Residential energy scheduling for variable weather solar energy based on adaptive dynamic programming | |
Liu DR(刘德荣)1,2; Xu YC(徐延才)1; Wei QL(魏庆来)1; Xinliang Liu3 | |
刊名 | IEEE/CAA Journal of Automatica Sinica |
2017-12-20 | |
卷号 | 5期号:1页码:36-46 |
关键词 | Action Dependent Heuristic Dynamic Programming Adaptive Dynamic Programming Control Strategy Residential Energy Management Smart Grid |
DOI | 10.1109/JAS.2017.7510739 |
英文摘要 | The residential energy scheduling of solar energy is an important research area of smart grid. On the demand side, factors such as household loads, storage batteries, the outside public utility grid and renewable energy resources, are combined together as a nonlinear, time-varying, indefinite and complex system, which is difficult to manage or optimize. Many nations have already applied the residential real-time pricing to balance the burden on their grid. In order to enhance electricity efficiency of the residential micro grid, this paper presents an action dependent heuristic dynamic programming U+0028 ADHDP U+0029 method to solve the residential energy scheduling problem. The highlights of this paper are listed below. First, the weather-type classification is adopted to establish three types of programming models based on the features of the solar energy. In addition, the priorities of different energy resources are set to reduce the loss of electrical energy transmissions. Second, three ADHDP-based neural networks, which can update themselves during applications, are designed to manage the flows of electricity. Third, simulation results show that the proposed scheduling method has effectively reduced the total electricity cost and improved load balancing process. The comparison with the particle swarm optimization algorithm further proves that the present method has a promising effect on energy management to save cost. |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/20374] |
专题 | 复杂系统管理与控制国家重点实验室_平行控制 |
作者单位 | 1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 2.School of Automation, Guangdong University of Technology, Guangzhou 510006, China 3.The Bureau of Informationization Development, Cyberspace Administration of China, Beijing 100010, China |
推荐引用方式 GB/T 7714 | Liu DR,Xu YC,Wei QL,et al. Residential energy scheduling for variable weather solar energy based on adaptive dynamic programming[J]. IEEE/CAA Journal of Automatica Sinica,2017,5(1):36-46. |
APA | Liu DR,Xu YC,Wei QL,&Xinliang Liu.(2017).Residential energy scheduling for variable weather solar energy based on adaptive dynamic programming.IEEE/CAA Journal of Automatica Sinica,5(1),36-46. |
MLA | Liu DR,et al."Residential energy scheduling for variable weather solar energy based on adaptive dynamic programming".IEEE/CAA Journal of Automatica Sinica 5.1(2017):36-46. |
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