Analysis of carbon emission, carbon displacement and heterogeneity of Guangdong power industry

The marginal carbon emission factor can more accurately reflect the real-time carbon emission of the system. Based on the hourly output, load and external power data of Guangdong Province from 2017 to 2020, this paper uses the seemingly unrelated regressions (SUR) model to calculate the marginal carbon emission factor and carbon displacement coefficient of Guangdong’s power industry and compares them with the average carbon emission intensity, which can provide support for the formulation of emission reduction policies in the province. The study shows that the average carbon emission factor underestimates the actual carbon emission of the power system, and the marginal carbon emission factor is a more appropriate indicator to reflect the carbon emission of the system in policy regulation. In addition, this paper also analyzes the annual, quarterly and peak–valley heterogeneity of marginal carbon emissions. The results show that the marginal carbon emission factor at peak demand times increases significantly, featuring more gas turbines participating in power generation.