Research On Differences In Influencing Factors And Interprovincial Energy Intensity Prediction In China

Nowadays,China is in a period of steady economic development,and its economic level is gradually increasing at a medium to high level.However,energy consumption is still the basic guarantee for China's economic activities and social development,and will continue to increase in a certain period.With the limitation of energy resources and various environmental problems becoming increasingly prominent,the problems of climate change and pollutant emission caused by energy consumption become increasingly serious.As a major energy consumption country,China must control the growth of energy consumption.In addition,the resource conditions and economic levels of different regions in China are different,and the level of energy utilization is different.Therefore,to reduce the dependence of economic development on energy consumption,to find out the influence conditions of energy efficient utilization,and to formulate reasonable energy constraint objectives based on the actual situation of the region are important issues worthy of study.First of all,this paper reviews the influencing factors of energy intensity at home and abroad,the selection of research methods and the research status of prediction model.Secondly,spatial distribution map and exploratory spatial data are used to analyze the status quo of energy intensity differences,and a spatial lag panel convergence model is established to analyze the convergence of energy intensity areas.Then,select six factors that have great influence and can be controlled,establish the spatial Doberman model,and analyze the influence of each factor on the energy intensity of the local and surrounding areas.Then,the paper establishes a geographical weighted regression model to analyze the influence of various factors on different regions.On this basis,the short-term memory model optimized by the improved quantum particle swarm optimization algorithm is constructed,and two different development scenarios are set up in combination with the development planning,actual situation and the key influencing factors proposed above,so as to predict the energy intensity of each province in 2018-2025,and put forward energy-saving suggestions for one or two key factors of each type of city.The results show that there are strong differences and correlations in China's energy intensity,and the autocorrelation effect is increasing,while the high-intensity areas will not spontaneously tend to lower energy intensity level,it is necessary to find out the influence factors of these areas for targeted control.According to the analysis results of influence factors,the influence distribution of each factor in different regions is different.The five factors,namely coal consumption proportion,internal funds for research and experimental development,foreign direct investment,urbanization rate and the proportion of secondary industry,have a greater impact on the energy intensity of the region,while the four factors,namely,the number of civil automobiles,internal funds for research and experimental development,urbanization rate and the proportion of secondary industry Factors have a strong spillover effect on the energy intensity of the surrounding areas.In addition,according to the influence of various factors on different regions,30 provinces and cities are divided into seven categories.Finally,according to the prediction results by 2025,under the benchmark scenario,the energy intensity of 30 provinces and cities in China is 0.43-3.17 tons of standard coal / 10000 yuan,and under the enhanced scenario of key factor control,the energy intensity of each province and city is less than 2.15 tons of standard coal / 10000 yuan.The prediction results set the energy intensity control goal of the next five-year plan for each province and city,and improve the regional energy utilization level Provide reference basis.