基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略

蒋怡静; 于艾清; 屠亚南

基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略

上海电力大学电气工程学院,上海 200090

基金项目: 上海市绿色能源并网工程技术研究中心项目(13DZ2251900)

详细信息

作者简介:
蒋怡静(1994—),女,硕士研究生,研究方向为电动汽车有序充放电调度,E-mail:jiang_yijing@mail.shiep.edu.cn;于艾清(1981—),女,副教授,研究生导师,研究方向为电力系统规划与调度、电力电子系统及其智能控制技术, E-mail:yuaiqing@shiep.edu.cn;屠亚南(1990—),女,硕士研究生,研究方向为智能优化算法,E-mail:15638215107@163.com。

中图分类号: TM732

Coordinated Charging Strategy for Electric Vehicles in Temporal-spatial Dimension Based on IBQPSO Algorithm

School of Electric Power Engineering,Shanghai University of Electric Power, Shanghai 200090, China

摘要: 大规模电动汽车的无序充电会影响电网的安全经济运行,以车联网系统为基础,提出电动汽车的充电行为引导策略。充电站运营商按用户在时间和空间上接受充电引导所起的作用对于整体调度作用的贡献程度,分别对用户进行费用补偿,在此基础上建立时空双尺度有序充电引导模型。其次,提出一种IBQPSO算法求解规划问题。最后,通过具体算例对模型进行仿真,结果能满足电网、充电站运营商和电动汽车用户三方的利益,表明了模型与算法的可行性与有效性。
- 电动汽车 /
- 时空双尺度 /
- 多方利益 /
- 有序充电 /
- BQPSO改进算法
Abstract: The disorderly charging of large-scale electric vehicles will affect the safe and economic operation of the power grid. The charging behavior of electric vehicles needs to be guided by the cost compensated by the charging station operator according to contribution of user’s guided charging behavior in temporal and spatial levels to the grid scheduling. Based on this, a temporal-spatial charging guidance model is established. Then, an IBQPSO algorithm is proposed based on Bloch sphere to solve the model. Finally, the simulated results of a specific example show that the interests of the grid, charging station operators and electric vehicle users can be meet, and the feasibility and effectiveness of the model and algorithm are verified.
- electric vehicles /
- temporal-spatial dimension /
- the interests of multi-party /
- coordinated charging /
- improved BQPSO algorithm

[1]	LOPES J A P, SOARES F J, ALMEIDA P M R. Integration of electric vehicles in the electric power system[J]. Proceedings of the IEEE, 2011, 99(1): 68183.
[2]	胡泽春,宋永华,徐智威,等.电动汽车接入电网的影响与利用[J]. 中国电机工程学报,2012,32(4):110. HU Zechun, SONG Yonghua, XU Zhiwei, et al.Impacts and utilization of electric vehicles integration into power systems[J].Proceedings of the CSEE, 2012, 32(4):110.
[3]	ATIA R, YAMADA N. More accurate sizing of renewable energy sources under high levels of electric vehicle integration [J].Renewable Energy, 2015,81: 918925.
[4]	常方宇,黄梅,张维戈.分时充电价格下电动汽车有序充电引导策略[J].电网技术,2016,40(9):26092615. CHANG Fangyu, HUANG Mei, ZHANG Weige. Research on coordinated charging of electric vehicles based on TOU charging price[J]. Power System Technology, 2016,40(9):26092615.
[5]	徐智威,胡泽春,宋永华,等.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):36383647. XU Zhiwei, HU Zechun, SONG Yonghua, et al. Coordinated charging strategy for PEV charging stations based on dynamic time-of-use tariffs[J].Proceedings of the CSEE,2014, 34(22):36383647.
[6]	牛利勇,张帝,王晓峰,等.基于自适应变异粒子群算法的电动出租车充电引导[J].电网技术,2015,39(1):6368. NIU Liyong, ZHANG Di, WANG Xiaofeng, et al.An adaptive particle mutation swarm optimization based electric taxi charging guidance[J].Power System Technology,2015,39(1):6368.
[7]	黄晶,杨健维,王湘,等.下一目的地导向下的电动汽车充电引导策略[J].电网技术,2017,7(41): 21732181. HUANG Jing, YANG Jianwei, WANG Xiang, et al. Destination oriented electric vehicle charging guiding strategy[J].Power System Technology,2017, 7(41): 21732181.
[8]	陈丽丹,张尧,ANTONIO Figueiredo.融合多源信息的电动汽车充电负荷预测及其对配电网的影响[J/OL].电力自动化设备,2018,38(12):110. CHEN Lidan, ZHANG Yao, ANTONIO Figueiredo. Charging load forecasting of electric vehicles based on multi-source information fusion and its influence on distribution network[J/OL]. Electric Power Automation Equipment,2018,38(12):110.
[9]	罗禹贡,严弈遥,朱陶,等,智能电动车辆最优充电路径规划方法[J].工程研究—跨学科视野中的工程,2014,6(1):9298. LUO Yugong,YAN Yiyao,ZHU Tao,et al.Optimal charging station recommendation method for intelligent electric vehicle[J]. Journal of Engineering Studies,2014, 6(1):9298.
[10]	李盼池,王海英.基于Bloch球面坐标编码的量子粒子群算法及应用[J].计算机系统应用,2012,21(8):7684. LI Panchi, WANG Haiying. Bloch coordinates-based quantum particle swarm optimization algorithm and its application[J].Computer Systems and applications,2012, 21(8): 7684.
[11]	黄敏丽,于艾清.基于改进布谷鸟算法的电动汽车换电站有序充电策略研究[J].中国电机工程学报,2018,38(4):10751083. HUANG Minli, YU Aiqing. Study on coordinated charging strategy for battery swapping station based on improved cuckoo search algorithm[J]. Proceedings of the CSEE,2018,38(4):1075 1083.
[12]	GUO Qinglai, XIN Shujun, SUN Hongbin, et al. Rapid-charging navigation of electric vehicles based on real-time power systems and traffic data[J].IEEE Trans on Smart Grid,2014,5(4):19691979.
[13]	宋永华,阳岳希,胡泽春.电动汽车电池的现状及发展趋势[J].电网技术,2011,35(4):17. SONG Yonghua, YANG Yuexi, HU Zechun. Present status and development trend of batteries for electric vehicles[J]. Power System Technology, 2011,35(4):17.
[14]	郑竞宏,戴梦婷,张曼,等. 住宅区式电动汽车充电站负荷集聚特性及其建模[J].中国电机工程学报,2012,32(22):3238. ZHENG Jinghong, DAI Mengting, ZHANG Man, et al. Load clusters characteristic and modeling of EV charge station in residential district[J]. Proceedings of the CSEE,2012,32(22): 3238.

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基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略

Coordinated Charging Strategy for Electric Vehicles in Temporal-spatial Dimension Based on IBQPSO Algorithm

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基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略

上海电力大学电气工程学院,上海 200090

English Abstract

Coordinated Charging Strategy for Electric Vehicles in Temporal-spatial Dimension Based on IBQPSO Algorithm

School of Electric Power Engineering,Shanghai University of Electric Power, Shanghai 200090, China

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基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略

Coordinated Charging Strategy for Electric Vehicles in Temporal-spatial Dimension Based on IBQPSO Algorithm

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基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略

上海电力大学电气工程学院,上海 200090

English Abstract

Coordinated Charging Strategy for Electric Vehicles in Temporal-spatial Dimension Based on IBQPSO Algorithm

School of Electric Power Engineering,Shanghai University of Electric Power, Shanghai 200090, China

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