Assessment of the worthwhileness of efficient driving in railway systems with high-receptivity power supplies

Eco-driving is one of the most important strategies for significantly reducing the energy consumption of railways with low investments. It consists of designing a way of driving a train to fulfil a target running time, consuming the minimum amount of energy. Most eco-driving energy savings come from the substitution of some braking periods with coasting periods. Nowadays, modern trains can use regenerative braking to recover the kinetic energy during deceleration phases. Therefore, if the receptivity of the railway system to regenerate energy is high, a question arises: is it worth designing eco-driving speed profiles? This paper assesses the energy benefits that eco-driving can provide in different scenarios to answer this question. Eco-driving is obtained by means of a multi-objective particle swarm optimization algorithm, combined with a detailed train simulator, to obtain realistic results. Eco-driving speed profiles are compared with a standard driving that performs the same running time. Real data from Spanish high-speed lines have been used to analyze the results in two case studies. Stretches fed by 1 × 25 kV and 2 × 25 kV AC power supply systems have been considered, as they present high receptivity to regenerate energy. Furthermore, the variations of the two most important factors that affect the regenerative energy usage have been studied: train motors efficiency ratio and catenary resistance. Results indicate that the greater the catenary resistance, the more advantageous eco-driving is. Similarly, the lower the motor efficiency, the greater the energy savings provided by efficient driving. Despite the differences observed in energy savings, the main conclusion is that eco-driving always provides significant energy savings, even in the case of the most receptive power supply network. Therefore, this paper has demonstrated that efforts in improving regenerated energy usage must not neglect the role of eco-driving in railway efficiency

Speed profile optimization of an electrified train in Cat Linh-Ha Dong metro line based on pontryagin's maximum principle

An urban railway is a complex technical system that consumes large amounts of energy, but this means of transportation still has been obtained more and more popularity in densely populated cities because of its features of high-capacity transportation capability, high speed, security, punctuality, lower emission, reduction of traffic congestion. The improved energy consumption and environment are two of the main objectives for future transportation. Electrified trains can meet these objectives by the recuperation and reuse of regenerative braking energy and by the energy - efficient operation. Two methods are to enhance energy efficiency: one is to improve technology (e.g., using energy storage system, reversible or active substations to recuperate regenerative braking energy, replacing traction electric motors  by energy-efficient traction system as permanent magnet electrical motors; train's mass reduction by lightweight material mass...); the other is to improve operational procedures (e.g. energy efficient driving including: eco-driving; speed profile optimization; Driving Advice System (DAS); Automatic Train Operation (ATO); traffic management optimization...). Among a lot of above solutions for saving energy, which one is suitable for current conditions of metro lines in Vietnam. The paper proposes the optimization method based on Pontryagin's Maximum Principle (PMP) to find the optimal speed profile for electrified train of Cat Linh-Ha Dong metro line, Vietnam in an effort to minimize the train operation energy consumption

A review of modelling and optimisation methods applied to railways energy consumption

[EN] Railways are a rather efficient transport mean, and yet there is increasing interest in reducing their energy consumption and making them more sustainable in the current context of climate change. Many studies try to model, analyse and optimise the energy consumed by railways, and there is a wide diversity of methods, techniques and approaches regarding how to formulate and solve this problem. This paper aims to provide insight into this topic by reviewing up to 52 papers related to railways energy consumption. Two main areas are analysed: modelling techniques used to simulate train(s) movement and energy consumption, and optimisation methods used to achieve more efficient train circulations in railway networks. The most used methods in each case are briefly described and the main trends found are analysed. Furthermore, a statistical study has been carried out to recognise relationships between methods and optimisation variables. It was found that deterministic models based on the Davis equation are by far (85% of the papers reviewed) the most common in terms of modelling. As for optimisation, meta-heuristic methods are the preferred choice (57.8%), particularly Genetic Algorithms.Martínez Fernández, P.; Villalba Sanchis, I.; Yepes, V.; Insa Franco, R. (2019). A review of modelling and optimisation methods applied to railways energy consumption. Journal of Cleaner Production. 222:153-162. https://doi.org/10.1016/j.jclepro.2019.03.037S15316222

An integrated metro operation optimization to minimize energy consumption

Energy efficient techniques are receiving increasing attention because of rising energy prices and environmental concerns. Railways, along with other transport modes, are facing increasing pressure to provide more intelligent and efficient power management strategies. This paper presents an integrated optimization method for metro operation to minimize whole day substation energy consumption by calculating the most appropriate train trajectory (driving speed profile) and timetable configuration. A train trajectory optimization algorithm and timetable optimization algorithm are developed specifically for the study. The train operation performance is affected by a number of different systems that are closely interlinked. Therefore, an integrated optimization process is introduced to obtain the optimal results accurately and efficiently. The results show that, by using the optimal train trajectory and timetable, the substation energy consumption and load can be significantly reduced, thereby improving the system performance and stability. This also has the effect of reducing substation investment costs for new metros

System energy optimisation strategies for DC railway traction power networks

Energy and environmental sustainability in transportation are becoming ever more important. In Europe, the transportation sector is responsible for about 32% of the final energy consumption. Electrified railway systems play an important role in contributing to the reduction of energy usage and C0$_2$ emissions compared with other transport modes. Previous studies have investigated train driving strategies for traction energy saving. However, few of them consider the overall system energy optimisation. This thesis analyses the energy consumption of urban systems with regenerating trains, including the energy supplied by substations, used in power transmission networks, consumed by monitoring trains, and regenerated by braking trains. This thesis proposes an approach to searching energy-efficient driving strategies with coasting controls. A Driver Advisory System is designed and implemented in a field test on Beijing Yizhuang Subway Line. The driver guided by the DAS achieves 16% of traction energy savings, compared with normal driving. This thesis also proposes an approach to global system energy consumption optimisation, based on a Monte Carlo Algorithm. The case study indicates that the substation energy is reduced by around 38.6% with the system optimised operations. The efficiency of using regenerative braking energy is improved to from 80.6 to 95.5%

System energy optimisation strategies for metros with regeneration

Energy and environmental sustainability in transportation are becoming ever more important. In Europe, the transportation sector is responsible for about 30% of the final end use of energy. Electrified railway systems play an important role in contributing to the reduction of energy usage and CO2 emissions compared with other transport modes. For metro-transit systems with frequently motoring and braking trains, the effective use of regenerated braking energy is a significant way to reduce the net energy consumption. Although eco-driving strategies have been studied for some time, a comprehensive understanding of how regeneration affects the overall system energy consumption has not been developed. This paper proposes a multi-train traction power network modelling method to determine the system energy flow of the railway system with regenerating braking trains. The initial results show that minimising traction energy use is not the same as minimising the system energy usage in a metro system. An integrated optimisation method is proposed to solve the system energy-saving problem, which takes train movement and electrical power flow into consideration. The results of a study of the Beijing Yizhuang metro line indicate that optimised operation could reduce the energy consumption at the substations by nearly 38.6% compared to that used with the existing ATO operation

DC railway power supply system reliability evaluation and optimal operation plan

With the continuous and rapid development of the economy and the acceleration of urbanisation, public transport in cities has entered a period of rapid development. Urban rail transit is characterised by high speed, large traffic volume, safety, reliability and punctuality, which are incomparable with those of other forms of public transport. The traction power supply system (TPSS) is an important part of an electrified railway, and its safety issues are increasingly prominent. Different from the substation in a general power system, the load of a TPSS has a great impact on the traction transformer; moreover, in order to ensure normal operation of the train in case of failure, the traction substation must be able to access a cross-district power supply, as it has a high demand for reliable operation. The safe and reliable operation of DC TPSSs is the basis of the whole urban railway transit system. Previous studies have investigated the reliability of the TPSS main electrical wiring system. However, the impact of traction load and the actual operation of trains on system reliability has not been considered when designing a DC railway power supply system. The purpose of the research for this thesis is to find an optimal system operation plan for urban railways, considering load characteristics. This thesis begins with a review of the main arrangements of DC railway power supply systems and the literature on railway reliability studies. A model of single train simulation and a power supply system is established in MATLAB. The developed simulator is then integrated with a TPSS reliability model to evaluate the energy and reliability performance of DC railway power systems. Based on the train traction load model and train schedule, a comprehensive method for evaluating a DC TPSS considering traction load is proposed. Through simulation of the actual operation of the train group, the system energy consumption and substation life loss generated under different train operation diagrams and schedules are compared to provide a reference for the reasonable design of the timetable. Taking the life loss and energy consumption of the whole TPSS as the objective function, a genetic algorithm is used to optimise the train speed, coasting velocity, station dwell time and headway to find the optimal operation strategy. This is illustrated with a case study of the Singapore East–West metro line. The study has addressed the following issues: development of a multi-train power simulator, evaluation of reliability performance, and finally the search for an optimal operation plan. The train running diagram and timetable are optimised jointly. This can help railway operators make decisions for an optimal operation plan and reduce the operation risk of the power system

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

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