全生命周期视角下区域级电动汽车碳排放评估

doi:10.12204/j.issn.1000-7229.2023.06.004

摘要/Abstract

摘要：

碳达峰、碳中和是国家实施的重要战略决策,而发展电动汽车是实现低碳的举措之一。针对现有电动汽车碳排放评估片面和不准确的问题,提出了一种全生命周期视角下区域级电动汽车碳排放评估方法。为评估电动汽车整个生命周期内的碳排放,首先从材料周期和燃料周期出发构建了电动汽车碳排放的评估指标及其量化模型。进而,利用三阶段数据包络分析法对区域级内所有的电动汽车碳排放量进行分析,获取区域级内电动汽车碳排放评价结果。最后,将省级作为区域级,采用各省实际车辆和发展数据,对我国各省电动汽车碳排放展开评估。仿真结果表明,我国省级电动汽车碳排放效率差异较大,所提评估方法能够消除随机因素扰动,对区域级电动汽车碳排放全面评估。

关键词: 电动汽车, 碳排放评估, 全生命周期, 数据包络分析法

Abstract:

“Carbon peaking” and “carbon neutrality” are important strategic decisions implemented by countries, and the development of electric vehicles is one measure of achieving low carbon emissions. This study proposes a regional-level method for assessing carbon emissions of electric vehicles from a full lifecycle perspective. This method addresses the one-sidedness and inaccuracies present in existing carbon emission assessments for electric vehicles. To evaluate the carbon emissions of electric vehicles throughout their life cycle, an evaluation index and a quantitative model, beginning from the material and fuel cycles, were constructed. Subsequently, a three-stage data envelopment analysis was employed to analyze the carbon emissions and obtain the carbon emission assessment results of all regional electric vehicles. The method was further applied at the provincial level using actual vehicle and development data from each province to evaluate the carbon emissions of electric vehicles in various provinces of China. The simulation results indicated significant differences in the carbon emission efficiency of provincial electric vehicles in China and demonstrated that the proposed evaluation method can eliminate random factor disturbances and comprehensively evaluate the carbon emissions of regional electric vehicles.

Key words: electric vehicles, carbon emission assessment, full life cycle, data envelopment analysis

中图分类号:

TM73

王嘉诚, 刘晓峰, 梅文卿, 季振亚, 刘国宝. 全生命周期视角下区域级电动汽车碳排放评估[J]. 电力建设, 2023, 44(6): 33-40.

WANG Jiacheng, LIU Xiaofeng, MEI Wenqing, JI Zhenya, LIU Guobao. Carbon-Emission Assessment of Regional Electric Vehicles From the Full Life Cycle Perspective[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(6): 33-40.

图/表 11

图1 区域级电动汽车全生命周期碳排放评估框架

Fig.1 Carbon emission assessment framework of electric vehicles from the perspective of full life cycle

表1 电动汽车碳排放DEA的参数

Table 1 Parameters of carbon emission DEA of electric vehicles

表2 数据的描述性统计结果

Table 2 Descriptive statistical results of data

图2 各年碳排放评估参数平均值

Fig.2 Mean values of carbon emission assessment parameters in each year

表3 SFA回归分析结果

Table 3 Results of SFA regression analysis

图3 2016—2020年各省Sev散点图

Fig.3 Scatter plot of Sev in each province from 2016 to 2020

表4 调整前后Sev结果

Table 4 Sev results before and after adjustment

图4 碳排放评估调整前后比较

Fig.4 Comparison of carbon emission assessment before and after adjustment

表5 2018年电动汽车碳排放评价调整前后比较

Table 5 Comparison of electric vehicle carbon emission assessment before and after adjustment in 2018

图5 单位碳排放量与人均收入

Fig.5 Carbon emissions per unit and income per capita

表6 2020年电动汽车单位碳排放量与碳排放绩效排序比较

Table 6 Comparison of unit carbon emission and carbon emission performance of electric vehicles in 2020

参考文献 31

[1]	李响, 牛赛. 双碳目标下源-网-荷多层评价体系研究[J]. 中国电机工程学报, 2021, 41(S1): 178-184.
	LI Xiang, NIU Sai. Study on multi-layer evaluation system of source-grid-load under carbon-neutral goal[J]. Proceedings of the CSEE, 2021, 41(S1): 178-184.
[2]	杨奇, 王丹, 何伟, 等. 基于社会清洁福利最大化的电热联合双边竞价市场出清优化策略研究[J]. 电力系统保护与控制, 2021, 49(14):112-122.
	YANG Qi, WANG Dan, HE Wei, et al. Research on clearing optimization of electricity-heat coordinated double auction market based on social clean welfare maximization[J]. Power System Protection and Control, 2021, 49(14):112-122.
[3]	LI Y M, HA N N, LI T T. Research on carbon emissions of electric vehicles throughout the life cycle assessment taking into vehicle weight and grid mix composition[J]. Energies, 2019, 12(19): 3612. doi: 10.3390/en12193612 URL
[4]	蔡黎, 张权文, 代妮娜, 等. 规模化电动汽车接入主动配电网研究进展综述[J]. 智慧电力, 2021, 49(6):75-82.
	CAI Li, ZHANG Quanwen, DAI Nina, et al. Review on research progress of large-scale electric vehicle access to active distribution network[J]. Smart Power, 2021, 49(6):75-82.
[5]	CHEN X, SHUAI C Y, WU Y, et al. Analysis on the carbon emission peaks of China’s industrial, building, transport, and agricultural sectors[J]. Science of the Total Environment, 2020, 709: 135768. doi: 10.1016/j.scitotenv.2019.135768 URL
[6]	李咸善, 陈敏睿, 程杉, 等. 基于双重激励协同博弈的含电动汽车微电网优化调度策略[J]. 高电压技术, 2020, 46(7): 2286-2296.
	LI Xianshan, CHEN Minrui, CHENG Shan, et al. Research on optimal scheduling strategy of microgrid with electric vehicles based on dual incentive cooperative game[J]. High Voltage Engineering, 2020, 46(7): 2286-2296.
[7]	张菁, 林毓军, 齐晓光, 等. 考虑碳税与碳交易替代效应的电力系统低碳经济调度方法[J]. 电力建设, 2022, 43(6): 1-11. doi: 10.12204/j.issn.1000-7229.2022.06.001
	ZHANG Jing, LIN Yujun, QI Xiaoguang, et al. Low-carbon economic dispatching method for power system considering the substitution effect of carbon tax and carbon trading[J]. Electric Power Construction, 2022, 43(6): 1-11. doi: 10.12204/j.issn.1000-7229.2022.06.001
[8]	周建力, 乌云娜, 董昊鑫, 等. 计及电动汽车随机充电的风-光-氢综合能源系统优化规划[J]. 电力系统自动化, 2021, 45(24): 30-40.
	ZHOU Jianli, WU Yunna, DONG Haoxin, et al. Optimal planning of wind-photovoltaic-hydrogen integrated energy system considering random charging of electric vehicles[J]. Automation of Electric Power Systems, 2021, 45(24): 30-40.
[9]	檀勤良, 代美, 梅书凡. 考虑电动汽车碳配额及需求响应的电力系统调度研究[J]. 电网与清洁能源, 2021, 37(7): 79-86.
	TAN Qinliang, DAI Mei, MEI Shufan. Research on electric vehicle carbon quota and demand response in electric power system dispatching[J]. Power System and Clean Energy, 2021, 37(7): 79-86.
[10]	于大洋, 黄海丽, 雷鸣, 等. 电动汽车充电与风电协同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 benefit by coordinated dispatch of electric vehicle charging and wind power[J]. Automation of Electric Power Systems, 2012, 36(10): 14-18.
[11]	朱磊, 黄河, 高松, 等. 计及风电消纳的电动汽车负荷优化配置研究[J]. 中国电机工程学报, 2021, 41(S1): 194-203.
	ZHU Lei, HUANG He, GAO Song, et al. Research on optimal load allocation of electric vehicle considering wind power consumption[J]. Proceedings of the CSEE, 2021, 41(S1): 194-203.
[12]	胡健, 秦玉杰, 焦提操, 等. 泛在电力物联网环境下考虑碳排放权约束的VPP理性调峰模型[J]. 电力系统保护与控制, 2020, 48(3): 49-57.
	HU Jian, QIN Yujie, JIAO Ticao, et al. Rational peak shaving model of VPP considering carbon emission rights constraints in ubiquitous power Internet of Things environment[J]. Power System Protection and Control, 2020, 48(3): 49-57.
[13]	高亚静, 李瑞环, 梁海峰, 等. 碳市场环境下计及碳捕集电厂和换电站的电力系统优化调度[J]. 电力系统自动化, 2014, 38(17): 150-156.
	GAO Yajing, LI Ruihuan, LIANG Haifeng, et al. Power system optimal dispatch incorporating carbon capture power plant and battery swap station under carbon market environment[J]. Automation of Electric Power Systems, 2014, 38(17): 150-156.
[14]	周雅夫, 史宏宇. 面向实车数据的电动汽车电池退役轨迹预测[J]. 太阳能学报, 2022, 43(5): 510-517. doi: 10.19912/j.0254-0096.tynxb.2022-0506
	ZHOU Yafu, SHI Hongyu. Battery retirement trajectory prediction of electric vehicle based on real vehicle data[J]. Acta Energiae Solaris Sinica, 2022, 43(5): 510-517. doi: 10.19912/j.0254-0096.tynxb.2022-0506
[15]	汪宜秀, 魏学哲, 房乔华, 等. 面向整组寿命最大化的电动汽车电池一致性变化规律及其均衡策略[J]. 机械工程学报, 2020, 56(22): 176-183. doi: 10.3901/JME.2020.22.176
	WANG Yixiu, WEI Xuezhe, FANG Qiaohua, et al. Consistency variation law and equalization strategy of electric vehicle battery for maximizing the life of the battery pack[J]. Journal of Mechanical Engineering, 2020, 56(22): 176-183. doi: 10.3901/JME.2020.22.176
[16]	XIE R, FANG J Y, LIU C J. The effects of transportation infrastructure on urban carbon emissions[J]. Applied Energy, 2017, 196: 199-207. doi: 10.1016/j.apenergy.2017.01.020 URL
[17]	ZHOU Y, LIU Y S. Does population have a larger impact on carbon dioxide emissions than income? Evidence from a cross-regional panel analysis in China[J]. Applied Energy, 2016, 180: 800-809. doi: 10.1016/j.apenergy.2016.08.035 URL
[18]	哈宁宁. 电动汽车全生命周期碳排放评估及对环境的影响[D]. 北京: 华北电力大学, 2020.
	HA Ningning. Life cycle assessment of electric vehicles’ carbon emission and its impact on the environment[D]. Beijing: North China Electric Power University, 2020.
[19]	周博雅. 电动汽车生命周期的能源消耗、碳排放和成本收益研究[D]. 北京: 清华大学, 2016.
	ZHOU Boya. Life cycle assessment of EnergyUse, carbon emissions and cost benefit of electric vehicles[D]. Beijing: Tsinghua University, 2016.
[20]	WANKE P, ABUL KALAM AZAD M, EMROUZNEJAD A, et al. A dynamic network DEA model for accounting and financial indicators: a case of efficiency in MENA banking[J]. International Review of Economics & Finance, 2019, 61: 52-68.
[21]	刘岑婕. 我国城市碳减排潜力和减排政策影响效应研究[D]. 长沙: 湖南大学, 2019.
	LIU Cenjie. Study on the urban carbon reduction potential and the impact of carbon reduction policy in China[D]. Changsha: Hunan University, 2019.
[22]	QIAO Q Y, ZHAO F Q, LIU Z W, et al. Life cycle greenhouse gas emissions of electric vehicles in China: combining the vehicle cycle and fuel cycle[J]. Energy, 2019, 177: 222-233. doi: 10.1016/j.energy.2019.04.080 URL
[23]	郑继虎, 中国汽车技术研究中心公司. 节能与新能源汽车发展报告 2019[M]. 北京: 人民邮电出版社, 2019.
[24]	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.
[25]	KUANG B, LU X H, ZHOU M, et al. Provincial cultivated land use efficiency in China: empirical analysis based on the SBM-DEA model with carbon emissions considered[J]. Technological Forecasting and Social Change, 2020, 151: 119874. doi: 10.1016/j.techfore.2019.119874 URL
[26]	WILL C, LEHMANN N, BAUMGARTNER N, et al. Consumer understanding and evaluation of carbon-neutral electric vehicle charging services[J]. Applied Energy, 2022, 313: 118799. doi: 10.1016/j.apenergy.2022.118799 URL
[27]	刘晓峰, 高丙团, 罗京, 等. 基于非合作博弈的居民负荷分层调度模型[J]. 电力系统自动化, 2017, 41(14): 54-60.
	LIU Xiaofeng, GAO Bingtuan, LUO Jing, et al. Non-cooperative game based hierarchical dispatch model of residential loads[J]. Automation of Electric Power Systems, 2017, 41(14): 54-60.
[28]	黄伟, 叶波. 综合能源系统环境下电动汽车分群优化调度[J]. 电力建设, 2021, 42(4): 27-39. doi: 10.12204/j.issn.1000-7229.2021.04.004
	HUANG Wei, YE Bo. Optimal scheduling of electric vehicle clusters in integrated energy system[J]. Electric Power Construction, 2021, 42(4): 27-39. doi: 10.12204/j.issn.1000-7229.2021.04.004
[29]	AYGUN A I, KAMALASADAN S. An optimal approach to manage electric vehicle fleets routing[C]// 2022 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy (PESGRE). IEEE, 2022: 1-6.
[30]	LAI S Y, QIU J, TAO Y C, et al. Pricing for electric vehicle charging stations based on the responsiveness of demand[J]. IEEE Transactions on Smart Grid, 2023, 14(1): 530-544. doi: 10.1109/TSG.2022.3188832 URL
[31]	LYU K N, YANG S W, ZHENG K, et al. How does the digital economy affect carbon emission efficiency? evidence from energy consumption and industrial value chain[J]. Energies, 2023, 16(2): 761. doi: 10.3390/en16020761 URL