Methodology for Multiobjective Optimization of the AC Railway Power Supply System

Abstract

Electrical dimensioning design in a railway infrastructure has high complexity and is strongly nonlinear. There are several parameters and constraints to take into account. The presented methodology is working to improve the decision making about the design, hence developing an expert system. The final set of possible solutions that the method is achieved is based on a pair of main objectives. On the one hand are installation costs, environmental impact, main electrical components costs such as catenary, traction substations, neutral zones, and the difficulty to connect substation to general electric grid. On the other hand are exploitation costs, such as maintenance costs and energy loss depending on the dimensioning design. A specific line discretization has been developed in order to distribute the critical zones along the line. Integration of a multiobjective genetic algorithm (NSGA-II), hence the code of the genotype, is another highlight. Electrical analysis, railway systems using single alternate current (1 × 25), and a simplification due to the search of the highest peaks of power demanded by the trains during simulations help to minimize the quantity of studies. Every simulation is possible by using a railway simulator, Hamlet, which provides modules such as infrastructure, rolling stock, signaling, and electrical. Designers have the possibility to analyze several scenarios with different railway exploitation critical levels, analyze electrical degraded situations, and finally obtain an optimal Pareto Front, reaching a powerful methodology to help in the electrical dimensioning design.