Optimization of electrified railway operations: Energy efficiency, travel time, and regenerative energy utilization

Electrified railway systems are a cornerstone of sustainable transportation due to their energy efficiency and low emissions. Enhancing energy management during train operations by minimizing power consumption and travel time while maximizing the utilization of regenerative braking energy is essential for improving both operability and environmental performance. This study formulates a multi-objective optimization problem as a Mixed-Integer Nonlinear Programming (MINLP) model aimed at achieving these objectives concurrently. Numerical analysis based on different electrified railway case studies demonstrates the effectiveness of the proposed approach, revealing substantial reductions in energy consumption and travel time, along with improved use of regenerated energy. The optimized solution achieved a regeneration percentage of 29.00%, which is significantly higher compared to all other case studies. The results highlight the potential for broad implementation of the framework in urban rail systems to support more sustainable and efficient railway operations.