Online Battery Protective Energy Management for Energy-Transportation Nexus
Li, Shuangqi1,2; Zhao, Pengfei3,4; Gu, Chenghong1; Li, Jianwei1; Cheng, Shuang1; Xu, Minghao1
发表期刊IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
ISSN1551-3203
2022-11-01
卷号18期号:11页码:8203-8212
通讯作者Gu, Chenghong(c.gu@bath.ac.uk)
摘要Grid-connected electric vehicles (GEVs) and energy-transportation nexus bring a bright prospect to improve the penetration of renewable energy and the economy of microgrids (MGs). However, it is challenging to determine optimal vehicle-to-grid (V2G) strategies due to the complex battery aging mechanism and volatile MG states. This article develops a novel online battery anti-aging energy management method for energy-transportation nexus by using a novel deep reinforcement learning (DRL) framework. Based on battery aging characteristic analysis and rain-flow cycle counting technology, the quantification of aging cost in V2G strategies is realized by modeling the impact of number of cycles, depth of discharge, and charge and discharge rate. The established life loss model is used to evaluate battery anti-aging effectiveness of agent actions. The coordination of GEVs charging is modeled as multiobjective learning by using a DRL algorithm. The training objective is to maximize renewable penetration while reducing MG power fluctuations and vehicle battery aging costs. The developed energy-transportation nexus energy management method is verified to be effective in optimal power balancing and battery anti-aging control on a MG in the U.K. This article provides an efficient and economical tool for MG power balancing by optimally coordinating GEVs charging and renewable energy, thus helping promote a low-cost decarbonization transition.
关键词Batteries Aging Vehicle-to-grid US Department of Defense Costs Renewable energy sources Reinforcement learning Battery aging mitigation deep reinforcement learning (DRL) electric vehicle microgrid (MG) renewable energy transportation electrification vehicle-to-grid (V2G)
DOI10.1109/TII.2022.3163778
关键词[WOS]GRID OPERATIONS ; ION BATTERIES ; V2G ; CAPACITY ; SUPPORT ; MODEL
收录类别SCI
语种英语
WOS研究方向Automation & Control Systems ; Computer Science ; Engineering
WOS类目Automation & Control Systems ; Computer Science, Interdisciplinary Applications ; Engineering, Industrial
WOS记录号WOS:000856145200084
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
被引频次:14[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/173211/50443
专题复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
通讯作者Gu, Chenghong
作者单位1.Univ Bath, Dept Elect & Elect Engn, Bath BA2 7AY, Avon, England
2.Beijing Inst Technol, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100045, Peoples R China
4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China
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GB/T 7714
Li, Shuangqi,Zhao, Pengfei,Gu, Chenghong,et al. Online Battery Protective Energy Management for Energy-Transportation Nexus[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,2022,18(11):8203-8212.
APA Li, Shuangqi,Zhao, Pengfei,Gu, Chenghong,Li, Jianwei,Cheng, Shuang,&Xu, Minghao.(2022).Online Battery Protective Energy Management for Energy-Transportation Nexus.IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,18(11),8203-8212.
MLA Li, Shuangqi,et al."Online Battery Protective Energy Management for Energy-Transportation Nexus".IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 18.11(2022):8203-8212.
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