This study presents a multiscale, multiagent simulation approach aimed at enhancing global energy efficiency in urban rail transit systems. By examining the underlying mechanism of energy efficiency emergence, it conceptually distinguishes energy efficiency from energy consumption, focusing on the optimization of infrastructure performance and its scientific utilization, particularly in train control and transport organization. Global energy efficiency is promoted through the cooperative evolution of micro-level components—trains, stations, lines, dispatching sub-centers, and a dispatching center. A general agent model is developed to generate these components, while an energy efficiency algorithm platform, incorporating a 0–1 integer programming model for the decomposition of the global energy efficiency index, identifies key influencing factors to guide targeted strategies for energy efficiency improvement. The proposed strategies have the potential to reduce energy consumption by 12.40% to 16.51% and increase energy efficiency by 14.16% to 19.77%. The findings suggest that enhancing energy efficiency goes beyond merely reducing consumption, emphasizing the foundational role of the energy efficiency emergence mechanism in improving the global energy efficiency of urban rail transit systems. Moreover, the results highlight the need for adaptable simulation platforms capable of supporting diverse urban rail transit systems at various stages of development.
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