Method for analyzing carbon emission intensity of regional power system based on carbon emission impact factor and systematic perspective

All countries have set the goal of achieving "carbon peak and carbon neutrality," in which carbon emission assessment is the basis for developing carbon reduction measures. A method for calculating and analyzing the carbon emission intensity of regional power systems based on carbon emission influencing factors and a systematic perspective is proposed in this paper, which identifies the main influencing factors of carbon emissions and implements relevant policies and regulations to achieve carbon peak. Firstly, carbon emission impact factors are provided, considering the energy-economy-electricity-environment (4E) balance system. To support accurate carbon emissions monitoring, relevant data are collected, including energy consumption, economic growth rate, electricity production, and carbon emission indicators. The influence contribution is quantified using methods such as the improved Kaya constant equation. Logarithmic means the Divisa Index approach (LMDI), which selects the divers with solid correlation. Secondly, the carbon emissions data are pre-processed using the Ensemble Complementary Empirical Modal Decomposition (ECEMD) method. Finally, the future carbon emission trend is predicted using the Particle Swarm Optimization Long and Short-Term Memory Network (LSTM) algorithm. Some real power system data are used to verify the method's effectiveness and perform predictive analysis for the example.