电动汽车充电区/站两级实时能量管理机制及优化策略
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摘要
未来电力系统中电动汽车保有量会相当庞大,由调度机构直接控制每辆电动汽车进行有序充电是不现实的,比较可行的方案是由代理商和电网调度中心共同对电动汽车进行分层分区管理。基于此,提出包括电网调度中心、区域能量管理系统(Area-EMS)和微调度能量管理系统(μ-EMS)的电动汽车充电分层能量管理架构,并详细阐述各个层级的功能以及该架构模型的运行原理;针对代理商负责的Area-EMS和μ-EMS分别提出两级实时能量管理策略,该策略在满足电动汽车充电需求和保证经济效益的同时,能够适应不同的电网耦合模式,改善区域电网的负荷峰谷特性;通过仿真算例验证所提分层架构和实时能量管理策略的有效性和实用性。
A large number of electric vehicles will be integrated into the power system in the promising future. In this case,it is more or less unrealistic to directly dispatch each electric vehicle for orderly charging. A more realistic plan is to manage those electric vehicles in different levels and zones in a decentralized basis. In this regard,an EV charging layered energy management architecture including power system dispatching center,Area-EMS(Area Energy Manage System) and μ-EMS(fine-tuning Energy Management System) is proposed. The function of each layer and the operation scheme of the layered management architecture are introduced in detail. A two-stage real-time energy management strategy is designed for Area-EMS and μ-EMS in charge of agents respectively. The strategy can satisfy the charging needs of electric vehicles and ensure economic benefits. Moreover,this strategy is adaptive to different power grid coupling modes,and can improve load peak-valley characteristics of regional power grid. Simulation examples are conducted to verify the effectiveness and practicability of the proposed layered architecture and real-time energy management strategy.
A large number of electric vehicles will be integrated into the power system in the promising future. In this case,it is more or less unrealistic to directly dispatch each electric vehicle for orderly charging. A more realistic plan is to manage those electric vehicles in different levels and zones in a decentralized basis. In this regard,an EV charging layered energy management architecture including power system dispatching center,Area-EMS(Area Energy Manage System) and μ-EMS(fine-tuning Energy Management System) is proposed. The function of each layer and the operation scheme of the layered management architecture are introduced in detail. A two-stage real-time energy management strategy is designed for Area-EMS and μ-EMS in charge of agents respectively. The strategy can satisfy the charging needs of electric vehicles and ensure economic benefits. Moreover,this strategy is adaptive to different power grid coupling modes,and can improve load peak-valley characteristics of regional power grid. Simulation examples are conducted to verify the effectiveness and practicability of the proposed layered architecture and real-time energy management strategy.
引文
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[9] 翁国庆,黄飞腾,张有兵,等.电动公交汽车电池集群参与海岛微网能量调度的V2G策略[J].电力自动化设备,2016,36(10):31-39.WENG Guoqing,HUANG Feiteng,ZHANG Youbing,et al.V2G stra-tegy for energy dispatch of island microgrid wih EBBG[J].Electric Power Automation Equipment,2016,36(10):31-39.
[10] 高亚静,王辰,吕孟扩,等.计及车主满意度的EV最优峰谷分时电价模型[J].电力自动化设备,2014,34(2):8-13.GAO Yajing,WANG Chen,Lü Mengkuo,et al.Optimal time-of-use price model considering satisfaction degree of electric vehicle owners[J].Electric Power Automation Equipment,2014,34(2):8-13.
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[12] 葛少云,王龙,刘洪,等.计及EV入网的峰谷电价时段优化模型研究[J].电网技术,2013,37(8):2316-2321.GE Shaoyun,WANG Long,LIU Hong,et al.An optimization model of peak-valley price time-interval considering vehicle-to-grid[J].Power System Technology,2013,37(8):2316-2321.
[13] 李秋硕.EV接入电网的电能有序利用模型与控制策略研究[D].北京:华北电力大学,2014.LI Qiushuo.Research on models and strategies of electric energy coordinated consumption with electric vehicles integrated in power system[D].Beijing:North China Electric Power University,2014.
[14] 张良,严正,冯冬涵,等.采用两阶段优化模型的EV充电站内有序充电策略[J].电网技术,2014,38(4):967-973.ZHANG Liang,YAN Zheng,FENG Donghan,et al.Two-stage optimization model based coordinated charging for EV charging station[J].Power System Technology,2014,38(4):967-973.
[15] ZHAN K,HU Z,SONG Y,et al.A probability transition matrix based decentralized electric vehicle charging method for load valley filling[J].Electric Power Systems Research,2015(125):1-7.
[16] 于浩明.基于分时电价的EV有序充电优化[D].长沙:湖南大学,2015.YU Haoming.The coordinated charging optimization for electric vehicles based on time-of-use price[D].Changsha:Hunan University,2015.
[17] 温剑锋,陶顺,肖湘宁.基于出行链随机模拟的EV充电需求分析[J].电网技术,2015,39(6):1477-1484.WEN Jianfeng,TAO Shun,XIAO Xiangning.Analysis on charging demand of EV based on stochastic simulation of trip chain[J].Power System Technology,2015,39(6):1477-1484.
[2] MA Z,CALLAWAY D S,HISKENS L A.Decentralized charging control of large populations of plug-in electric vehicles[J].IEEE Transactions on Control Systems Technology,2013,21(1):67-78.
[3] 王建,吴奎华,刘志珍,等.电动汽车充电对配电网负荷的影响及有序控制研究[J].电力自动化设备,2013,33(8):47-52.WANG Jian,WU Kuihua,LIU Zhizhen,et al.Impact of electric vehicle charging on distribution network load and coordinated control[J].Electric Power Automation Equipment,2013,33(8):47-52.
[4] 陈静鹏,朴龙健,艾芊,等.基于分布式控制的EV分层优化调度[J].电力系统自动化,2016,40(18):24-31,47.CHEN Jingpeng,PU Longjian,AI Qian,et al.Hierarchical optimal scheduling for electric vehicles based on distributed control[J].Automation of Electric Power Systems,2016,40(18):24-31,47.
[5] 姚伟锋,赵俊华,文福拴,等.基于双层优化的EV充放电调度策略[J].电力系统自动化,2012,36(11):30-37.YAO Weifeng,ZHAO Junhua,WEN Fushuan,et al.A charging and discharging strategy for electric vehicles based on bi-level optimization[J].Automation of Electric Power Systems,2012,36(11):30-37.
[6] 李敏,苏小林,阎晓霞,等.多目标分层分区的EV有序充放电优化控制[J].电网技术,2015,39(12):3556-3562.LI Min,SU Xiaolin,YAN Xiaoxia,et al.Coordinated charging and discharging of plug-in electric vehicles based on multi-layered and multi-regional optimization[J].Power System Technology,2015,39(12):3556-3562.
[7] 占恺峤,胡泽春,宋永华,等.含新能源接入的EV有序充电分层控制策略[J].电网技术,2016,40(12):3689-3695.ZHAN Kaiqiao,HU Zechun,SONG Yonghua,et al.Electric vehicle coordinated charging hierarchical control strategy considering rene-wable energy generation integration[J].Power System Technology,2016,40(12):3689-3695.
[8] 张颖达,刘念,张建华.电动汽车换电站V2G运行对中压配电网故障特征的影响[J].电力自动化设备,2014,34(11):55-61.ZHANG Yingda,LIU Nian,ZHANG Jianhua.Impact of battery swap station using V2G technology on fault characteristics of medium voltage distribution network[J].Electric Power Automation Equipment,2014,34(11):55-61.
[9] 翁国庆,黄飞腾,张有兵,等.电动公交汽车电池集群参与海岛微网能量调度的V2G策略[J].电力自动化设备,2016,36(10):31-39.WENG Guoqing,HUANG Feiteng,ZHANG Youbing,et al.V2G stra-tegy for energy dispatch of island microgrid wih EBBG[J].Electric Power Automation Equipment,2016,36(10):31-39.
[10] 高亚静,王辰,吕孟扩,等.计及车主满意度的EV最优峰谷分时电价模型[J].电力自动化设备,2014,34(2):8-13.GAO Yajing,WANG Chen,Lü Mengkuo,et al.Optimal time-of-use price model considering satisfaction degree of electric vehicle owners[J].Electric Power Automation Equipment,2014,34(2):8-13.
[11] 项顶,宋永华,胡泽春,等.EV参与V2G的最优峰谷电价研究[J].中国电机工程学报,2013,33(31):15-25.XIANG Ding,SONG Yonghua,HU Zechun,et al.Research on optimal time of use price for electric vehicle participating V2G[J].Proceedings of the CSEE,2013,33(31):15-25.
[12] 葛少云,王龙,刘洪,等.计及EV入网的峰谷电价时段优化模型研究[J].电网技术,2013,37(8):2316-2321.GE Shaoyun,WANG Long,LIU Hong,et al.An optimization model of peak-valley price time-interval considering vehicle-to-grid[J].Power System Technology,2013,37(8):2316-2321.
[13] 李秋硕.EV接入电网的电能有序利用模型与控制策略研究[D].北京:华北电力大学,2014.LI Qiushuo.Research on models and strategies of electric energy coordinated consumption with electric vehicles integrated in power system[D].Beijing:North China Electric Power University,2014.
[14] 张良,严正,冯冬涵,等.采用两阶段优化模型的EV充电站内有序充电策略[J].电网技术,2014,38(4):967-973.ZHANG Liang,YAN Zheng,FENG Donghan,et al.Two-stage optimization model based coordinated charging for EV charging station[J].Power System Technology,2014,38(4):967-973.
[15] ZHAN K,HU Z,SONG Y,et al.A probability transition matrix based decentralized electric vehicle charging method for load valley filling[J].Electric Power Systems Research,2015(125):1-7.
[16] 于浩明.基于分时电价的EV有序充电优化[D].长沙:湖南大学,2015.YU Haoming.The coordinated charging optimization for electric vehicles based on time-of-use price[D].Changsha:Hunan University,2015.
[17] 温剑锋,陶顺,肖湘宁.基于出行链随机模拟的EV充电需求分析[J].电网技术,2015,39(6):1477-1484.WEN Jianfeng,TAO Shun,XIAO Xiangning.Analysis on charging demand of EV based on stochastic simulation of trip chain[J].Power System Technology,2015,39(6):1477-1484.