Optimization Analysis of Carbon Flow Calculation Model Based on Graph Models
Aiming at the limitations of traditional carbon flow calculation methods in dealing with the complexity of power systems,a graph model and graph neural network-based optimization analysis method for power system carbon flow calculation mode is proposed.This method represents the power system as a graph structure,fully considering the correlation between nodes,and more accurately describing the distribution characteristics of carbon flow.On this basis,the graph neural network optimization calculation mode is introduced,utilizing its powerful feature extraction and correlation modeling capabilities to automatically learn the complex carbon flow distribution patterns in the power system.The results indicate that the proposed optimization method has significantly improved computational accuracy and efficiency,providing strong technical support for achieving low-carbon power systems.
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