A novel railway power systems design methodology using genetic algorithms: models and application

The development and the upgrade of railway networks is one of the strategies to reach decarbonization targets in the transportation field, thanks to the considerably lower energy consumption of electric trains with respect to other vehicles, typically fossil fuel powered. The design process of electric railway power systems is complex, requiring advanced simulation tools. The paper proposes a novel methodology for the design of the electrical power system of railway tracks, using genetic optimization. For this purpose, the authors developed ROAR, a flexible simulation and optimization software that generates optimized railway power system designs, helping engineers find the most efficient design solutions from a technical and economic feasibility perspective. After validating the simulation engine and comparing it with well-established software, the proposed method was applied to an operational electrified railway line in Italy to assess the effectiveness of the optimization algorithm. The results demonstrate excellent convergence properties, finding a different infrastructure design that achieves the same electrical performance, reducing costs with respect to the existing design.