Integrated Optimization of Urban Rail Train Timetable and Bidirectional Converter Characteristics

The significant energy consumption issue in urban rail transit has attracted widespread attention, with the insufficient utilization of regenerative energy from trains being a significant constraint to reducing energy consumption. This paper proposes an integrated optimization method for the urban rail train timetable and bidirectional converter characteristics to address urban rail operations' energy efficiency and safety. First, the output characteristics on the DC side of the bidirectional converter under capacity constraints are analyzed. Then, a multi-objective optimization model is constructed to minimize traction energy consumption and grid voltage fluctuations. This model combines the power flow calculation method for bidirectional converter-driven traction systems with the Fast, Non-dominated Sorting Genetic Algorithm (NSGA-II) to solve the Pareto front solution set and selects the optimal solution for the timetable and bidirectional converter characteristics using the distance-based ideal point method. Finally, simulations based on a metro line in Beijing are conducted for verification. The results show that, compared to the original parameters, the optimized traction energy consumption and grid voltage fluctuation values are reduced by 7.7% and 23.1%, respectively, achieving safe and efficient operation of the urban rail multi-train system.