A Structural Demand-Oriented Framework for Public Charging Infrastructure: Integrating Physical Space and Population Activity in Qingdao, China

Under China’s “Dual Carbon” goals, the electric vehicle (EV) industry has expanded rapidly, while the imbalance between supply and demand in public charging infrastructure (PCI) has emerged as a critical bottleneck. Accordingly, a structural assessment of PCI demand potential is essential for improving planning effectiveness. Focusing on the seven municipal districts of Qingdao, this study developed a dual-dimensional framework integrating physical space and population activity. Five core factors were incorporated: road network accessibility, road network betweenness, POI functional mixing density, population distribution density, and nighttime light intensity. By integrating Spatial Design Network Analysis (sDNA), Kernel Density Estimation (KDE), and the entropy weighting method, we conducted a structural assessment of PCI demand potential and derived spatial demand tiers and hierarchy. The results indicate that: (1) road network betweenness had the highest weight (0.396), acting as the dominant driver of structural demand potential, followed by POI functional mixing density (0.271), whereas nighttime light intensity (0.151) and population distribution density (0.143) functioned as baseline supportive indicators; (2) spatial demand was classified into five levels (Levels 1–5), with Level 1 hotspots exhibiting a radial spatial structure characterized by “one primary core, four secondary cores, three corridors, and multiple nodes”; and (3) while the existing PCI distribution exhibited overall gradient consistency with the structurally derived demand tiers, quantitative deviation results indicated localized mismatches, including under-allocation in high-demand areas and over-allocation in selected lower-demand pockets. The proposed dual-dimensional framework facilitates the identification of structural demand gradients for PCI by explicitly incorporating traffic-flow potential, functional aggregation, and population concentration. These findings provide planning-oriented diagnostic support for PCI configuration and contribute to the sustainable transformation of urban transportation systems in megacities.