Action dependent heuristic dynamic programming for home energy resource scheduling
文献类型：期刊论文
| 作者 | Fuselli, Danilo1; De Angelis, Francesco1; Boaro, Matteo1; Squartini, Stefano1; Wei, Qinglai3 ; Liu, Derong2; Piazza, Francesco1
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| 刊名 | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
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| 出版日期 | 2013-06-01 |
| 卷号 | 48页码:148-160 |
| 关键词 | Adaptive dynamic programming Action dependent heuristic dynamic programming Particle swarm optimization Neural networks Smart grid Home energy management |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Engineering, Electrical & Electronic |
| 研究领域[WOS] | Engineering |
| 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记录号 | WOS:000315250200015 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3859]  |
| 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, 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. |
入库方式： OAI收割
来源：自动化研究所
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