIC DESIGNS ; DEMAND-SIDE MANAGEMENT ; STORAGE SYSTEM ; BATTERY ; GENERATION ; SMART
收录类别	SCI
语种	英语
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000315250200015
引用统计	被引频次：113[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/173211/3859
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.Univ Politecn Marche, Dipartimento Ingn Informaz, Ancona, Italy 2.Univ Illinois, Dept Elect & Comp Engn, Chicago, IL USA 3.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Fuselli, Danilo,De Angelis, Francesco,Boaro, Matteo,et al. Action dependent heuristic dynamic programming for home energy resource scheduling[J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS,2013,48:148-160.
APA	Fuselli, Danilo.,De Angelis, Francesco.,Boaro, Matteo.,Squartini, Stefano.,Wei, Qinglai.,...&Piazza, Francesco.(2013).Action dependent heuristic dynamic programming for home energy resource scheduling.INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS,48,148-160.
MLA	Fuselli, Danilo,et al."Action dependent heuristic dynamic programming for home energy resource scheduling".INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 48(2013):148-160.