Research On Subregional Low Carbon Transformation Of Power Industry Under Carbon Neutrality Goal

With the development of economy and society,global warming is increasing day by day.The world emits about 51 billion tons of greenhouse gases into the atmosphere every year.To avoid climate disasters,human beings need to stop emitting greenhouse gases into the atmosphere and achieve zero emissions.As the global greenhouse effect continues to intensify,countries around the world have defined the time for carbon neutrality.Our country’s commitment to achieve carbon neutrality by 2060 reflects our country’s responsibility as a major country.Compared with developed countries,our country’s goal of achieving carbon neutrality has a tighter schedule,greater magnitude and more difficulties.At the same time,the process of realizing the carbon neutrality goal is also a process of giving birth to new industries and business models.Our country should follow the general trend of technological revolution and industrial transformation,seize the huge development opportunities brought by green transformation,and seek development opportunities from green development.and motivation.Our country has a vast territory,and regional development is unbalanced and inadequate.Achieving the goal of carbon neutrality requires promoting the realization of regional carbon neutrality in different regions on the basis of following the internal laws of economy and carbon emissions.From the perspective of carbon emission sources,our country’s energy-related CO₂ emissions account for 72.7%in2020.Specific to the industry,the carbon emissions of the power industry account for as high as 40%,making it the largest carbon emitter.Therefore,it is necessary to study the low-carbon transformation of the power industry in different regions under the carbon neutrality goal.Based on the above background,in this paper,the Pearson correlation coefficient method is used to obtain the correlation between each influencing factor and carbon emission,and principal component analysis is used to study the weight of the influencing factors of carbon emission.On the basis of the research on influencing factors,referring to the relevant literature,the influencing factors and dynamic influencing factors related to carbon neutrality are added,taking 30 provinces,municipalities and autonomous regions across the country as samples,using BA-KMeans algorithm,LWBA-KMeans algorithm,PSO-KMeans algorithm,and K-Means algorithm were used to cluster and analyze the carbon neutrality trend of each province and city.Comparing the effects of each algorithm on carbon-neutral clustering in various provinces and cities in China,the results show that compared with the other three algorithms,the LWBA-KMeans algorithm has a smaller error between the number of clusters and the actual number of clusters,the intra-class similarity is high,the inter-class similarity is small,the number of iterations is small,and the clustering effect is better.From the perspective of carbon neutrality trend,the provinces and cities are classified,and the 30 provinces,municipalities and autonomous regions in the country are divided into 5 categories,the leading,potential,transformational,exploratory,and budding provinces and cities,respectively.Finally,it analyzes our country’s power industry from the aspects of power supply structure,power supply and demand situation,and carbon emissions in the power industry,and puts forward suggestions for low-carbon transformation of the power industry.At the same time,according to the characteristics of each province and city in the results of the cluster analysis of carbon neutrality trend,suggestions for low-carbon transformation are put forward for various provinces and cities.