Optimal Control Method of Charging Station with Energy Storage System Considering Dynamic Safety Margin of Second-Use Batteries

doi:10.16628/j.cnki.2095-8188.2020.07.006

Abstract

Abstract:

In order to meet the demand of echelon utilization brought by large-scale decommissioning of power battery in the near future,an optimal control method according to the battery health assessment model in the whole life cycle in the application scenario of charging station with energy storage system was proposed.With the optimal control method,the output power of echelon energy storage system was limited while the cycle life was effectively extended.The feasibility and effectiveness of the model was proved by the example analysis.

Key words: second-use batteries, dynamic safety margin, charging station with ESS, energy optimization

CLC Number:

TM631

XI Peifeng. Optimal Control Method of Charging Station with Energy Storage System Considering Dynamic Safety Margin of Second-Use Batteries[J]. LOW VOLTAGE APPARATUS, 2020, 592(7): 36-41.

Figures/Tables 8

References 25

[1]	何英. 梯次利用储能市场受追捧[EB/OL]. [2018-05-14]. http://www.escn.com.cn/news/show-523345.html.
[2]	动力电池梯次利用市场前景广阔[EB/OL]. [2018-01-30]. http://www.xinhuanet.com/energy/2018-06/21/c_1123011563.html.
[3]	新能源汽车动力蓄电池回收利用管理暂行办法[EB/OL]. [2018-07-02]. http://www.people.com.cn/n1/2018/0704/c1005-30126324.html.
[4]	李建林, 修晓青, 刘道坦, 等. 计及政策激励的退役动力电池储能系统梯次应用研究[J]. 高电压技术, 2015,41(8):2562-2568.
[5]	XIE S B, HU X S, QI S W, et al. Model predictive energy management for plug-in hybrid electric vehicles considering optimal battery depth of discharge[J]. Energy, 2019,4(173):667-678.
[6]	BAI L Q, LI F X, HU Q R, et al. Application of battery-supercapacitor energy storage system for smoothing wind power output:An optimal coordinated control strategy:2016 IEEE Power and Energy Society General Meeting (PESGM)[C]. 2016.
[7]	马泽宇, 姜久春, 文锋, 等. 用于储能系统的梯次利用锂电池组均衡策略设计[J]. 电力系统自动化, 2014,38(3):106-111. doi: 10.7500/AEPS20130330001
[8]	刘方, 杨秀, 时珊珊, 等. 考虑不确定因素下含充换储一体化电站的微网能量优化[J]. 电网技术, 2015,39(3):669-676. doi: 10.13335/j.1000-3673.pst.2015.03.013
[9]	奚培锋, 鞠晨. 电动公交车枢纽站补电模式及储充系统优化配置研究[J]. 电器与能效管理技术, 2019(20):77-82.
[10]	余晓玲, 靳文涛, 韩晓娟, 等. 基于退役动力电池梯次利用的光伏充电站容量配置[J]. 电器与能效管理技术, 2017(13):39-55.
[11]	李朝晖, 艾瑶瑶, 宋宁希, 等. 基于电池储能的光伏充电站经济性评估[J]. 电器与能效管理技术, 2018(1):33-38.
[12]	MORENO TORRES P, NAVARRO G, BLANCO M, et al. Power smoothing system for wave energy converters by means of a supercapacitor-based energy storage system:European Conference on Power Electronics and Applications[C]. 2015.
[13]	邹福强. 电动汽车光伏充电站的在线能量管理方法[D]. 北京:华北电力大学, 2016.
[14]	陈健, 王成山, 赵波, 等. 考虑储能系统特性的独立微电网系统经济运行优化[J]. 电力系统自动化, 2012,36(20):25-31.
[15]	吴鸣, 孙丽敬, 寇凌峰, 等. 考虑需求侧响应的主动配电网电池梯次储能的容量配置方法[J]. 高电压技术, 2020,46(1):71-79.
[16]	杨艳红, 裴玮, 邓卫, 等. 计及蓄电池储能寿命影响的微电网日前调度优化[J]. 电工技术学报, 2015,30(22):172-180.
[17]	SCHIFFER J, SAUER D U, BINDNER H, et al. Model prediction for ranking lead-acid batteries according to expected lifetime in renewable energy systems and autonomous power-supply systems[J]. Journal of Power Sources, 2007,168(1):66-78. doi: 10.1016/j.jpowsour.2006.11.092
[18]	DROUILHET S, JOHNSON B L. A battery life prediction method for hybrid power applications:AIAA Aerospace Sciences Meeting and Exhibit[C]. 1997.
[19]	SARASKETA Z E, GANDIAGA I, RODRIGUEZ M L M, et al. Calendar ageing analysis of a LiFePO4/graphite cell with dynamic model validations:towards realistic lifetime predictions[J]. Journal of Power Sources, 2014,2(272):45-47.
[20]	DOHRMANN C R, ROBINETT R D. Dynamic programming method for constrained discrete-time optimal control[J]. Journal of Optimization Theory and Applications, 1999,101(2):259-283. doi: 10.1023/A:1021733425632
[21]	颜宁, 李相俊, 张博, 等. 基于电池健康度的微电网群梯次利用储能系统容量配置方法[J]. 电网技术, 2020,44(5):1630-1638.
[22]	韩晓娟, 张婳, 修晓青, 等. 配置梯次电池储能系统的快速充电站经济性评估[J]. 储能科学与技术, 2016,5(4):514-521.
[23]	赵书涛, 李云鹏, 王二旭, 等. 基于电-振信号熵权特征的断路器储能机构故障诊断方法[J]. 高压电器, 2019,55(11):204-210.
[24]	潘福荣, 张建赟, 周子旺, 等. 用户侧电池储能系统的成本效益及投资风险分析[J]. 浙江电力, 2019,38(5):43-49.
[25]	蒋永梅, 张谦, 金武杰. 一种利用超级电容储能系统实现直驱风电机组高电压穿越的新方案[J]. 浙江电力, 2018,37(8):54-58.

参数名称	参数值
变压器配置容量P_T/kVA	1 600
梯次储能系统P_ba、E_b	0.5 MW×1 h
储能裕度基本限制[SOC_min,SOC_max]	[0.2,0.8]

时段	分时电价/(元/kWh)
6∶00~8∶00	0.607
8∶00~11∶00	0.995
11∶00~18∶00	0.607
18∶00~21∶00	0.995
21∶00~22∶00	0.607
22∶00~次日6∶00	0.214