

浏览全部资源
扫码关注微信
1.省部共建电工装备可靠性与智能化国家重点实验室(河北工业大学),天津市 300131
2.国网江苏省电力有限公司电力科学研究院,江苏省南京市 211130
3.智能电网教育部重点实验室(天津大学),天津市 300072
Received:21 April 2023,
Revised:2023-08-25,
Published Online:17 November 2023,
Published:10 July 2024
移动端阅览
董晓红,孔华志,丁飞等.考虑电池老化的电动汽车中长期充电负荷预测方法[J].电力系统自动化,2024,48(13):109-119.
DONG Xiaohong,KONG Huazhi,DING Fei,et al.Medium- and Long-term Charging Load Forecasting Method for Electric Vehicles Considering Battery Aging[J].Automation of Electric Power Systems,2024,48(13):109-119.
董晓红,孔华志,丁飞等.考虑电池老化的电动汽车中长期充电负荷预测方法[J].电力系统自动化,2024,48(13):109-119. DOI: 10.7500/AEPS20230421001.
DONG Xiaohong,KONG Huazhi,DING Fei,et al.Medium- and Long-term Charging Load Forecasting Method for Electric Vehicles Considering Battery Aging[J].Automation of Electric Power Systems,2024,48(13):109-119. DOI: 10.7500/AEPS20230421001.
随着电动汽车市场份额逐年上升,受限于区域内动力电池容量大小的电动汽车充电负荷占总用电负荷的比例不断提高。为此,提出一种考虑电池老化的电动汽车中长期充电负荷预测方法。首先,构建考虑电池老化的区域电动汽车电池总容量预测模型,预测电池老化带来的总容量衰减以及更换新电池和车辆数目增长带来的总容量上升。其次,构建考虑温度变化的动力电池老化特性估计模型,预估每次充电后电池最大容量、可充电量和续航电量,当电池最大容量不足以保证车辆安全运行时,对车辆更换新电池。最后,构建考虑充电成本的车辆行为仿真模型,模拟车辆出行和充电过程;借助模糊
C
均值法对不同种类电动汽车充电负荷进行划分,通过蒙特卡洛模拟与线性加权确定区域内电动汽车中长期负荷。仿真结果表明,随着车辆使用时间的增加,年负荷曲线波动程度不断变大;相较于新车,电池老化后单位车辆周均用电负荷峰值出现的时间会提前,且负荷峰谷差也会增大。
As the market share of electric vehicles continues to grow annually
the proportion of electric vehicle charging load limited by the capacity of power battery in the region to the total electricity load continues to increase. To this end
this paper proposes a medium- and long-term charging load forecasting method for electric vehicles considering battery aging. First
a total capacity forecasting model for electric vehicle batteries in the rigion considering battery aging is constructed to forecast the total capacity attenuation caused by battery aging
as well as the total capacity increase caused by the replacement with new batteries and the growth in the number of the vehicles. Then
an estimation model for the aging characteristics of power batteries considering temperature changes is constructed to estimate the maximum capacity
rechargeable capacity and driving range of the battery after each charging cycle. When the maximum capacity of the battery is insufficient to ensure the safe operation of the vehicle
it is replaced with a new one. Finally
a vehicle behavior simulation model considering charging costs is constructed to simulate both vehicle travel and charging processes. By using the fuzzy
C
-means method t
o partition different kinds of charging loads of electric vehicles
the medium- and long-term loads of electric vehicles in the region are determined through Monte Carlo simulation and linear weighting. The simulation results show that as the vehicle usage time increases
the fluctuation degree of the annual load curve continues to increase. Compared with new vehicles
after battery aging
the peak time of weekly electricity load of single vehicle will be earlier
and the peak-to-valley differences of loads will also increase.
郑远硕 , 李峰 , 董九玲 , 等 . “车-路-网”模式下电动汽车充放电时空灵活性优化调度策略 [J]. 电力系统自动化 , 2022 , 46 ( 12 ): 88 - 97 .
ZHENG Yuanshuo , LI Feng , DONG Jiuling , et al . Optimal dispatch strategy of spatio-temporal flexibility for electric vehicle charging and discharging in vehicle-road-grid mode [J]. Automation of Electric Power Systems , 2022 , 46 ( 12 ): 88 - 97 .
DABBAGHJAMANESH M , MOEINI A , KAVOUSI-FARD A . Reinforcement learning-based load forecasting of electric vehicle charging station using Q -learning technique [J]. IEEE Transactions on Industrial Informatics , 2021 , 17 ( 6 ): 4229 - 4237 .
李恒杰 , 朱江皓 , 傅晓飞 , 等 . 基于集成学习的电动汽车充电站超短期负荷预测 [J]. 上海交通大学学报 , 2022 , 56 ( 8 ): 1004 - 1013 .
LI Hengjie , ZHU Jianghao , FU Xiaofei , et al . Ultra-short-term load forecasting of electric vehicle charging stations based on ensemble learning [J]. Journal of Shanghai Jiao Tong University , 2022 , 56 ( 8 ): 1004 - 1013 .
刘文霞 , 龙日尚 , 徐晓波 , 等 . 考虑数据新鲜度和交叉熵的电动汽车短期充电负荷预测模型 [J]. 电力系统自动化 , 2016 , 40 ( 12 ): 45 - 52 .
LIU Wenxia , LONG Rishang , XU Xiaobo , et al . Forecasting model of short-term EV charging load based on data freshness and cross entropy [J]. Automation of Electric Power Systems , 2016 , 40 ( 12 ): 45 - 52 .
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 .
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 .
YANG W , XIANG Y , LIU J Y , et al . Agent-based modeling for scale evolution of plug-in electric vehicles and charging demand [J]. IEEE Transactions on Power Systems , 2018 , 33 ( 2 ): 1915 - 1925 .
赵堃 , 李晓婷 , 李远卓 , 等 . 考虑电动汽车充电需求的城市配电网负荷预测 [J]. 华北电力技术 , 2017 ( 11 ): 1 - 5 .
ZHAO Kun , LI Xiaoting , LI Yuanzhuo , et al . Urban distribution network load forecasting considering electric vehicle charging demand [J]. North China Electric Power , 2017 ( 11 ): 1 - 5 .
李科 , 皇甫霄文 , 李梦超 , 等 . 光-储一体电动汽车充电站储能规划 [J]. 电力系统及其自动化学报 , 2023 , 35 ( 8 ): 82 - 93 .
LI Ke , HUANGFU Xiaowen , LI Mengchao , et al . Energy storage planning for integrated PV-energy storage electric vehicle charging station [J]. Proceedings of the CSU-EPSA , 2023 , 35 ( 8 ): 82 - 93 .
刘志强 , 张谦 , 朱熠 , 等 . 计及车-路-站-网融合的电动汽车充电负荷时空分布预测 [J]. 电力系统自动化 , 2022 , 46 ( 12 ): 36 - 45 .
LIU Zhiqiang , ZHANG Qian , ZHU Yi , et al . Spatial-temporal distribution prediction of charging loads for electric vehicles considering vehicle-road-station-grid integration [J]. Automation of Electric Power Systems , 2022 , 46 ( 12 ): 36 - 45 .
黄学劲 , 钟锦星 , 路京雨 , 等 . 基于用户画像的电动汽车充电负荷预测方法 [J]. 吉林大学学报(工学版) , 2023 , 53 ( 8 ): 2193 - 2200 .
HUANG Xuejin , ZHONG Jinxing , LU Jingyu , et al . Electric vehicle charging load forecasting method based on user portrait [J]. Journal of Jilin University (Engineering and Technology Edition) , 2023 , 53 ( 8 ): 2193 - 2200 .
于海东 , 张焰 , 潘爱强 . 电动私家车充电负荷中长期推演模型 [J]. 电力系统自动化 , 2019 , 43 ( 21 ): 80 - 87 .
YU Haidong , ZHANG Yan , PAN Aiqiang . Medium- and long-term evolution model of charging load for private electric vehicle [J]. Automation of Electric Power Systems , 2019 , 43 ( 21 ): 80 - 87 .
华远鹏 , 王圆圆 , 韩丁 , 等 . 考虑有序充电的居民区电动汽车中长期充电负荷预测 [J]. 电力系统及其自动化学报 , 2022 , 34 ( 6 ): 142 - 150 .
HUA Yuanpeng , WANG Yuanyuan , HAN Ding , et al . Mid-and long-term charging load forecasting for electric vehicles in residential areas considering orderly charging [J]. Proceedings of the CSU-EPSA , 2022 , 34 ( 6 ): 142 - 150 .
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 .
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 .
牛牧童 , 廖凯 , 杨健维 , 等 . 考虑季节特性的多时间尺度电动汽车负荷预测模型 [J]. 电力系统保护与控制 , 2022 , 50 ( 5 ): 74 - 85 .
NIU Mutong , LIAO Kai , YANG Jianwei , et al . Multi-time-scale electric vehicle load forecasting model considering seasonal characteristics [J]. Power System Protection and Control , 2022 , 50 ( 5 ): 74 - 85 .
中华人民共和国中央人民政府 . 国务院办公厅印发《新能源汽车产业发展规划(2021—2035)》 [EB/OL].( 2020-11-02 )[ 2023-01-01 ]. https://www.gov.cn/xinwen/2020-11/02/content_5556762.htm https://www.gov.cn/xinwen/2020-11/02/content_5556762.htm .
The Central People’s Government of the People’s Republic of China . The General Office of the State Council issued the “Development Planning for New Energy Vehicle Industry ( 2021 — 2035 )”[EB/OL]. ( 2020-11-02 )[ 2023-01-01 ]. https://www.gov.cn/xinwen/2020-11/02/content_5556762.htm https://www.gov.cn/xinwen/2020-11/02/content_5556762.htm .
王帅 , 尹忠东 , 郑重 , 等 . 基于电压曲线的退役电池模组分选方法 [J]. 中国电机工程学报 , 2020 , 40 ( 8 ): 2691 - 2705 .
WANG Shuai , YIN Zhongdong , ZHENG Zhong , et al . A sorting method for retired battery modules based on voltage curves [J]. Proceedings of the CSEE , 2020 , 40 ( 8 ): 2691 - 2705 .
万仁美 . 2023年动力电池产业联盟大会专家观点撷英 [N]. 中国汽车报 , 2023-05-04 (010).
WAN Renmei . Experts’ opinion on the 2023 Power Battery Industry Alliance Conference [N]. China Automotive News , 2023-05-04 (010).
郭磊 . 考虑不确定性的电动汽车充电设施与配电系统协同规划研究 [D]. 郑州 : 郑州大学 , 2020 .
GUO Lei . Collaborative planning of EV charging facilities and distribution power system considering uncertainty factors [D]. Zhengzhou : Zhengzhou University , 2020 .
董彦君 , 闫志杰 , 马喜平 , 等 . 基于加权Voronoi图和自适应PSO算法的电动汽车充换电站联合规划 [J]. 电源学报 , 2018 , 16 ( 4 ): 71 - 79 .
DONG Yanjun , YAN Zhijie , MA Xiping , et al . Joint planning of EV charging and battery swapping stations based on weighted Voronoi diagram and adaptive PSO algorithm [J]. Journal of Power Supply , 2018 , 16 ( 4 ): 71 - 79 .
周杰 , 南东亮 , 耿保华 , 等 . 基于改进飞蛾扑火算法的BP神经网络蓄电池寿命预测 [J]. 电工技术 , 2020 ( 17 ): 21 - 23 .
ZHOU Jie , NAN Dongliang , GENG Baohua , et al . Battery life prediction of BP neural network based on improved moth-flame optimization algorithm [J]. Electric Engineering , 2020 ( 17 ): 21 - 23 .
ZHENG Y C , SHAO Z Y , ZHANG Y M , et al . A systematic methodology for mid-and-long term electric vehicle charging load forecasting: the case study of Shenzhen, China [J]. Sustainable Cities and Society , 2020 , 56 : 102084 .
WANG J , LIU P , HICKS-GARNER J , et al . Cycle-life model for graphite-LiFePO 4 cells [J]. Journal of Power Sources , 2011 , 196 ( 8 ): 3942 - 3948 .
BLOOM I , COLE B W , SOHN J J , et al . An accelerated calendar and cycle life study of Li-ion cells [J]. Journal of Power Sources , 2001 , 101 ( 2 ): 238 - 247 .
陈芬放 . 高能量密度NCA正极锂离子电池老化过程产热特性研究 [D]. 杭州 : 浙江大学 , 2021 .
CHEN Fenfang . Study on the heat generation characteristics of high-specific-energy lithium ion batteries with NCA cathode during aging [D]. Hangzhou : Zhejiang University , 2021 .
闫啸宇 , 周思达 , 卢宇 , 等 . 锂离子电池容量衰退机理与影响因素 [J]. 北京航空航天大学学报 , 2023 , 49 ( 6 ): 1402 - 1413 .
YAN Xiaoyu , ZHOU Sida , LU Yu , et al . Degradation mechanism and influencing factors on lithium-ion batteries [J]. Journal of Beijing University of Aeronautics and Astronautics , 2023 , 49 ( 6 ): 1402 - 1413 .
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 .
TIAN Liting , SHI Shuanglong , JIA Zhuo . A statistical model for charging power demand of electric vehicles [J]. Power System Technology , 2010 , 34 ( 11 ): 126 - 130 .
张恒嘉 . 基于实证的纯电动汽车性能评估方法和普及可能性研究 [D]. 武汉 : 武汉理工大学 , 2014 .
ZHANG Hengjia . Study on the assessing methods and the possibility of popularity of pure electric vehicles based on the empirical test [D]. Wuhan : Wuhan University of Technology , 2014 .
李文华 , 贾玉雯 , 范新涛 . 基于改进的模糊c-均值聚类算法的负荷特性指标分析与分类 [J]. 燕山大学学报 , 2016 , 40 ( 3 ): 230 - 235 .
LI Wenhua , JIA Yuwen , FAN Xintao . Index analysis and classification of load characteristics based on improved fuzzy c-means algorithm [J]. Journal of Yanshan University , 2016 , 40 ( 3 ): 230 - 235 .
李杰 , 徐勇 , 朱昭贤 , 等 . 模糊C均值算法参数仿真研究 [J]. 系统仿真学报 , 2008 , 20 ( 2 ): 509 - 513 .
LI Jie , XU Yong , CHU Zhaoxian , et al . Simulation research on parameters of fuzzy C-means algorithm [J]. Journal of System Simulation , 2008 , 20 ( 2 ): 509 - 513 .
YANG X G , LENG Y J , ZHANG G S , et al . Modeling of lithium plating induced aging of lithium-ion batteries: transition from linear to nonlinear aging [J]. Journal of Power Sources , 2017 , 360 : 28 - 40 .
赖桂君 . 城市功能区单元尺度下的深圳市居民出租车出行时空特征研究 [D]. 广州 : 广州大学 , 2022 .
LAI Guijun . Spatial and temporal characteristics of Shenzhen residents’ taxi trips at the scale of urban functional area units [D]. Guangzhou : Guangzhou University , 2022 .
孙丙香 , 任鹏博 , 陈育哲 , 等 . 锂离子电池在不同区间下的衰退影响因素分析及任意区间的老化趋势预测 [J]. 电工技术学报 , 2021 , 36 ( 3 ): 666 - 674 .
SUN Bingxiang , REN Pengbo , CHEN Yuzhe , et al . Analysis of influencing factors of degradation under different interval stress and prediction of aging trend in any interval for lithium-ion battery [J]. Transactions of China Electrotechnical Society , 2021 , 36 ( 3 ): 666 - 674 .
0
Views
0
下载量
1
CSCD
Publicity Resources
Related Articles
Related Author
Related Institution
京公网安备11010802024621