Decomposition Of Influencing Factors And Multi-Scenario Prediction Of Carbon Emission In Power Industry

Climate change caused by greenhouse gas emissions has been a global concern,and China,the world’s largest emitter of carbon dioxide in the developing world,has come under increasing pressure.To alleviate greenhouse gas emissions,China has announced the goal of reaching the peak of carbon dioxide emissions by 2030 and achieving carbon neutrality by 2060.Most of China’s carbon emissions come from energy and other industrial activities.The power sector,as the largest energy consumer,accounts for more than 40%of China’s total carbon emissions and should be a key area for carbon reduction efforts.It is of great significance to study the influence factors and development trends of carbon emission in electric power industry and formulate emission reduction policies in line with the characteristics of Industrial and regional development.Taking the carbon emission of the power industry as the research theme,this paper builds the LMDI decomposition model based on the influencing factors from the perspective of the whole process of power generation side,transmission and distribution side and consumption side,and identifies the driving factors and inhibiting factors of the carbon emission of the power industry from 2006 to 2020 at the national and provincial levels.The carbon emission factors of 30 provinces(cities)were grouped and analyzed.The weight of BP neural network was optimized by particle swarm optimization algorithm,and the PSO-BP power industry carbon emission prediction model was built.The representative provinces(cities)of six cluster regions were taken as samples to test the effectiveness of the model.Considering the uncertainties in the future,this paper sets four different development situations,respectively makes mediumand long-term forecasts of carbon emissions in the power industry of six representative provinces(cities)based on four scenarios,and compares and analyzes the development trend and peak point of carbon emissions in the power industry under each scenario,which provides a judgment basis for the realization of the carbon peak target in the power industry in 2030 in each region.The research shows that economic development is the most important driving factor of carbon emissions in the power industry of the country and all the provinces(cities),and the factors of carbon emissions inhibition in the power industry of different cluster regions are different,mainly reflected in the industrial structure,industrial power consumption intensity,thermal power fuel conversion rate and the effect of power structure.Among the 6 regional representative provinces(cities),Tianjin,Hunan,Qinghai,Guizhou and Shanghai can all achieve the goal of carbon peaking in the power industry by 2030.The carbon emissions of the power industry in Qinghai province have reached the peak in 2017,and the peak time of Tianjin,Hunan,Guizhou and Shanghai is in 2025-2030.Xinjiang Autonomous Region has failed to reach the target of reaching the peak before 2030,and Region 6 represented by Xinjiang Autonomous Region should be the focus of emission reduction work in the future.Compared with the baseline scenario,the economic development priority scenario will lead to the overall increase of carbon emissions in the power industry and delay the peak of carbon emissions in Shanghai.The energy saving scenario makes the carbon emissions of the power industry decrease as a whole,and the peak is advanced in Tianjin,Qinghai and Guizhou.The energy transition scenario could also lead to lower carbon emissions in the power sector and an earlier peak in Xinjiang.For different regional representative provinces(cities),the emission reduction effect of energy-saving measures and energy transformation measures is not the same,therefore,provinces(cities)should follow the general direction of national policies combined with their own development characteristics,and the focus of power emission reduction work should be flexibly adjusted.