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

Q1 Engineering

Transportation Engineering Pub Date : 2026-03-01 Epub Date: 2026-02-17 DOI:10.1016/j.treng.2026.100429

Ahmed Abughali , Ameena Saad Al-Sumaiti , Shaikha Alteneiji , Mrityunjay Kumar Mishra

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Abstract

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.

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电气化铁路运营优化：能源效率、行程时间和可再生能源利用

电气化铁路系统因其能源效率和低排放而成为可持续交通的基石。通过最大限度地减少电力消耗和行驶时间，同时最大限度地利用再生制动能量，加强列车运行期间的能源管理，对于提高可操作性和环境绩效至关重要。本研究将多目标优化问题表述为混合整数非线性规划（MINLP）模型，旨在同时实现这些目标。基于不同电气化铁路案例研究的数值分析证明了所提出方法的有效性，揭示了能源消耗和旅行时间的大幅减少，以及可再生能源的改善利用。优化后的溶液再生率为29.00%，与所有其他案例研究相比，这一比例要高得多。研究结果强调了在城市轨道系统中广泛实施该框架以支持更可持续、更高效的铁路运营的潜力。

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