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1. 四川大学 电气信息学院四川,成都,610065
2. 国网福建省电力有限公司 电力科学研究院福建,福州,350007
3. 国网福建省电力有限公司 厦门供电公司福建,厦门,361000
纸质出版日期:2017,
网络出版日期:2016-12-19,
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吕林,许威,向月,张逸,熊军.基于马尔科夫链充电负荷预测的多区域充电桩优化配置研究[J].工程科学与技术,2017,49(3):170-178.
LYU Lin, XU Wei, XIANG Yue, et al. Optimal Allocation of Charging Piles in Multi-areas Considering Charging Load ForecastingBased on Markov Chain[J]. Advanced Engineering Sciences, 2017,49(3):170-178.
吕林,许威,向月,张逸,熊军.基于马尔科夫链充电负荷预测的多区域充电桩优化配置研究[J].工程科学与技术,2017,49(3):170-178. DOI: 10.15961/j.jsuese.201600357.
LYU Lin, XU Wei, XIANG Yue, et al. Optimal Allocation of Charging Piles in Multi-areas Considering Charging Load ForecastingBased on Markov Chain[J]. Advanced Engineering Sciences, 2017,49(3):170-178. DOI: 10.15961/j.jsuese.201600357.
中文摘要: 考虑用户出行习惯的复杂性、多样性,对区域充电桩进行合理的配置以满足充电需求。首先,通过马尔科夫链模型描述电动汽车用户一天出行过程中在行驶、充电、不充电也不行驶3种决策行为下,动力电池荷电状态的变化情况。以此确定该过程中电动汽车用户的实时充电行为,得出不同类型电动汽车的快充、慢充负荷需求。然后,考虑规划区内电动汽车的移动特性及其不同时段不同类型电动汽车辆数,预测各区域各时段充电负荷的需求情况。最后,以投资、运维成本最小为目标建立区域充电桩优化配置模型。该模型计及了电动汽车移动特性均衡等约束条件,并通过粒子群优化算法求解。对33节点4区域系统电动汽车充电负荷需求预测及其充电桩配置进行仿真,仿真结果验证了所提方法的有效性和可行性。
Abstract:Considering the complexity and diversity of customers' travel habits
the charging piles need to be allocated appropriately to satisfy the charging demand.Firstly
Markov chain is used to describe the variation of battery state of charge on electric vehicle owners' trip in the whole day
according to three decision-making behavior including driving
charging
neither charging nor driving.Then the real-time charging behavior in the process could be determinated
which indicates the fast and slow charging demand of different vehicle types.Considering mobility characteristics of electric vehicles and the number of different types of electric vehicles in different time periods in some area
the total load demand could be forecasted.The optimal allocation model for charging piles is proposed and aims to minimize investment and operating costs for the charging piles.The mobility characteristics of electric vehicles are integrated into the constraints
and the model is solved by the particle swarm optimization algorithm.The effectiveness and feasiblility of the proposed method are verified by the 33-bus four-area case study on the charging load forecasting and optimal allocation of charing piles.
电动汽车马尔科夫链负荷需求移动特性充电桩
electric vehicleMarkov chaincharging demandmobility characteristicscharging piles
Feng Lin,Zhang Jingning,Li Guojie,et al.Cost reduction of a hybrid energy storage system considering correlation between wind and PV power[J].Protection and Control of Modern Power Systems,2016(1):1-9. [DOI:10.1186/s41601-016-0021-1]
Liu Junyong,Xiang Yue,Yang Wei,et al..Key technology analysis and study for charging and swapping service network and its coordinated planning with distribution network[J]..Electric Power Construction,2015,36(7):47-55..[刘俊勇,向月,杨威,等.充换电服务网络及其与配电网协同规划关键技术分析与研究[J].电力建设,2015,36(7):47-55.]
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.[李如琦,苏浩益.基于排队论的电动汽车充电桩优化配置.电力系统自动化,2011,35(14):58-61.]
Tang Xiangang,Liu Junyong,Liu Youbo,et al.Electric vehicle charging station planning based on computational geometry method[J].Automation of Electric Power Systems,2012,36(8):24-30.[唐现刚,刘俊勇,刘友波,等.基于计算几何方法的电动汽车充电站规划[J].电力系统自动化,2012,36(8):24-30.]
Qian Kejun,Zhou Chengke,Allan M,et al.Modeling of load demand due to EV battery charging in distribution systems[J].IEEE Transactions on Power Systems,2011,26(2):802-810.
Tian Liting,Shi Shuanglong,Jia Zhuo.A statistical model or charging power demand of electric vehicles[J].Power System Technology,2010,34(11):126-130.[田立亭,史双龙,贾卓.电动汽车充电功率需求的统计学建模方法[J].电网技术,2010,34(11):126-130.]
Luo Zhuowei,Hu Zechun,Song Yonghua,et al.Study on plug-in electric vehicles charging load calculating[J].Automation of Electric Power Systems,2011,35(14):36-42.[罗卓伟,胡泽春,宋永华,等.电动汽车充电负荷计算方法[J].电力系统自动化,2011,35(14):36-42.]
Zhang Hongcai,Hu Zechun,Song Yonghua,et al.A prediction method for electric vehicle charging load considering spatial and temporal distribution[J].Automation of Electric Power Systems 2014,38(1):13-20.[张洪财,胡泽春,宋永华,等.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.]
Wang Xiaoyin,Liu Junyong,Tang Xiangang,et al.Study on coordinated charging of electric based on spatial load forecasting[J].Zhejiang Electric Power,2014,(2):7-13.[王晓寅,刘俊勇,唐现刚,等.基于空间负荷预测的电动汽车有序充电方法研究[J].浙江电力,2014,(2):7-13.]
Xiong Hu,Xiang Tieyuan,Zhu Yonggang,et al.Electric vehicle public charging station location optimal planning[J].Automation of Electric Power Systems,2012,36(20):1-6.[熊虎,向铁元,祝勇刚,等.电动汽车公共充电站布局的最优规划[J].电力系统自动化,2012,36(20):1-6.]
Kou Lingfeng,Liu Zifa,Zhou Huan.Modeling algorithm of charging station planning for regional electric vehicle[J].Modern Electric Power,2010,27(4):44-48.[寇凌峰,刘自发,周欢.区域电动汽车充电站规划的模型与算法[J].现代电力,2010,27(4):44-48.]
Ren Yulong,Shi Lefeng,Zhang Qian,et al.Optimal distribution and scale of charging stations for electric vehicles[J].Automation of Electric Power Systems,2011,35(14):53-57.[任玉珑,史乐峰,张谦,等.电动汽车充电站最优分布和规模研究[J].电力系统自动化,2011,35(14):53-57.]
Cruz-Zambrano M,Corchero C,Igualada-Gonzalez L,et al.Optimal location of fast charging stations in Barcelon:a flow-capturing approach[C]//Proceedings of the 10th International Conferenceonthe European Energy Market (EEM).Stockholm,Sweden:IEEE,2013:1–6.
Tao Shu,Xiao Xiangnin,Wen Jianfeng,et al.Configuration ratio for distributed electrical vehicle charging infrastructures[J].Transactions of China electrotechnical society,2014,29(8):11-19.[陶顺,肖湘宁,温剑锋,等.电动汽车分散充电桩配比度分析与计算方法[J].电工技术学报,2014,29(8):11-19.]
Grahn P,Munkhammar J,Widen J,et al.PHEV home charging model based on residential activity patterns[J].IEEE Transactions on Power Systems,2013,28(3):2507-2515.
Wu Di,Aliprantis D C,Gkritza K.Electric energy and power consumption by light-duty plug-in electric vehicles[J].IEEE Transactions on Power Systems.,2011,26(2):738-746.
Santos A,McGuckin N,Nakamoto H Y,et al.Summary of travel trends:2009 national household travel survey[R].Washington,DC:U.S. Department of Transportation,2011.
Xiang Yue,Liu Junyong,Tang Shuoya,et al.A traffic flow based planning strategy for optimal siting and sizing of charging stations[C]//Proceedings of IEEE PES 2015 Asia-Pacific Power and Energy Conference.Brisbane,Australia:IEEE,2015:1–5.
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