Modeling and simulation of future railways

Abstract: This master thesis project aims at improving a train power system program which simulates the interaction between a predefined train power supply system structure and a train traffic schedule. The simulator, called TPSS (Train Power System Simulator), is used for training TPSA (Train Power System Approximator) which is included in a larger investment planning program where the welfare of the society is to be maximized. The development of the railway power system implies wise investments that should last a long time. In order to make the good decisions, the consequences of different power system configurations related to the future train traffic demands have to be studied. Aiming at an investment planning in the long term, models and methods used by the simulator for the railway power system and the electric traction devices are of great importance. In this thesis electrical and mechanical models are presented and improvements are discussed thereafter. Moreover methods were modified to improve the accuracy and reduce the simulator running time. Indeed reduction of the computation time is really important when a great variety of cases are studied. In addition some further controls are implemented to obtain more workable and more realistic outcomes. Some bugs are fixed and the former models are changed aiming at a faster computation time and a better quality of the results. Comparisons between the different simulator versions are presented along the report to illustrate the benefits of the changes. Finally a global examination showing impacts of all improvements is performed. As explained the program TPSS intends to participate in a long term investment planning suggestion. The program.s outcomes of several simulations would be extracted to train a Neural Network. The latter will aim at approximating outcomes for other cases avoiding too many simulations and thus saving time.