This paper deals with the design of underground rail system timetables that synchronize the movement of trains to allow the energy consumption from substations to be reduced by maximizing the use of regenerative-braking energy. Nowadays, most trains are equipped with regenerative-braking systems and any of this recovered energy not used by on-board auxiliary services can be consumed by other trains in the same rail section. A mathematical programming optimization model has been designed to synchronize the braking of trains arriving at station with the acceleration of trains exiting from the same or another station. In addition, a power flow model of the electrical network has been developed to calculate the power-saving factor for each synchronization event in order to encourage better synchronizations, particularly those which have fewer energy losses. These models were applied in the design of a schedule for line 3 of the Madrid underground system. This schedule was then trialled for a week. Energy savings were measured and a significant correlation with the synchronization of train movements was observed. It was concluded that a modification in the published timetables would result in energy savings, with no effect on the quality of service for passengers and low associated investment costs.

Traffic operation has a significant impact on energy consumption in metro lines and thus it is important to analyze strategies to minimize it. In lines equipped with Automatic Train Operation systems (ATO), traffic regulation system selects one ATO speed profile on line among a preprogrammed set of optimized speed profiles. Previous works only minimize the energy demanded by the train in pantograph without considering energy savings measured at substations due to regenerative energy in detail. The main objective of this work is to design optimal ATO speed profiles of metro trains taking into account the energy recovered from regenerative brake in order to minimize the net energy at substations. A model of a train with an on-board energy storage device as well as a network model for estimating the energy recovered by the train is presented. Different scenarios are analyzed to assess the achievable energy savings due to possible investments such as installing power inverters or storage devices and energy savings due to the optimal design of ATO speed profiles are estimated. A real line of the Madrid Underground has been considered obtaining comparative results to facilitate an evaluation of the most advantageous scenario and possible investment. A future application would be the optimal design of driving for the newest train signaling system communications-based train control (CBTC). The CBTC improves train operation and control, due to continuous communication with each train. However, its features have not been taken full advantage yet to reduce the energy consumption. The proposed method could be applied to design and execute in real time the most energy-efficient driving according to the traffic and electrical situation of the line.

Metropolitan railway operators' strategic plans include nowadays actions to reduce energy consumption. The application of ecodriving initiatives in lines equipped with automatic train operation (ATO) systems can provide important savings with low investments. Previous studies carried out under the ATO framework have not considered the main uncertainties in the traffic operation: the train load and delays in the line. This paper proposes a method to design robust and efficient speed profiles to be programmed in the ATO equipment of a metro line. First, an optimal Pareto front for ATO speed profiles that are robust to changes in train load is constructed. There are two objectives: running time and energy consumption. A robust optimization technique and an alternative method based on the conservation of the shape of the speed profiles (pattern robustness) are compared. Both procedures make use of a multi objective particle swarm optimization algorithm. Then, the set of speed profiles to be programmed in the ATO equipment is selected from the robust Pareto front by means of an optimization model. This model is a particle swarm optimization algorithm (PSO) to minimize the total energy consumption considering the statistical information about delays in the line. This procedure has been applied to a case study. The results showed that the pattern robustness is more restrictive and meaningful than the robust optimization technique as it provides information about shapes that are more comfortable for passengers. In addition, the use of statistical information about delays provides additional energy savings between 3% and 14%.

Trains equipped with automatic train operation (ATO) systems are operated between stations according to the speed commands they receive from balises. These commands define a particular speed profile and running time, with associated energy usage (consumption). The design of speed profiles usually takes into account running times and comfort criteria, but not energy consumption criteria. In this article, a computer-aided procedure for the selection of optimal speed profiles, including energy consumption, which does not have an effect on running times, is presented. To this end, the equations and algorithms that define the train motion and ATO control have been modelled and implemented in a very detailed simulator. This simulator includes four independent modules (ATO, motor, train dynamics, and energy consumption), an automatic generator of every possible profile and a graphical assistant for the selection of speed commands in accordance with decision theory techniques. The results have been compared with measured data in order to adjust and validate the simulator. The implementation of this new procedure in the Madrid underground has led to a 13 per cent of energy saving. As a result, the decision has been taken to redesign all the ATO speed profiles on this underground.