In the current context of searching for measures to mitigate climate change, Mass Transit Systems (MTS) are a one of the most sustainable alternatives for urban transport. Railway operators have a great interest in improving the electrical infrastructure of these systems in order to reach the maximum levels of energy saving. Installations associated with these improvements involve big investments that need to be adequately assessed. However, the methodology to determine the optimal design of these installations is not sufficiently developed in the scientific literature: decisions are usually made by means of unrealistic railway simulators or even based only on the experience of railway infrastructure managers. In consequence, providing a rigorous and detailed methodology for designing the installation of the MTSs’ infrastructure improvements has become a demand of railway infrastructure managers and a necessity for society. This PhD tries to respond to this demand and addresses the proposal of a methodology with those requirements. The methodology is based on the application of nature-inspired optimization algorithms (genetic algorithm, particle swarm optimization algorithm and fireworks algorithm) to optimize the installation of Reversible Substations and Energy Storage Systems. The algorithms make use of a realistic railway simulator to properly assess the impact of installing these improvements on the MTS energy efficiency. The realistic railway simulator develops some features missing in the literature: a detailed traffic model able to generate representative-enough traffic scenarios and the capability of dealing with any type of line topology.
Keywords: Energy efficiency; Train regenerative braking; Optimization of railway electrical infrastructures; Railway power systems; Railway simulation; Nature-inspired optimization algorithms.
Universidad Pontificia Comillas. Madrid (Spain)
July 2nd, 2020
D. Roch Dupré (2020), Improving the electrical infrastructure of dc-electrified railway systems to increase energy efficiency, taking into account complex topologies and representative traffic scenarios. Universidad Pontificia Comillas. Madrid (Spain).