TransEnergy - a tool for energy storage optimization, peak power and energy consumption reduction in DC electric railway systems

Abstract

Electrified railways are large users of electrical power at a time when grid supply conversion to renewable energy production is making supply to the grid less predictable and environmental concerns demand reduction in energy use. These developments make it desirable to control and reduce both total energy usage and peak power demand of railway systems. While AC systems have a well-developed ability to regenerate power to the grid, high transmission losses in DC systems make local storage of energy a more attractive option. A model has been created integrating a versatile and configurable database-driven generic rail network model with a power supply network representative of DC electric railways. The work is intended as a high-level design tool to explore system wide behaviors prior to detailed final design modelling of specific technologies. To validate our method, predictions of train motion and power demand have been compared with data from the Merseyrail network in the UK. Simulating a full day of traffic for the Wirral Line of Merseyrail (237 services on two routes) with the assumption of energy storage being available at each electrical sub-station revealed the dependence of storage effectiveness on the timetable and traffic density at specific locations. The model is combined with a genetic algorithm to optimise system parameters (storage size, charge/discharge power limits, timetable, train driving style/trajectory) and also enables identification of cases in which poorly specified storage technology would have little impact on peak power and energy consumption