Research On Forecast Of Generation Side Carbon Emissions Based On STIRPAT Model

With the rapid development of our economy and further development of industrialization, global warming is becoming increasingly serious, greenhouse gas emissions have become the focus of attention and energy conservation and emissions reduction problem has become the national economy and social problems need to solve urgently in the process of sustainable development. The influence of CO2 on greenhouse effect is the largest and CO2 is the leading greenhouse gas of atmospheric warming, so the reduction of carbon dioxide emissions to alleviate global warming is very important. In greenhouse gas emissions, the emissions of energy related industries are most obvious, especially the carbon emissions of power industry. Electricity is the main secondary energy and the generation of electricity needs plenty of primary energy, so it will produce large amounts of greenhouse gases. The carbon emissions of generation side comes mainly from thermal power, because thermal power requires a lot of fossil fuels. In this paper, the CO2 emissions produced by thermal power is calculated to stand for the carbon emissions of generation side. The influencing factors is analyzed and the carbon emissions of generation side is forecast, on this basis the strategies to reduce carbon emissions in generation side are put forward.In this paper, the calculation methods are compared, then the direct calculation method based on energy balance table is determined to calculate the carbon emissions of generation side, at the same time the characteristics of the carbon emissions of generation side is analyzed. The results show that the carbon dioxide emissions of generation side is rising and the unit power carbon dioxide emissions is on a declining trend. The extended STIRPAT model and ridge regression are used to analyze the influencing factors, including population, urbanization level, per capita gross domestic product, the added value of the second industry, standard coal consumption and the structure of power generation. The results of ridge regression show that the population has most significant effect on the carbon dioxide emissions of generation side followed by urbanization level and the per capita gross domestic product and the structure of power generation have little effect on the carbon dioxide emissions of generation side. The STIRPAT model and Logistic model are used to forecast the carbon dioxide emissions of generation side, and then the IOWHA operator is used for empowerment to enhance the accuracy of the forecast of carbon dioxide emissions. The results show that the carbon dioxide emissions of generation side in 2020 will reach 4.50209 billion tons. According to parameter settings of each influencing factor and scene settings, eight kinds of scenarios are established, and then each scenario is forecast and analyzed. According to the results of influencing factors analysis and scenario analysis, the corresponding strategies to reduce carbon emissions are put forward.