Development Paths of New Energy Vehicles Incorporating CO2 Emissions Trading Scheme

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

Abstract

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

CLC Number:

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.

References

[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.

Development Paths of New Energy Vehicles Incorporating CO₂ Emissions Trading Scheme

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Fan Changjia, Du Yanqiu, Liang Di, Hu Kai, Huang Jiayan. Modeling and Simulation of Emergency Medical Resources Allocation in Shanghai during COVID-19 [J]. Journal of System Simulation, 2022, 34(1): 93-103.
[2]	Lu Xuepeng, Shang Jiao, Zhao Junhui, Lü Lulu, Zhou Li. Transmission Process Prediction of Novel Coronavirus Based on System Dynamics [J]. Journal of System Simulation, 2021, 33(7): 1713-1721.
[3]	Zhang Libo, Ge Lulu, Chen Changqi, Tang Mingduan. Simulation on the Development of Residential Distributed Photovoltaic Power Generation under the Declining Trend of Feed-in-Tariff [J]. Journal of System Simulation, 2021, 33(6): 1397-1405.
[4]	Fu Yueqiang, Xia Tiantian. Modeling and Simulation of Electric Vehicle Industry Development Based on System Dynamics [J]. Journal of System Simulation, 2021, 33(4): 973-981.
[5]	Huang Guangqiu, Wang Wenxin. Study on Ultimate Carrying Capacity and Regulation Methods of Urban Atmospheric Environment [J]. Journal of System Simulation, 2021, 33(1): 159-168.
[6]	Liu Feng. Modeling and Simulation for Prevention and Control of Drug Abuse and Drug-Related Crime Based on System Dynamics [J]. Journal of System Simulation, 2020, 32(5): 866-873.
[7]	Hao Xiaoxiong, Ma Jianwei, Huang Zhaohui, Wang Yungui. System Dynamics and Multi-Agent Simulation Research on Ground CombatPersonnel Attrition [J]. Journal of System Simulation, 2020, 32(4): 738-743.
[8]	Zhang Yongsheng, Xiong Zhengxiang. Exploration of Soldier Morale Using Multi-mode Simulation Approach [J]. Journal of System Simulation, 2019, 31(12): 2740-2749.
[9]	Luo Longxi, Wu Jianping, Chen Yun, Xu Zhe. System Dynamics Modeling for Simulation of Water Supply and Demand Relationship in Beijing [J]. Journal of System Simulation, 2019, 31(12): 2790-2801.
[10]	Yang Guangming, Shi Yanjun. Study on Ecological Compensation of Three Gorges Basin Based on Evolutionary Game Theory [J]. Journal of System Simulation, 2019, 31(10): 2058-2068.
[11]	Li Han, Fan Wenhui, Feng Yuan, Zhu Mengni, Zhang Shengxiao. Modeling and Simulation for Automobile Connecting Rod Production Line Based on System Dynamics [J]. Journal of System Simulation, 2018, 30(9): 3351-3359.
[12]	Zhang Hong, Zheng Rongbei, Qiao Wenshan. Research on Concession Period Performance of Highway PPP Project Based on Pavement Maintenance [J]. Journal of System Simulation, 2018, 30(8): 3130-3138.
[13]	Chen Yalin, Gui Wang sheng, Dong Qianjin, Ye Chun, Wu Haotian. Simulation of Influence of Coal-based Industry on Water Resources Bearing System [J]. Journal of System Simulation, 2018, 30(12): 4770-4777.
[14]	Huang Guangqiu, Lu Qiuqin. Correlation Analysis Model of Generalized Stochastic System Dynamics [J]. Journal of System Simulation, 2018, 30(1): 69-79.
[15]	Liu Yingjie, Liu Yun, Guo Shanshan. Study on Vehicle Handling Inverse Dynamics Based on Model Predictive Control Theory [J]. Journal of System Simulation, 2018, 30(1): 304-310.