The synergistic development of economic construction and low-carbon transformation of energy systems must be promoted for building a green, low-carbon, and cyclic economic system and achieving the “double carbon” goal in China. Based on the panel data of 30 provincial-level administrative regions in China from 2015 to 2019, the global entropy method, coupling coordination degree model, and spatial statistical analysis methods are applied to analyse the factors affecting the coupling effect. The coordination degree increased in the study period, with Beijing, Shanghai, Tianjin, Jiangsu, and Zhejiang being the regions with the highest values. The spatial distribution of the coupling coordination degree is strongly positively correlated with the eastern provincial-level administrative regions located in the high–high concentration area of the Moran scatterplot and western provincial-level administrative regions concentrated in the low–low concentration area. The spatial association pattern is stable in the study period, with only two provinces exhibiting a transition: Shandong province made the transition to high–high agglomeration areas, and Liaoning province made the transition to low–low agglomeration areas. The level of regional economy, urbanization process, energy consumption structure, and level of investment in science and innovation enhance the coupling coordination degree, whereas the industrial structure deteriorates this degree.