Volume 43: Energy Transitions toward Carbon Neutrality: Part VI

Understanding Human Mobility Patterns from Urban Energy Consumption Records: Through Electric Vehicle Charging Records Dou Huang, Junxiang Zhang, Zhiling Guo, Shibo Zhu, Xiaodan Shi,Wenjie Gong, Haoran Zhang*



This study pioneers a novel method to interpret urban energy consumption through human mobility patterns, utilizing electric vehicle (EV) charging data as a proxy. By applying algorithms like DBSCAN and a pre-trained human mobility model, the research effectively transforms EV charging logs into a detailed map of urban movement. Analyzing data from Shanghai, the study successfully correlates these synthesized mobility trajectories with actual human movement patterns, revealing a strong interplay between EV charging behavior and urban dynamics. This innovative approach not only offers fresh insights into urban energy dynamics but also respects individual privacy, marking a significant advancement in the field of urban planning and sustainable development.

Keywords urban energy system, human mobility patterns, data-driven methodology

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