引入碳交易机制的新能源汽车发展路径研究

doi:10.16182/j.issn1004731x.joss.21-0006

系统仿真学报 ›› 2021, Vol. 33 ›› Issue (6): 1451-1465.doi: 10.16182/j.issn1004731x.joss.21-0006

引入碳交易机制的新能源汽车发展路径研究

李文翔¹, 李晔^2,*, 董洁霜¹, 李一鸣¹

1.上海理工大学管理学院,上海 200093;
2.同济大学交通运输工程学院,上海 201804

收稿日期:2021-01-04 修回日期:2021-03-15 出版日期:2021-06-18 发布日期:2021-06-23
通讯作者: 李晔(1974-),男,博士,教授,研究方向为交通治理、公共政策。E-mail: jamesli@tongji.edu.cn
作者简介:李文翔(1992-),男,博士,讲师,研究方向为低碳交通。E-mail：liwx@usst.edu.cn
基金资助:
国家自然科学基金(52002244,71774118); 上海市科技创新行动计划软科学项目(20692192200); 上海市浦江人才计划(2020PJC083); 上海市晨光计划(20CG55)

Development Paths of New Energy Vehicles Incorporating CO₂ Emissions Trading Scheme

Li Wenxiang¹, Li Ye^2,*, Dong Jieshuang¹, Li Yiming¹

1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;
2. College of Transportation Engineering, Tongji University, Shanghai 2010804, China

Received:2021-01-04 Revised:2021-03-15 Online:2021-06-18 Published:2021-06-23

摘要/Abstract

摘要： 中国新能源汽车进入“后补贴时代”,亟需探索建立市场化发展的长效机制。引入道路交通碳交易机制替代财政补贴,形成市场化激励与惩罚机制,建立起燃油汽车反哺新能源汽车的市场机制。采用系统动力学解析道路交通碳交易机制影响新能源汽车发展的关键政策参数,构建基于多智能体的道路交通碳交易仿真模型,并对引入碳交易机制的新能源汽车发展路径进行仿真预测。结果表明：在各发展路径下,2030年和2050年的中国新能源汽车市场份额分别能够达到50%~85%和91%~98%,反映引入道路交通碳交易机制可以有效促进“后补贴时代”新能源汽车跨越式发展。

关键词: 新能源汽车, 碳交易机制, 多主体协同, 智能体建模与仿真, 系统动力学

Abstract: New energy vehicles in China have entered the “post-subsidy era”, and it is urgent to explore and establish a long-term mechanism for market-oriented development. The CO₂ emission trading scheme for road transport (ETS-RT) is introduced to replace financial subsidies, forming a market-oriented incentive and punishment mechanism. Therefore, a market mechanism is established where internal combustion engine vehicles feed new energy vehicles. A causal loop diagram of system dynamics was used to analyze the key policy parameters of the ETS-RT that affect the development of new energy vehicles. Then a multi-agents-based model of ETS-RT is established to simulate the development paths of new energy vehicles incorporating ETS-RT. The results show that: the market share of new energy vehicles in 2030 and 2050 may reach 50%-85% and 91%-98% respectively under the development paths. It reflects that the introduction of ETS-RT can effectively promote the leaping development of China's new energy vehicles in the “post-subsidy era”.

Key words: new energy vehicle, CO₂ emission trading scheme, multi-agent collaboration, agent-based modeling and simulation, system dynamics

中图分类号:

李文翔, 李晔, 董洁霜, 李一鸣. 引入碳交易机制的新能源汽车发展路径研究[J]. 系统仿真学报, 2021, 33(6): 1451-1465.

Li Wenxiang, Li Ye, Dong Jieshuang, Li Yiming. Development Paths of New Energy Vehicles Incorporating CO₂ Emissions Trading Scheme[J]. Journal of System Simulation, 2021, 33(6): 1451-1465.

参考文献

[1] 袁博. 后补贴时代中国新能源汽车产业发展研究[J]. 区域经济评论, 2020(3): 58-64.
Yuan Bo.Research on the Development of China’s New Energy Vehicle Industry in the Post Subsidy Era[J]. Regional Economic Review, 2020(3): 58-64.
[2] 李晔, 李文翔, 魏愚獒. 道路交通碳排放权交易研究现状与展望[J]. 同济大学学报(自然科学版), 2018, 46(4): 465-471.
Li Ye, Li Wenxiang, Wei Yuao.Research Status and Prospect of Carbon Emission Trading in Road Traffic[J]. Journal of Tongji University (Natural Science Edition), 2018, 46(4): 465-471
[3] Li Y, Li W, Wei Y, et al.Using Personal Carbon Dioxide Trading to Promote Cleaner Cars[J]. Proceedings of the Institution of Civil Engineers-Transport (S0965-092X), 2016, 170(2): 86-98.
[4] 钟永光, 贾晓菁, 钱颖. 系统动力学[M]. 2版. 北京: 科学出版社, 2013.
Zhong Yongguang, Jia Xiaojing, Qian Ying.System Dynamics[M]. 2nd ed. Beijing: Science Press, 2013.
[5] 廖守亿, 陈坚, 陆宏伟, 等. 基于Agent的建模与仿真概述[J]. 计算机仿真, 2008, 25(12): 1-7.
Liao Shouyi, Chen Jian, Lu Hongwei, et al.Overview of Agent-based Modeling and Simulation[J]. Computer Simulation, 2008, 25(12): 1-7.
[6] Keles D, Wietschel M, Most D, et al.Market Penetration of Fuel Cell Vehicles-Analysis based on Agent Behaviour[J]. International Journal of Hydrogen Energy (S0360-3199), 2008, 33(16): 4444-4455.
[7] Park S Y, Kim J W, Lee D H.Development of a Market Penetration Forecasting Model for Hydrogen Fuel Cell Vehicles Considering Infrastructure and Cost Reduction Effects[J]. Energy Policy (S0301-4215), 2011, 39(6): 3307-3315.
[8] Wang N, Tang L, Zhang W, et al.How to Face the Challenges Caused by the Abolishment of Subsidies for Electric Vehicles in China?[J]. Energy (S0360-5442), 2019, 166: 359-372.
[9] Liu D, Xiao B.Exploring the Development of Electric Vehicles under Policy Incentives: A Scenario-based System Dynamics Model[J]. Energy Policy (S0301-4215). 2018, 120: 8-23.
[10] 王浩淞. 基于碳减排的新能源汽车应用推广模式研究[D]. 哈尔滨: 东北林业大学, 2017: 27-47.
Wang Haosong.Research on the Application and Promotion Model of New Energy Vehicles Based on Carbon Emission Reduction[D]. Harbin: Northeast Forestry University, 2017: 27-47.
[11] 姚志超. 新能源汽车扩散模型的仿真研究[D]. 南京: 南京航空航天大学, 2015: 8-20.
Yao Zhichao.Simulation Study on Diffusion Model of New Energy Vehicles[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2015: 8-20.
[12] 胡剑. 基于Agent的多类新能源汽车扩散模型及仿真研究[D]. 上海: 华东理工大学, 2013: 9-21.
Hu Jian.Agent-based Diffusion Model and Simulation of Multi-class New Energy Vehicles[D]. Shanghai: East China University of Science and Technology, 2013: 9-21.
[13] Schwoon M.Simulating the Adoption of Fuel Cell Vehicles[J]. Journal of Evolutionary Economics (S1432-1386), 2006, 16(4): 435-472.
[14] Shafiei E, Thorkelsson H, Ásgeirsson E I, et al.An Agent-based Modeling Approach to Predict the Evolution of Market Share of Electric Vehicles: A Case Study from Iceland[J]. Technological Forecasting and Social Change (S0040-1625), 2012, 79(9): 1638-1653.
[15] Noori M, Tatari O.Development of an Agent-based Model for Regional Market Penetration Projections of Electric Vehicles in the United States[J]. Energy (S0360-5442), 2016, 96: 215-230.
[16] Zhuge C, Wei B, Dong C, et al.Exploring the Future Electric Vehicle Market and its Impacts with an Agent-based Spatial Integrated Framework: A Case Study of Beijing, China[J]. Journal of Cleaner Production (S0959-6526), 2019, 221: 710-737.
[17] 严筱. 低碳交通背景下中国新能源汽车的市场扩散研究[D]. 武汉: 中国地质大学, 2016.
Yan Xiao.Research on Market Diffusion of New Energy Vehicles in China under the Background of Low-carbon Transportation[D]. Wuhan: China University of Geosciences, 2016.
[18] 赵倩倩. 基于Agent的新能源汽车市场扩散建模及仿真[J]. 综合运输, 2019, 41(10): 107-112.
Zhao Qianqian.An Agent-Based Diffusion Modeling and Simulation of New Energy Vehicle Market[J]. China Transportation Review, 2019, 41(10): 107-112.
[19] 詹文杰, 邵原. 连续竞价市场的交易策略研究综述[J]. 管理学报, 2008(6): 921-927.
Zhan Wenjie, Shao Yuan.A Summary of the Research on Trading Strategies in Continuous Bidding Market[J]. Journal of Management, 2008(6): 921-927.
[20] 李军. 个人交通碳排放权交易机制对交通领域碳减排的影响研究[D]. 合肥: 中国科学技术大学, 2017.
Li Jun.Research on the Impact of Individual Transportation Carbon Emission Trading Mechanism on Carbon Emission Reduction in Transportation Field[D]. Hefei: University of Science and Technology of China, 2017.
[21] Schwoon M.Simulating the Adoption of Fuel Cell Vehicles[J]. Journal of Evolutionary Economics (S1432-1386), 2006, 16(4): 435-472.
[22] Shafiei E, Thorkelsson H, Ásgeirsson E I, et al.An Agent-based Modeling Approach to Predict the Evolution of Market Share of Electric Vehicles: A Case Study from Iceland[J]. Technological Forecasting and Social Change (S0040-1625), 2012, 79(9): 1638-1653.
[23] Jochem P.A CO₂ Emission Trading Scheme for German Road Transport: Assessing the Impacts using a Meso Economic Model with Multi-agent Attributes[D]. Baden-Baden, Germany: Universität Karlsruhe (TH), 2009.
[24] Frondel M, Peters J, Vance C.Identifying the Rebound - Evidence from a German Household Panel[R]. Ruhr Economic Paper, 2007.
[25] Wang T, Chen C.Impact of Fuel Price on Vehicle Miles Traveled (VMT): do the Poor Respond in the Same Way as the Rich?[J]. Transportation (S1572-9435), 2014, 41(1): 91-105.
[26] Newmark G L, Haas P M. Income, Location Efficiency,VMT: Affordable Housing as a Climate Strategy[R]. Housing California, 2015.
[27] Liddle B.Long-run Relationship among Transport Demand, Income, and Gasoline Price for the US[J]. Transportation Research Part D: Transport and Environment (S1361-9209), 2009, 14(2): 73-82.
[28] Wadud Z.Personal Tradable Carbon Permits for Road Transport: Heterogeneity of Demand Responses and Distributional Analysis[D]. London: Imperial College London, 2007.
[29] Weiss M, Patel M K, Junginger M, et al.On the Electrification of Road Transport - Learning Rates and Price Forecasts for Hybrid-Electric and Battery-Electric Vehicles[J]. Energy Policy (S0301-4215), 2012, 48: 374-393.
[30] 中国汽车工程学会. 节能与新能源汽车技术路线图[M]. 北京: 机械工业出版社, 2016.
China Automotive Engineering Society. Technical Roadmap for Energy Saving and New Energy Vehicles [M]. Beijing: Machinery Industry Press, 2016.
[31] Huo H, Wang M.Modeling Future Vehicle Sales and Stock in China[J]. Energy Policy (S0301-4215), 2012, 43: 17-29.
[32] Huo H, Wang M, Johnson L, et al. Projection of Chinese Motor Vehicle Growth, Oil Demand,CO₂ Emissions Through2050[J]. Transportation Research Record: Journal of the Transportation Research Board, (S0361-1981), 2007(1): 69-77.
[33] Hao H, Wang H, Ouyang M, et al.Vehicle Survival Patterns in China[J]. Science China Technological Sciences (S1869-1900), 2011, 54(3): 625-629.
[34] Ou X, Zhang X, Chang S.Scenario Analysis on Alternative Fuel/Vehicle for China’s Future Road Transport: Life-cycle Energy Demand and GHG Emissions[J]. Energy Policy (S0301-4215), 2010, 38(8): 3943-3956.

引入碳交易机制的新能源汽车发展路径研究

Development Paths of New Energy Vehicles Incorporating CO₂ Emissions Trading Scheme

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	李锋, 魏莹. 社会学习和参照点效应对企业产品决策的影响[J]. 系统仿真学报, 2022, 34(2): 234-246.
[2]	樊长佳, 杜炎秋, 梁笛, 胡凯, 黄葭燕. COVID-19期间上海市应急医疗资源配置建模与仿真[J]. 系统仿真学报, 2022, 34(1): 93-103.
[3]	路雪鹏, 尚娇, 赵俊辉, 吕露露, 周丽. 基于系统动力学的新冠病毒传播过程预测[J]. 系统仿真学报, 2021, 33(7): 1713-1721.
[4]	张力菠, 葛禄璐, 陈昌奇, 汤铭端. 电价补贴退坡趋势下户用光伏发展演化的仿真研究[J]. 系统仿真学报, 2021, 33(6): 1397-1405.
[5]	付跃强, 夏天添. 基于系统动力学的电动汽车产业发展建模与仿真[J]. 系统仿真学报, 2021, 33(4): 973-981.
[6]	李锋, 魏莹. 复杂网络对羊群效应现象影响的仿真研究[J]. 系统仿真学报, 2021, 33(3): 539-553.
[7]	黄光球, 王文昕. 城市大气环境极限承载力及调控方法研究[J]. 系统仿真学报, 2021, 33(1): 159-168.
[8]	刘风. 基于系统动力学的毒品违法犯罪防治建模与仿真[J]. 系统仿真学报, 2020, 32(5): 866-873.
[9]	郝枭雄, 马建威, 黄朝晖, 王云贵. 战斗减员过程的系统动力学与多智能体仿真研究[J]. 系统仿真学报, 2020, 32(4): 738-743.
[10]	李锋, 魏莹. 时序网络视角下网络舆情的演化模型研究[J]. 系统仿真学报, 2020, 32(3): 394-403.
[11]	张永胜, 熊正祥. 基于多模式仿真方法的士兵士气研究[J]. 系统仿真学报, 2019, 31(12): 2740-2749.
[12]	罗龙溪, 吴建平, 陈云, 徐哲. 基于系统动力学的北京供需水关系仿真研究[J]. 系统仿真学报, 2019, 31(12): 2790-2801.
[13]	杨光明, 时岩钧. 基于演化博弈的长江三峡流域生态补偿机制研究[J]. 系统仿真学报, 2019, 31(10): 2058-2068.
[14]	李晗, 范文慧, 冯袁, 朱梦妮, 张生晓. 基于系统动力学的汽车连杆生产线建模与仿真[J]. 系统仿真学报, 2018, 30(9): 3351-3359.
[15]	张宏, 郑荣贝, 乔文珊. 基于路面维护的高速公路PPP项目特许期绩效研究[J]. 系统仿真学报, 2018, 30(8): 3130-3138.

引入碳交易机制的新能源汽车发展路径研究

Development Paths of New Energy Vehicles Incorporating CO2 Emissions Trading Scheme

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

Development Paths of New Energy Vehicles Incorporating CO₂ Emissions Trading Scheme