Nash Q-learning based equilibrium transfer for integrated energy management game with We-Energy

doi:10.1016/j.neucom.2019.01.109

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

	Nash Q-learning based equilibrium transfer for integrated energy management game with We-Energy
	Yang, Lingxiao 2; Sun, Qiuye 2; Ma, Dazhong 2; Wei, Qinglai 1
刊名	NEUROCOMPUTING
	2020-07-05
卷号	396 页码:216-223
关键词	Nash Q-learning Integrated energy management game Interconnected multicarrier systems Equilibrium transfer We-Energy
ISSN号	0925-2312
DOI	10.1016/j.neucom.2019.01.109
通讯作者	Yang, Lingxiao(ylxiao66@163.com)
英文摘要	This paper proposes an innovative energy interacting unit ("We-Energy") with the characteristic of full duplex trading mode. In order to manage all the We-Energies in an optimal way, a new integrated energy management framework based on a noncooperative game is performed so as to allocate the energy demands of each WE such that the benefit of each WE can be maximized. To overcome the impact of the randomness and inaccurate information of renewable energy sources, Nash Q-learning algorithm is applied for computation of game equilibrium under the unknown environment. The novelty of the proposed algorithms is related to the incorporation of the continuous action space into the discrete adaptive action set and combined the equilibrium transfer to improve the efficiency of the algorithm. Simulation studies of modified IMS confirm that it has a better performance with the desired equilibrium strategy and convergence speed. (C) 2019 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[61573094] ; National Natural Science Foundation of China[61433004] ; Fundamental Research Funds for the Central Universities[N170405002]
WOS关键词	REINFORCEMENT ; MARKET
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000536806600001
资助机构	National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/39560]
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
通讯作者	Yang, Lingxiao
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 2.Northeastern Univ, Sch Informat Sci & Engn, Shenyang, Peoples R China
推荐引用方式 GB/T 7714	Yang, Lingxiao,Sun, Qiuye,Ma, Dazhong,et al. Nash Q-learning based equilibrium transfer for integrated energy management game with We-Energy[J]. NEUROCOMPUTING,2020,396:216-223.
APA	Yang, Lingxiao,Sun, Qiuye,Ma, Dazhong,&Wei, Qinglai.(2020).Nash Q-learning based equilibrium transfer for integrated energy management game with We-Energy.NEUROCOMPUTING,396,216-223.
MLA	Yang, Lingxiao,et al."Nash Q-learning based equilibrium transfer for integrated energy management game with We-Energy".NEUROCOMPUTING 396(2020):216-223.