Determination of the optimal sizes and locations of hydrogen refueling stations for deploying hydrogen locomotives using multi-objective particle swarm optimization - Sarma, Upasana; Ganguly, Sanjib (Soft computing (Berlin, Germany), 2025)
This study presents a multi-objective, capacitated flow refueling location model aimed at identifying the optimal locations and capacities of hydrogen refueling stations (HRS) to support the deployment of hydrogen-powered passenger trains in the Northeast Frontier Railway (NFR) region of Assam, India. The model simultaneously minimizes two key objectives: the total cost of ownership and the average refueling cost over a specified planning horizon. The analysis assumes centralized hydrogen production for the initial deployment phase and considers existing intercity railway stations in NFR as candidate sites for HRS installation. Optimization is conducted for three scenarios, each with different HRS capacity levels. Real-time intercity railway traffic data from NFR is used as input, and the optimization problem is solved using a Strength Pareto Evolutionary Algorithm 2-based Multi-Objective Binary Particle Swarm Optimization (SPEA2-based-MOBPSO) technique. The resulting Pareto fronts provide a range of optimal HRS layout configurations, highlighting trade-offs between infrastructure investment and operational efficiency.