Energy consumption optimization of train operation for railway systems: Algorithm development and real-world case study.

Abstract Traction energy is the main component of railway operation energy, and a timetable that predefines the running time of train operation can be used to determine the traction energy consumption. This study proposes a bi-level model that optimizes timetables to achieve the energy-saving control of railway systems. The upper level of the model ensures the relative stability of the timetable while maintaining railway safety constraints, which makes train operations more convenient for the railway sector as well as passengers; while the lower level of the model optimizes the arrival and departure time among intermediate stations to minimize the energy consumption of each train. Then, a unified iterative optimization algorithm combining particle swarm is developed to solve the model, and a timetable that ensures energy consumption optimizations is thus obtained. A case study using actual operation data from the Beijing-Shanghai high-speed railway is developed to illustrate the proposed method. Results show that the total energy consumption is reduced by more than 7.6%, and the average adjustment time for each distance interval is approximately 1 min, which maintains the stability of the original timetable. Highlights • A bi-level model is developed to optimize railway energy and passenger convenience. • Energy saving, timetable stability, and train tracking constraints are investigated. • Spare time of timetable are optimally distributed by an iterative-loop algorithm. • Train optimal energy-saving operation strategies are proposed and verified by a case. • The model is applied in a real case saving 7.6% energy consumption. [ABSTRACT FROM AUTHOR]