Prediction and Analysis of the Relationship between Energy Mix Structure and Electric Vehicles Holdings Based on Carbon Emission Reduction Constraint: A Case in the Beijing-Tianjin-Hebei Region, China

Weijun Wang, Dan Zhao, Zengqiang Mi and Liguo Fan
Additional contact information
Weijun Wang: Department of Economics and Management, North China Electric Power University, 689 Huadian Road, Baoding 071000, China
Dan Zhao: Department of Economics and Management, North China Electric Power University, 689 Huadian Road, Baoding 071000, China
Zengqiang Mi: Power System and Automation, North China Electric Power University, 689 Huadian Road, Baoding 071000, China
Liguo Fan: Department of Economics and Management, North China Electric Power University, 689 Huadian Road, Baoding 071000, China

Sustainability, 2019, vol. 11, issue 10, 1-20

Abstract: In response to air pollution problems caused by carbon emissions, electric vehicles are widely promoted in China. Since thermal power generation is the main form of power generation, the large-scale development of electric vehicles is equivalent to replacing oil with coal, which will accordingly result in carbon emissions increasing if the scale of electric vehicles exceeds a certain limit. A relationship model between regional energy mix structure and electric vehicles holdings under the constraint of carbon emission reduction is established to perform a quantitative analysis of the limitation mechanism. In order to measure the scale of the future electric vehicle market under the constraint of carbon emissions reduction, a method called Extreme Learning Machine optimized by Improved Particle Swarm Optimization (IPSO-ELM) with higher precision than Extreme Learning Machine (ELM) is proposed to predict the power structure and the trend of electric vehicle development in the Beijing-Tianjin-Hebei region from 2019–2030. The calculation results show that the maximum number of electric vehicles must not exceed 19,340,000 and 26,867,171 based on emissions reduction aims and also the predicted energy mix structure in the Beijing-Tianjin-Hebei region in 2020 and 2030. At this time, the ratio of electric vehicles to traditional car ownership is 75.6% and 78.3%. The proportion of clean energy generation should reach 0.314 and 0.323 to match a complete replacement of traditional fuel vehicles for electric vehicles. A substantial increase in clean energy generation is needed so that the large-scale promotion of electric vehicles can still achieve the goal of carbon reduction. Therefore, this article will be helpful for policy-making on electric vehicle development scale and energy mix structure in the Beijing-Tianjin-Hebei region.

Keywords: electric vehicle; carbon emission; power production structure; constraint model; improved particle swarm optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/10/2928/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/10/2928/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:10:p:2928-:d:233571

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().