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基于多代理系统的电动汽车充放电分布式协同调度策略 被引量:16

Multi-agent system based charging and discharging of electric vehicles distributed coordination dispatch strategy
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摘要 大规模电动汽车(Electric Vehicles, EV)无序充电行为将增加电力系统运行的安全隐患,而数量庞大的电动汽车充放电优化控制为电力系统能量管控提出了新的挑战。提出一种改进的基于多代理系统(Multi-AgentSystem,MAS)的电动汽车充放电分布式协同调度方法。该方法以负荷填谷为目标,在虚拟电价协同机制框架下,综合考虑了配电网三相负荷平衡、变压器容量约束和节点电压约束,与MAS信息交互机制相结合,通过采用迭代修正虚拟电价的方法,实现EV有序的智能充放电。以IEEE33节点系统为例进行仿真分析,验证了所提方法的特点和有效性。 The large-scale Electric Vehicles(EV)uncontrolled charging behavior will increase the safety hazard of the power system operation,and a large number of EV charging and discharging control brings new challenge to energy management of the power system.In this paper,an improved EV charging and discharging distributed coordination dispatch control strategy based on Multi-Agent System(MAS)is proposed.It aims at the valley-filling,under the framework of the virtual price coordination mechanism,considers the distribution network three-phase balance,transformer capacity and node voltage constraint,and combining with MAS information interaction mechanism,adopts iterative correction of virtual price to achieve the intelligent charging and discharging of EV.Taking IEEE33 node system as an example,simulation and analysis verify the characteristics and effectiveness of the proposed method.
作者 于娜 于飞 黄大为 陈厚合 张鹏宇 YU Na;YU Fei;HUANG Dawei;CHEN Houhe;ZHANG Pengyu(School of Electrical Engineering,Northeast Electric Power University,Jilin 132012,China;Shanxi Electric Power Survey and Design Co.,Ltd.,Energy Construction Group of China,Taiyuan 030001,China;State Grid Jilin Electric Power Company Limited,Changchun 130021,China)
出处 《电力系统保护与控制》 EI CSCD 北大核心 2019年第5期1-9,共9页 Power System Protection and Control
基金 长江学者和创新团队发展计划项目资助(IRT1114) 国家自然科学基金项目资助(51307019 51377016 51477027) 吉林省科技发展计划资助项目资助(20130102026JC 20140101210JC)~~
关键词 电动汽车 分布式充放电 多代理系统 节点电压 配电网 electric vehicle distributed charging and discharging multi-agent system node voltage distribution network
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  • 1郭联哲,谭忠富,李晓军.基于用户响应下的分时电价优化设计模型与方法[J].电网技术,2006,30(5):24-28. 被引量:37
  • 2Zhang L, Yah Z, Feng D, et al. Centralized and decentralized optimal scheduling for charging electric vehicles[J/OL], arXiv: 1410.3899, 2014. http:/ /arxiv.org/ftp/arxiv/papers/1410/1410.3 899.pdf. 被引量:1
  • 3Xu Shaolun, Feng Donghan, Yan Zheng, et al. Ant-based swarm algorithm for charging coordination of electric vehicle[J]. International Journal of Distributed Sensor Networks, doi: 10.1155/2013/268942. 被引量:1
  • 4Zhongjing Ma, Callaway D, Hiskens I, et al. Decentralized charging control for large populations of plug-in electric vehicles[C]//2010 49th IEEE Conference on Decision and Control(CDC). Atlanta: IEEE, 2010: 206-212. 被引量:1
  • 5Karfopoulos E L, Hatziargyriou ND. A multi-agent system for controlled charging of a large population of electric vehicles[J]. IEEE Transactions on Power Systems, 2013, 28(2): 1196-1204. 被引量:1
  • 6May G. Battery options for hybrid electric vehicles[C]//IET Hybrid Vehicle Conference. Coventry: IET, 2006: 67-78. 被引量:1
  • 7Federal High Way Administration, US Department of Transportation. Summary of travel trends: 2009 national household travel survey [EB/OL]. 201112014-07]. http://nhts.ornl.gov/2OO9/pub/stt.pdf. 被引量:1
  • 8McArthur S D J, Davidson E M, Catterson V M, et al. Multi-agent systems for power engineering applications, part I: concepts,approaches, and technical challenges[J]. IEEE Transactions on Power Systems, 2007, 22(4): 1743-1752. 被引量:1
  • 9Abedini R, Pinto T, Morais H, et al. Multi-agent approach for power system in a smart grid protection context[C]// 2013 IEEE PowerTech(POWERTECH). Grenoble: IEEE, 2013: 1-6. 被引量:1
  • 10Manickavasagam K, Nithya M, Priya K, et al. Control of distributed generator and smart grid using multi-agent systemiC]//2011 1st International Conference on Electrical Energy Systems(ICEES). Newport Beach: IEEE, 2011: 212-217. 被引量:1

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