- 中国高校优秀科技期刊
- 全国中文核心期刊
- 中国科技核心期刊
- 中国知网收录期刊
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| Citation: |
LIANG Wei, LIU Xiaonan, ZHANG Zhida, et al. A Random Charging Decision Method for Electric Private Cars Considering Individual Heterogeneity of Users and Latent Attitudinal Variables[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2023.0344
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According to the charging decision behavior of electric private cars (EPC), a random charging decision method for EPCs is proposed with individual heterogeneity and latent attitude variables taken into account. Firstly, an analysis on the influencing factors of charging decision is conducted, and questionnaires for the different factors are designed. Secondly, to address the design problem of latent variables of attitude, a measurement index is derived to indirectly quantify latent variables of attitude. Additionally, the quality of the survey data is analyzed through an examination of questionnaire data reliability and validity. Then, considering the charging scene variables, attitude latent variables and individual socioeconomic attributes that affect individual charging decisions, the hybrid choice model (HCM) is employed to establish the charging utility, and the charging probability is subsequently determined. Through the investigation data, the model parameters are estimated, leading to the determination of specific expressions of charging utility and three types of influencing factors. Compared to the prediction results based on the mixed Logit model, the proposed method achieves higher prediction accuracy, and the error has been reduced by nearly 14% when adopting the proposed method.
| [1] |
公安部: 2022年全国新能源汽车保有量达1310万辆[OL].https://baijiahao.baidu.com/s?id=1754698332767076172&wfr=spider&for=pc, 2023.01.11.
|
| [2] |
饶颖卿, 张晓东, 饶宇飞, 等. 考虑分段充电的实用型电动汽车概率负荷模型[J]. 电测与仪表, 2021, 58(06): 26−32.
RAO Yingqing, ZHANG Xiaodong, RAO Yufei, et al. A practical probability load model of electric vehicles considering segmental charging[J]. Electrical Measurement & Instrumentation, 2021, 58(06): 26−32(in Chinese).
|
| [3] |
刘勇, 李全优, 戴朝华. 电动汽车充电负荷时空分布建模研究综述[J]. 电测与仪表, 2022, 59(08): 1−9.
LIU Yong, LI Quanyou, DAI Chaohua. Review on the spatiotemporal distribution modeling of electric vehicle charging load[J]. Electrical Measurement & Instrumentation, 2022, 59(08): 1−9(in Chinese).
|
| [4] |
秦建华, 潘崇超, 张璇, 等. 基于充电行为分析的电动汽车充电负荷预测[J]. 电测与仪表, 2023, 60(04): 19−26.
QIN Jianhua, PAN Chongchao, ZHANG Xuan, et al. Charging load forecast of electric vehicle based on analysis of charging behavior[J]. Electrical Measurement & Instrumentation, 2023, 60(04): 19−26(in Chinese).
|
| [5] |
张美霞, 吴子敬, 杨秀. 基于动态能耗模型与用户心理的电动汽车充电负荷预测[J]. 现代电力, 2022, 39(06): 710−719.
ZHANG Meixia, WU Zijing, YANG Xiu. Electric vehicle charging load prediction based on dynamic energy consumption model and user psychology[J]. Modern Electric Power, 2022, 39(06): 710−719(in Chinese).
|
| [6] |
张美霞, 孙铨杰, 杨秀. 考虑多源信息实时交互和用户后悔心理的电动汽车充电负荷预测[J]. 电网技术, 2022, 46(02): 632−645.
ZHANG Meixia, SUN Quanjie, YANG Xiu. Electric vehicle charging load prediction considering multi-source information real-time interaction and user regret[J]. Power System Technology, 2022, 46(02): 632−645(in Chinese).
|
| [7] |
周翔, 陈杰军, 谢培元, 等. 基于效用最大化原则的电动汽车充电站负荷特性分析方法[J]. 电测与仪表, 2018, 55(04): 1−8.
ZHOU Xiang, CHEN Jiejun, XIE Peiyuan, et al. Load demand analyzing method for electric vehicle charging station based on the principle of maximizing utility[J]. Electrical Measurement & Instrumentation, 2018, 55(04): 1−8(in Chinese).
|
| [8] |
POWELL S, CEZAR G V, RAJAGOPAL R. Scalable probabilistic estimates of electric vehicle charging given observed driver behavior[J]. Applied Energy, 2022, 309: 118382. doi: 10.1016/j.apenergy.2021.118382
|
| [9] |
屈克庆, 赵登辉, 毛玲, 等. 考虑城市空间结构和用户有限理性的电动汽车快充负荷预测[J/OL]. 南方电网技术 [2024-05-08]. http://kns.cnki.net/kcms/detail/44.1643.TK.20231023.1624.004.html.
QU Keqing, ZHAO Denghui, MAO Ling, et al. Fast charging load prediction of electric vehicles considering urban spatial structure and user bounded rationality[J/OL]. Southern Power System Technology[2024-05-08]. http://kns.cnki.net/kcms/detail/44.1643.TK.20231023.1624.004.html(in Chinese).
|
| [10] |
周毅, 袁泉, 汤奕, 等. 基于路-电耦合网络的电动汽车充电决策优化方法[J]. 电网技术, 2021, 45(09): 3563−3572.
ZHOU Yi, YUAN Quan, TANG Yi, et al. Charging decision optimization for electric vehicles based on traffic-grid coupling networks[J]. Power System Technology, 2021, 45(09): 3563−3572(in Chinese).
|
| [11] |
冯万璐, 权轶, 付波, 等. 基于改进累积前景理论的电动运营车充电决策模型[J]. 电力工程技术, 2023, 42(02): 170−179.
FENG Wanlu, QUAN Yi, FU Bo, et al. Charging decision model of electric vehicle based on improved cumulative prospect theory[J]. Electric Power Engineering Technology, 2023, 42(02): 170−179(in Chinese).
|
| [12] |
YUN B, SUN DJ, ZHANG Y, et al. A charging location choice model for plug-in hybrid electric vehicle users[J]. Sustainability, 2019, 11(20): 5761. doi: 10.3390/su11205761
|
| [13] |
LI Hao, YU Lu, CHEN Yu, et al. Uncertainty of available range in explaining the charging choice behavior of BEV users[J]. Transportation Research Part A: Policy and Practice, 2023, 170: 103624. doi: 10.1016/j.tra.2023.103624
|
| [14] |
杨烨, 谭忠富, 焦港欣. 基于网联数据的电动车快速充电影响因素分析[J]. 交通运输系统工程与信息, 2020, 20(5): 86−92.
YANG Ye, TAN Zhongfu, JIAO Gangxin. Analysis of factors influencing fast charging behavior based on data of connected electric vehicles[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(5): 86−92(in Chinese).
|
| [15] |
孙庭源. 分时电价下电动出租车司机充电时间选择行为研究[D]. 南京: 东南大学, 2017.
|
| [16] |
LEE J H, CHAKRABORTY D, HARDMANS J, et al. Exploring electric vehicle charging patterns: mixed usage of charging infrastructure[J]. Transportation Research Part D: Transportation and Environment, 2020, 79: 102249. doi: 10.1016/j.trd.2020.102249
|
| [17] |
SUN X, YAMAMOTO T, TAKAHASHI K, et al. Home charge timing choice behavior of plug-in hybrid electric vehicle users under a dynamic electricity pricing scheme[J]. Transportation, 2018, 45(6): 1849−1869. doi: 10.1007/s11116-018-9948-6
|
| [18] |
PAN L, YAO E, MACKENZIED D. Modeling EV charging choice considering risk attitude and attribute non-attendance[J]. Transportation Research Part C: Emerging Technologies, 2019, 102: 60−72. doi: 10.1016/j.trc.2019.03.007
|
| [19] |
潘龙. 基于充电选择行为的电动汽车充电设施布局优化研究[D]. 北京: 北京交通大学, 2020.
|
| [20] |
WANG Yue, YAO Enjian, PAN Long. Electric vehicle drivers' charging behavior analysis considering heterogeneity and satisfaction[J]. Journal of Cleaner Production, 2021, 286: 124982. doi: 10.1016/j.jclepro.2020.124982
|
| [21] |
DAIAN N, POLAK J W, SIVAKUMAR A. Patent and latent predictors of electric vehicle charging behavior[J]. Transportation Research Record: Journal of the Transportation Research Board, 2015, 2502(1): 116−123. doi: 10.3141/2502-14
|
| [22] |
徐浩. 苗世洪, 钱甜甜, 等. 计及多日一充模式的规模化电动汽车充电负荷建模策略[J]. 电工技术学报, 2015, 30(9): 129−137.
XU Hao, MIAO Shihong, QIAN Tiantian, et al. A modeling strategy for charging loads of large-scale electric vehicles considering multi-days spaced charging mode[J]. Transaction of China Electrotechnical Society, 2015, 30(9): 129−137(in Chinese).
|
| [23] |
BEN-AKIVA M, WALKER J, BERNARDINO A, et al. Integration of choice and latent variable models[J]. In Perpetual Motion-Travel Behavior Research Opportunities and Application Challenges, 2002(1): 431−470.
|
| [24] |
张悦. 基于扩展TAM模型的公共充电桩用户使用意愿研究[D]. 长沙: 中南大学, 2022.
|
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