Carbon Accounting Method based on Power System Energy Carbon Footprint Characteristics and Multi-Source Data Fusion

Abstract

This paper presents a novel approach to carbon accounting by utilizing the energy use carbon footprint characteristics and data fusion of the electric power system. The method involves analyzing the energy use carbon footprint characteristics of various electric power systems and employing big data analysis and artificial intelligence techniques to accurately evaluate carbon emission sources. The paper outlines the measurement content, model design principles, and model selection strategy, taking into account factors such as carbon data from different sources and the strengths and weaknesses of existing carbon accounting methods. By identifying the factors that influence the carbon footprint of the electric power system under dual carbon targets, a carbon accounting method based on data fusion and the energy use carbon footprint characteristics of the electric power system is proposed. The paper also develops a carbon emission warning model for the electric power system, which can assist businesses and organizations in setting targeted reduction goals.