考虑风电消纳的电动汽车充电站有序充电控制

doi:10.19799/j.cnki.2095-4239.2020.0344

摘要/Abstract

摘要：

为实现电动汽车充电站对风电的充分利用，降低充电负荷对配网系统运行带来的负面影响，本工作提出一种考虑风电消纳的电动汽车充电优化策略。首先采用蒙特卡罗仿真法对不同数量电动汽车的充电负荷进行预测；然后，在综合考虑风电出力和电动汽车充电需求的基础上，根据风电功率的波动，动态调整分时电价，以包含充电负荷在内的配电网负荷峰谷差最小和用户充电花费最低为控制目标，建立电动汽车有序充电模型，采用改进的粒子群优化算法对模型求解，此外，通过与电动汽车直接接入配网充电的无序情形对比，结果表明，所提策略有效降低充电行为对配电网冲击的同时，能够直接促进风电消纳，提高用户充电的经济性。

关键词: 电动汽车, 风电消纳, 蒙特卡罗法, 有序充电

Abstract:

The grafting yield must be kept in a proper range to obtain a satisfactory gating property of membranes. An optimization strategy for EV charging with wind power consumption in mind was proposed to make full use of wind power in EV charging stations and reduce the negative impact of charging load on the distribution system operation. First, a Monte Carlo simulation method is used to predict the charging load of different numbers of EV. Then, considering wind power output and on the basis of the electric car charge demand, according to the fluctuation of wind power, we dynamically adjusted the time-of-use (TOU) pricing to include the charging load of the distribution network and user charge. With the lowest minimum peak valley load difference as the control target, a coordinated charging model is set up, using an improved particle swarm optimization algorithm to solve the model. In addition, through the electric vehicle charging directly connected to the distribution network of uncoordinated situation comparison, the results show that the proposed strategy on the impact of power distribution network at the same time effectively reduce the charging behavior can directly promote the wind power given, improve the economic benefit of charging users.

Key words: electric vehicle, wind energy accommodation, Monte Carlo simulation, coordinated charging

中图分类号:

TM 73

段俊东, 李高尚, 李一石, 付子恒, 黄泓叶. 考虑风电消纳的电动汽车充电站有序充电控制[J]. 储能科学与技术, 2021, 10(2): 630-637.

Jundong DUAN, Gaoshang LI, Yishi LI, Ziheng FU, Hongye HUANG. Coordinated charging control for EV charging stations considering wind power accommodation[J]. Energy Storage Science and Technology, 2021, 10(2): 630-637.

图/表 13

图1

图2

图3

图4

图5

图6

图7

图8

图9

表1

图10

图11

表2

参考文献 22

1	陈麒宇. 泛在电力物联网实施策略研究[J]. 发电技术, 2019, 40(2): 99-106.
	CHEN Qiyu. Research on the implementation strategy of ubiquitous power internet of things[J]. Power Generation Technology, 2019, 40(2): 99-106.
2	高赐威, 张亮. 电动汽车充电对电网影响的综述[J]. 电网技术, 2011, 35(2): 127-131.
	GAO Ciwei, ZHANG Liang. A Review of the impact of electric vehicle charging on the power grid[J]. Power System Technology, 2011, 35(2): 127-131.
3	RAGHVAN S S, KHALIGH A. Electrification potential factor: Energy-based value proposition analysis of plug-in hybrid electric vahicles[J]. IEEE Transactions on Vehicular Technology, 2012, 619(3): 1052-1059.
4	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): 1-10.
	HU Zechun, SONG Yonghua, XU Zhiwei, et al. Influence and Utilization of electric vehicles connected to power grid[J]. Proceedings of the CSEE, 2012, 32(4): 1-10.
5	PUTRUS G A, SUWANAPINGKARL P, JOHNSTON D, et al. Impact of electric vehicles on power distribution networks[C]//IEEE Vehicle Power and Propulsion Conference, Dearbom, USA, 2009: 827-831.
6	CLEMENT-NYNS K, HAESEN E, DRIESEN J. The impact of charging plug-in hybrid electric vehicles on a residential distribution grid[J]. IEEE Trans. on Power Systems, 2010, 25(1): 371-380.
7	杨冰, 王丽芳, 廖承林, 等. 分布式电动汽车有序充电控制系统模型[J]. 电力系统自动化, 2015, 39(20): 41-46.
	YANG Bing, WANG Lifang, LIAO Chenglin, et al. Model of distributed EV orderly charging control system[J]. Automation of electric Power Systems, 2015, 39(20): 41-46.
8	佟晶晶, 温俊强, 王丹, 等. 基于分时电价的电动汽车多目标优化充电策略[J]. 电力系统保护与控制, 2016, 44(1): 17-23.
	TONG Jingjing, WEN Junqiang, WANG Dan, et al. Multi-objective optimization charging strategy for EV based on time-of-use electricity price[J]. Power System Protection and Control, 2016, 44(1): 17-23.
9	QI Wei, XU Zhiwei, SHEN Zuojun, et al. Hierarchical coordinated control of plug-in electric vehicles charing in multifamily dwellings[J]. IEEE Transactions on Smart Grid, 2014, 5(3): 1465-1474.
10	杨晓东, 张有兵, 赵波, 等. 供需两侧协同优化的电动汽车充放电自动需求响应方法[J]. 中国机电工程学报, 2017, 37(1): 120-130.
	YANG Xiaodong, ZHANG Youbing, ZHAO Bo, et al. An automatic demand response method for charging and discharging of EV based on collaborative optimization of both supply and demand sides[J]. Proceedings of the CSEE, 2017, 37(1): 120-130.
11	AHMED Y S, GANESH K V. Plug-in vehicles and renewable energy sources for cost and emission reductions[J]. IEEE Transactions on Industrial Electronics, 2011, 58(4): 1229-1238.
12	AHMED Y S, GANESH K V. Resource scheduling under uncertainty in a smart grid with renewables and pulg-in vehicles[J]. IEEE Systems Journal, 2012, 6(1): 103-109.
13	苗轶群, 江全元, 曹一家. 基于微电网的电动汽车换电站运营策略[J]. 电力系统自动化, 2012, 36(15): 33-38.
	MIAO Yiqun, JIANG Quanyuan, CAO Yijia. Operation strategy for battery swap station of electric vehicles based on microg-rid[J].Automation of Electric Power Systems, 2012, 36(15): 33-38.
14	李正烁, 孙宏斌, 郭庆来, 等. 计及碳排放的输电网侧"风-车协调"研究[J]. 中国电机工程学报, 2012, 32(10): 41-48.
	LI Zhengshuo, SUN Hongbin, GUO Qinglai, et al. Study on wind-EV complementation on the transmission grid side considering carbon emission[J]. Proceedings of the CSEE, 2012, 32(10): 41-48.
15	于大洋, 黄海丽, 雷鸣, 等. 电动汽车充电与风电协调调度的碳减排效益分析[J]. 电力系统自动化, 2012, 36(10): 14-18.
	YU Dayang, HUANG Haili, LEI Ming, et al. CO₂ reduction benfit by coordinated dispatch of electric vehicle chaging and wind power[J]. Automation of Electric Power Systems, 2012, 36(10): 14-18.
16	赵俊华, 文福拴, 薛禹胜, 等. 计及电动汽车和风电出力不确定性的随机经济调度[J]. 电力系统自动化, 2010, 37(20): 20-29.
	ZHAO Junhua, WEN Fushuan, XUE Yusheng, et al. Stochastic economic scheduling with uncertainties of EV and wind power output included[J]. Automation of electric Power Systems, 2010, 37(20): 20-29.
17	于大洋, 宋曙光, 张波, 等. 区域电网电动汽车充电与风电协调调度的分析[J]. 电力系统自动化, 2011, 35(14): 24-29.
	YU Dayang, SONG Shuguang, ZHANG Bo, et al. Analysis on the coordinated dispatching of electric vehicle charging and wind power in regional power grid[J]. Automation of Electric Power Systems, 2011, 35(14): 24-29.
18	CASASOLA-AIGNESBERGER L, MARTINEZ S. Eletric vehicle recharge strategies for frequency control in electrical power systems with high wind power genration[C]//2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe, 2020.
19	ZHU Yongsheng, GAO Hongyang, XIAO Junming, et al. Dynamic multi-objective dispatch considering wind power and electric vehicles with probabilistic characteristics[J]. IEEE Access, 2019, 7: 185634-185653.
20	RAOOFAT M, SAAD M, LEFEBVRE S, et al. Wind power smoothing using demand response of electric vehicles[J]. International Journal of Electrical Power and Energy Systems, 2018, 99(7): 164-174.
21	QIAO Baihao, LIU Jing. Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm[J]. Renewable Energy, 2020, 154(7): 316-336.
22	常小强, 宋政湘, 王建华. 基于蒙特卡罗算法的电动汽车充电负荷预测及系统开发[J]. 高压电器, 2020, 56(8): 1-5.
	CHANG Xiaoqiang, SONG Zhengxiang, WANG Jianhua. Charging load prediction and system development of electric vehicles based on Monte Carlo Algorithm[J]. High Voltage Apparatus, 2020, 56(8): 1-5.

电价所属时段	具体时段	充电电价/元
高电价	4，5，6，7，8，11，12，13，14	1.28
平电价	3，10，15，16，17，18	0.8
低电价	1，2，9，19，20，21，22，23，24	0.32

[1]	武光华, 李宏胜, 李飞, 陈博, 张世科. 考虑时间相关性的电动汽车全生命周期碳排放量预测[J]. 储能科学与技术, 2022, 11(7): 2206-2212.
[2]	张岩, 韩伟, 宋闯, 杨双义. 含电动汽车的光储充一体化电站设施规划与运行联合优化[J]. 储能科学与技术, 2022, 11(5): 1502-1511.
[3]	王军, 阮琳, 邱彦靓. 锂离子电池低温快速加热方法研究进展[J]. 储能科学与技术, 2022, 11(5): 1563-1574.
[4]	刘偲艳, 胡毕华. 氢燃料汽车双向DC-DC变换器改进模型预测控制[J]. 储能科学与技术, 2021, 10(6): 2046-2052.
[5]	朱奕楠, 吕桃林, 赵芝芸, 杨文. 基于并行卡尔曼滤波器的锂离子电池荷电状态估计[J]. 储能科学与技术, 2021, 10(6): 2352-2362.
[6]	吴晓刚, 崔智昊, 孙一钊, 张锟, 杜玖玉. 电动汽车大功率充电过程动力电池充电策略与热管理技术综述[J]. 储能科学与技术, 2021, 10(6): 2218-2234.
[7]	陆燕娟, 陈友芹, 潘庭龙. 考虑EV和需求侧响应的社区微网能量管理[J]. 储能科学与技术, 2021, 10(2): 617-623.
[8]	王淮斌, 李阳, 王钦正, 杜志明, 冯旭宁. 电动汽车事故致灾机理及调查方法[J]. 储能科学与技术, 2021, 10(2): 544-557.
[9]	王栋, 郑莉莉, 李希超, 杜光超, 冯燕, 贾隆舟, 戴作强. 三元软包动力锂电池热安全性[J]. 储能科学与技术, 2020, 9(5): 1517-1525.
[10]	郑征, 高卫星, 张茜. 基于外部储能式动力电池放电均衡系统仿真研究[J]. 储能科学与技术, 2020, 9(4): 1167-1177.
[11]	郑海, 续彦芳, 刘汉涛, 陈凯, 桂文龙. 基于液体介质的锂离子动力电池热管理系统实验分析[J]. 储能科学与技术, 2020, 9(3): 885-891.
[12]	张骞, 武小兰, 白志峰, 程靖宜. 电动汽车混合储能系统自适应能量管理策略研究[J]. 储能科学与技术, 2020, 9(3): 878-884.
[13]	周　丹, 任志伟, 孙　可, 陈锡祥, 郑伟民. 复杂运营环境下快充型公交充电策略优化方法[J]. 储能科学与技术, 2020, 9(1): 195-203.
[14]	黄赛杰, 徐敏, 郑小鹿, 严晓, 黄碧雄. 动力电池充放电检测系统的设计与实现[J]. 储能科学与技术, 2019, 8(1): 146-154.
[15]	刘坚. 电动汽车退役电池储能应用潜力及成本分析[J]. 储能科学与技术, 2017, 6(2): 243-249.