Electricity consumption is a major source of greenhouse gas emissions, and understanding its driving mechanisms is crucial for achieving sustainable energy development. However, existing studies often overlook spatial heterogeneity and interaction effects among electricity consumption drivers. This study proposes a Spatial-SHapley Additive exPlanation-Network framework that integrates spatial heterogeneity and interaction effect analysis, validated using 293 prefecture-level cities in China during 2017-2019. The results show that: (1) Total nighttime light intensity and total gross domestic product are the most important electricity consumption drivers; (2) The primary electricity consumption contributors in central, western, and northeastern regions are more diversified, with temperature-related variables particularly influential in southern regions; (3) Total gross domestic product plays a core intermediary role in the electricity consumption driving system. This study provides a new methodological perspective for understanding the spatial heterogeneity and interrelationships of the electricity consumption drivers, and offers a new approach for formulating regional energy policies.
Li et al. (Fri,) studied this question.