基于TOPSIS方法的居民区电动汽车有序充电策略
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摘要
针对中国目前超大城市电动汽车保有量的快速增长与现有配电网制约用户充电需求的矛盾,提出了一种基于理想解法的居民区电动汽车有序充电策略,以最大限度调配现有可用的电能资源。通过分析电动汽车出行规律,建立了居民区电动汽车出行、返回、等待、充电的数学模型。在综合考虑充电时间、充电费用、等待时间、充电完成率、小区总负荷变化率等决策指标基础上,建立了基于理想解法的有序充电排序方法,并通过算例仿真进一步对比了分时电价策略下峰谷电价对用户充电行为的影响。仿真结果表明,与现有网格选取法有序充电结果相比,该方法可在保证电动汽车充电完成率和稳定居民区负荷前提下,更好地兼顾电动汽车充电的连续性、便捷性和经济性,为居民区停车场电动汽车有序充电管理提供决策依据。
In view of the rapid growth of electric vehicle(EV)ownership in megacities in China and the contradiction between the EV charging demand and the lower distribution network service ability,an orderly EV charging strategy based on technique for order preference by similarity to ideal solution(TOPSIS)is proposed to dispatch the available power energy resources to the utmost extent.By analyzing EV travel laws,a mathematical model is built to simulate the traveling,returning,waiting and charging process of EVs in residential areas.An orderly charging method based on TOPSIS analysis is proposed considering comprehensively the decision indicators such as charging time,charging cost,queuing time,charging completion rate,and the overall load variation rate of residential areas.The simulations further compare the impact of peak-valley price on users' charging behavior under the time-of-use price strategy.Simulation results show that,compared with the grid picking method,the proposed TOPSIS based orderly charging strategy can better consider the continuity,convenience and economy of EV charging,and provide a decision basis for the orderly charging management of EVs parking in residential areas under the premise of the high completion rate of EV charging and the stability of residential load.
In view of the rapid growth of electric vehicle(EV)ownership in megacities in China and the contradiction between the EV charging demand and the lower distribution network service ability,an orderly EV charging strategy based on technique for order preference by similarity to ideal solution(TOPSIS)is proposed to dispatch the available power energy resources to the utmost extent.By analyzing EV travel laws,a mathematical model is built to simulate the traveling,returning,waiting and charging process of EVs in residential areas.An orderly charging method based on TOPSIS analysis is proposed considering comprehensively the decision indicators such as charging time,charging cost,queuing time,charging completion rate,and the overall load variation rate of residential areas.The simulations further compare the impact of peak-valley price on users' charging behavior under the time-of-use price strategy.Simulation results show that,compared with the grid picking method,the proposed TOPSIS based orderly charging strategy can better consider the continuity,convenience and economy of EV charging,and provide a decision basis for the orderly charging management of EVs parking in residential areas under the premise of the high completion rate of EV charging and the stability of residential load.
引文
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[16]杨晓东,任帅杰,张有兵,等.电动汽车可调度能力模型与日内优先调度策略[J].电力系统自动化,2017,41(2):84-93.DOI:10.7500/AEPS20160323006.YANG Xiaodong,REN Shuaijie,ZHANG Youbing,et al.Schedulable ability model and priority-based intraday scheduling strategy for electric vehicle[J].Automation of Electric Power Systems,2017,41(2):84-93.DOI:10.7500/AEPS20160323006.
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[19]陈鹏,孟庆海,赵彦锦.基于蒙特卡洛法的电动汽车充电负荷计算[J].电气工程学报,2016,11(11):40-46.CHEN Peng,MENG Qinghai,ZHAO Yanjin.The electric vehicle charging load calculation based on the Monte Carlo method[J].Journal of Electrical Engineering,2016,11(11):40-46.
[20]刘自发,庞铖铖,魏建炜,等.基于IAHP和TOPSIS方法的负荷密度指标计算[J].电力系统自动化,2012,36(13):56-60.LIU Zifa,PANG Chengcheng,WEI Jianwei,et al.Index calculation of load density based on IAHP and TOPSISmethods[J].Automation of Electric Power Systems,2012,36(13):56-60.
[21]国网北京市电力公司.4440个公共充电桩明起执行峰谷电价[EB/OL].[2018-03-19].http://www.bj.sgcc.com.cn/html/main/col37/2016-06/15/20160615091559700402447_1.html.State Grid Beijing Electric Power Company.4440 public charging piles will carry out peak-valley price from tomorrow[EB/OL].[2018-03-19].http://www.bj.sgcc.com.cn/html/main/col37/2016-06/15/20160615091559700402447_1.html.
[2]人民网.北京:纯电动车指标今年配6万不摇号[EB/OL].[2017-11-08].http://energy.people.com.cn/n1/2016/0108/c71661-28029661.html.People’s Daily Online.Beijing:the index for pure electric vehicles will increase to 60thousand this year without plate lottery[EB/OL].[2017-11-08].http://energy.people.com.cn/n1/2016/0108/c71661-28029661.html.
[3]苏海锋,梁志瑞.基于峰谷电价的家用电动汽车居民小区有序充电控制方法[J].电力自动化设备,2015,35(6):17-22.SU Haifeng,LIANG Zhirui.Orderly charging control based on peak-valley electricity tariffs for household electric vehicles of residential quarter[J].Electric Power Automation Equipment,2015,35(6):17-22.
[4]王姝凝,杨少兵.居民小区电动汽车充电负荷有序控制策略[J].电力系统自动化,2016,40(4):71-77.DOI:10.7500/AEPS20150429013.WANG Shuning,YANG Shaobing.A coordinated charging control strategy for electric vehicles charging load in residential area[J].Automation of Electric Power Systems,2016,40(4):71-77.DOI:10.7500/AEPS20150429013.
[5]YANG Y,LIU Z,QU D,et al.Research on coordinated charging for electric vehicles[C]//2015 18th International Conference on Electrical Machines and Systems(ICEMS),October 25-28,2015,Pattaya,Thailand:525-530.
[6]李如琦,苏浩益.基于排队论的电动汽车充电设施优化配置[J].电力系统自动化,2011,35(14):58-61.LI Ruqi,SU Haoyi.Optimal allocation of charging facilities for electric vehicles based on queuing theory[J].Automation of Electric Power Systems,2011,35(14):58-61.
[7]李昊扬.基于需求侧响应的电动汽车有序充电研究[D].天津:天津大学,2012.LI Haoyang.Electric vehicle ordered charging based on the demand side response[D].Tianjin:Tianjin University,2012.
[8]TORABIKALAKI R,GOMES A.Optimizing the coordinated charging of a group of electric vehicles[C]//2014IEEE Vehicle Power and Propulsion Conference(VPPC),October 27-30,2014,Coimbra,Portugal:6p.
[9]张洪财,胡泽春,宋永华.考虑时空分布的电动汽车充电负荷预测方法[J].电力系统自动化,2014,38(1):13-20.DOI:10.7500/AEPS20130613009.ZHANG Hongcai,HU Zechun,SONG Yonghua.A prediction method for electric vehicle charging load considering spatial and temporal distribution[J].Automation of Electric Power Systems,2014,38(1):13-20.DOI:10.7500/AEPS20130613009.
[10]李秋硕,肖湘宁,郭静.电动汽车有序充电方法研究[J].电网技术,2012,36(12):32-38.LI Qiushuo,XIAO Xiangning,GUO Jing.Research on scheme for ordered charging of electric vehicles[J].Power System Technology,2012,36(12):32-38.
[11]TANG W,BI S,ZHANG Y J.Online coordinated charging decision algorithm for electric vehicles without future information[J].IEEE Transactions on Smart Grid,2014,5(6):2810-2824.
[12]徐智威,胡泽春,宋永华.基于动态分时电价的电动汽车充电站有序充电策略[J].中国电机工程学报,2014,34(22):3638-3646.XU Zhiwei,HU Zechun,SONG Yonghua.Coordinated charging strategy for PEV charging stations based on dynamic time-of-use tariffs[J].Proceedings of the CSEE,2014,34(22):3638-3646.
[13]张静,汤奕,陈成.考虑分时电价和系统峰谷差动态约束的电动汽车有序充电策略[J].电网与清洁能源,2014,30(5):79-84.ZHANG Jing,TANG Yi,CHEN Cheng.Coordinated charging strategy for electric vehicles considering time-of-use price and peak-valley difference dynamic constraints[J].Power System and Clean Energy,2014,30(5):79-84.
[14]ZOU S,MA Z,LIU X,et al.An efficient game for coordinating electric vehicle charging[J].IEEE Transactions on Automatic Control,2017,62(5):2374-2389.
[15]朴龙健,艾芊,余志文.计及客户满意度的电动汽车多代理充电定价策略[J].电力系统自动化,2015,39(22):68-75.DOI:10.7500/AEPS20150103003.PIAO Longjian,AI Qian,YU Zhiwen.Multi-agent-based pricing strategy for electric vehicle charging considering customer satisfaction degree[J].Automation of Electric Power Systems,2015,39(22):68-75.DOI:10.7500/AEPS20150103003.
[16]杨晓东,任帅杰,张有兵,等.电动汽车可调度能力模型与日内优先调度策略[J].电力系统自动化,2017,41(2):84-93.DOI:10.7500/AEPS20160323006.YANG Xiaodong,REN Shuaijie,ZHANG Youbing,et al.Schedulable ability model and priority-based intraday scheduling strategy for electric vehicle[J].Automation of Electric Power Systems,2017,41(2):84-93.DOI:10.7500/AEPS20160323006.
[17]北京交通发展研究院.2016北京市交通发展年度报告[EB/OL].[2018-03-19].https://wenku.baidu.com/view/c0734791d05abe23482fb4daa58da0116d171f6d.html.Beijing Transport Institute.2016 annual report on traffic development in Beijing[EB/OL].[2018-03-19].https://wenku.baidu.com/view/c0734791d05abe23482fb4daa58da0116d171f6d.html.
[18]张良,严正,冯冬涵.采用两阶段优化模型的电动汽车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.Two-stage optimization model based coordinated charging for EV charging station[J].Power System Technology,2014,38(4):967-973.
[19]陈鹏,孟庆海,赵彦锦.基于蒙特卡洛法的电动汽车充电负荷计算[J].电气工程学报,2016,11(11):40-46.CHEN Peng,MENG Qinghai,ZHAO Yanjin.The electric vehicle charging load calculation based on the Monte Carlo method[J].Journal of Electrical Engineering,2016,11(11):40-46.
[20]刘自发,庞铖铖,魏建炜,等.基于IAHP和TOPSIS方法的负荷密度指标计算[J].电力系统自动化,2012,36(13):56-60.LIU Zifa,PANG Chengcheng,WEI Jianwei,et al.Index calculation of load density based on IAHP and TOPSISmethods[J].Automation of Electric Power Systems,2012,36(13):56-60.
[21]国网北京市电力公司.4440个公共充电桩明起执行峰谷电价[EB/OL].[2018-03-19].http://www.bj.sgcc.com.cn/html/main/col37/2016-06/15/20160615091559700402447_1.html.State Grid Beijing Electric Power Company.4440 public charging piles will carry out peak-valley price from tomorrow[EB/OL].[2018-03-19].http://www.bj.sgcc.com.cn/html/main/col37/2016-06/15/20160615091559700402447_1.html.