Research On The Prediction Model Of Traffic Carbon Peak And The Path Of Automobile Electrification In Shijiazhuang City

In recent years,with the expansion of urban scale,the acceleration of transportation infrastructure construction,and the increase in car ownership,carbon dioxide emissions have increased,causing greater pressure on the environment.To achieve the goal of "carbon peaking and carbon neutrality".Further evaluation of the current status of carbon emissions from transportation,prediction of carbon emissions under different emission reduction measures,and optimization of low-carbon development paths for transportation are needed.Therefore,conducting traffic carbon peak prediction and researching low-carbon development paths has theoretical and practical significance.The thesis takes Shijiazhuang transportation as an example for research.The characteristics of transportation development in Shijiazhuang city were analyzed.Based on this,the carbon emissions from transportation were calculated and the decoupling status between transportation and economic development was analyzed.The driving factors of transportation carbon emissions are explored by LMDI and STIRPAT methods.Based on the LEAP model,five carbon reduction scenarios were set up to predict future motor vehicle emissions,quantify the effectiveness of different emission reduction governance policies,predict the peak time of transportation carbon emissions,and seek the optimal low-carbon development path for automobile electrification.Considering the synergistic emission reduction factors between electric vehicle charging and the power grid,a preliminary carbon reduction optimization model for the integration of electric vehicle charging and the power grid has been constructed.The main achievements of the thesis are as follows:(1)The impact of urban structure,travel modes,turnover,and fuel economy on carbon emissions are analyzed,the carbon emissions of transportation in Shijiazhuang in the past decade are calculated,and the contribution of different transportation modes to carbon emissions are calculated,and the decoupling status between carbon emissions and economic development are evaluated.(2)The LMDI and STIRPAT methods are comprehensively used to analyze the driving factors of transportation carbon emissions.The study finds that energy intensity,unit turnover,transportation intensity,per capita GDP,population size,proportion of clean energy and urbanization rate have a greater impact on transportation carbon emissions.(3)A traffic carbon peak prediction model was constructed based on LEAP.By analyzing five traffic emission reduction scenarios,the carbon peak time in Shijiazhuang was predicted,and the optimal low-carbon development path for automobile electrification in transportation was proposed.(4)The demand for the power system during the process of electric vehicle electrification are studied,and considering,the collaborative emission reduction between electric vehicle charging and the power grid,a carbon reduction optimization model for the integration of electric vehicle charging and the power grid,which minimizes the operating cost of thermal power units,carbon dioxide emissions,and owner payment costs is preliminarily constructed.