Energy Efficiency in Electric Transportation Systems

1. Introduction

Increasing energy efficiency in electric transportation systems is a topical issue, considering the worldwide concern for reducing CO₂ emissions, and especially through the significant reduction in energy loss and energy consumption.

There have been many examples of research in recent years and results published in scientific papers regarding new solutions to increase energy efficiency in railway traction systems, the power quality issue in traction systems, and traction power management, including the efficient management of regenerative braking energy.

This Special Issue is dedicated to presenting new approaches to energy efficiency in electric transportation systems.

The following section provides a brief review of the published papers on this topic.

2. A Short Review of the Contributions in This Topic

Haładyn, in [1], presented new challenges facing the modernization of railways in Poland based on a case study. The problem of the efficiency of the power supply system (3 kV DC) is analyzed in the context of the growing use of electric vehicles, which have a higher demand for electricity than the old ones. Critical problems in scheduling the use of the railway system are highlighted. It is pointed out that, in the timetable design process, it is absolutely necessary to take into consideration the admissible load capacity of the power network in all traffic situations.

In [2], based on the experimental measurements carried out on board a train, Cipolletta et al. quantified the amount of braking energy that can be potentially recovered adopting energy storage systems located in supply substations, in a real case study of a specific route on the Italian rail network. Additionally, an optimal level of voltage regarding the efficiency of the recovery process has been identified, taking into account the additional losses in the catenary, and the design of a stationary energy recovery system considering two energy management strategies has been achieved. It is shown that about 73% of the braking energy can be recovered.

Radaš et al. in [3] proposed a regenerative braking system for an electric tram to reduce the electric current peaks and increase the energy efficiency by reducing the consumption of electrical energy in the supply network. To store and use the braking energy, a supercapacitor module is used. The proposed control algorithm takes into account the influence of gravitational force on the vehicle. It is presented first in a variant which minimizes the energy taken from the supply network and then in a variant of minimum gradient which minimizes the number of peak currents over 1000 A. The operation of the control algorithm was tested on two lines of the Zagreb Electric Tram. It is shown that the maximum peak currents can be reduced up to 20%, and the total energy taken from the supply network can be reduced up to 21% by using regenerative braking energy.

The topic of efficiency in the railway transportation sector, along with that in the electrical vehicle and marine sectors, is well approached by Brenna et al. in their review paper [4]. The summarized solutions for improving the efficiency in the railway transportation sector are based on driving style management, timetable optimization, and innovative storage system integration (stationary and onboard energy storage systems).

An extensive review of power quality aspects, in terms of characteristics, influencing factors, and occurrence sources for different configurations of electric railway power systems, is provided by Kaleybar et al. in [5], and a systematic classification is presented. The different types of harmonics, system unbalance, low power factor, transient aspects, waveform deviations, and electromagnetic interference aspects are covered in detail.

A comprehensive review on the energy efficiency improvement in DC railway systems is presented by Popescu and Bitoleanu in [6]. After the presentation of the solutions for power quality conditioning in the traction regime of the traction substations and the braking energy storage solutions, the attention is directed to reversible substations. An overview of different achievements, implementations, and commercial solutions grouped on categories is provided. It is highlighted that the onboard storage systems are preferred as braking energy recovery in light railway systems due to their flexibility and moderate investment cost. Although more costly, wayside storage systems and reversible substations are the best solution to increase the efficiency of the whole system. Depending on concrete application, the best solution, even a hybrid one, can be selected.

In the comprehensive review paper [7], Khodaparastan et al. investigated and compared various methods for regenerative energy recuperation, including train timetable optimization, onboard and wayside energy storage systems, and reversible substations. It is illustrated that between 4% and 34.5% energy saving has been claimed through timetable optimization. It is also highlighted that about 30% of the energy consumed by the train can be saved by using energy storage systems. Regarding the use of reversible substations, up to 13% of the consumed energy by a vehicle can be fed back to the power supply.

In the specific situation of a train operating in a Madrid metro line in which a reversible substation has been installed, Cascetta et al. in [8] presented the onboard accurate measurement results related to energy flows and losses for both reversible regime operation and traction regime operation. An index of unavailability of the line to accept energy has been defined as the ratio of the energy dissipated by the braking rheostats and the braking energy. The average values of this index in case of high traffic (10% without reversible operation and 8% with reversible operation) and in case of low traffic (22% without reversible operation and 16% with reversible operation) highlight the greater impact of the reversible substation when few trains are running.

In order to compare the benefits of a reversible traction substation, a wayside energy storage system and an onboard energy storage system, Ramsey et al., in [9], modeled and simulated a DC railway system and then validated the results with real measures taken on a French railway system (Réseau Express Régional). A reduction of up to 30% of the total supplied energy is highlighted.

In [10], Urbaniak and Kardas-Cinal proposed an indirect optimization of the electrical energy recovered, to be used immediately by another vehicle, by maximizing the energy co-optimization duration. Taking into account the weighting factors of different objective functions, both single and multi-criteria optimizations can be applied in the proposed approach, which are important from the point of view of the operator, the infrastructure manager, and the passenger. It is highlighted that, in terms of organization, it is possible to increase the effects of energy cooperation among trains using the operating time reserve included in the timetable, especially by delaying the arrival or departure of a train at a particular station. The presented results are based on the train timetables used by some of the largest railway stations in Poland.

In [11], Su et al. developed an integrated energy-efficient optimization model in order to reduce the net energy consumption of the metro system. The timetable optimization, eco-driving, as well as a good utilization of the regenerative energy are integrated, so that a good energy-efficient performance is obtained. For the case study of the Beijing Yizhuang metro line, it is shown that the reused regenerative energy is increased by 161.65% for off-peak hours and by 168.68% for peak hours.

Li et al., in [12], are concerned with the minimization of the total energy consumption in urban railways while maximizing service quality, by proposing a multi-objective optimization model with timetable optimization. It was applied for the case study of the Yizhuang urban railway line in Beijing, and it was shown that the optimal quality of the service timetable reduced the total energy consumption by 6.09%, without increasing the deviation of train running time.

Solving the train-timetable-rescheduling problem is the objective of the research of Liao et al. in [13]. By using a modified genetic algorithm–gate recurrent unit real-time method based on deep learning, it is shown that a well-trained decision network can provide effective solutions after random disturbances occur, so that the net traction energy consumption of trains is optimized. In order to verify the energy-saving effect and real-time performance of the proposed method in solving the timetable-rescheduling problem, a comprehensive model of the Shanghai Metro Line One pilot network as a training and testing environment has been conceived. The results show that in the two-train metro system, the three-train metro system, and the five-train metro system, the proposed method can save an average of 4.45%, 6.16%, and 7.19% of energy, respectively.

To ensure the performance of the automatic train operation system through speed profile design and tracking control, an integrated optimal method has been proposed in [14] by Pu et al. through the design of a speed profile and fuzzy PID controller that adaptively adjusts the parameters. For the case study of Beijing Subway Line 8, it is shown that an energy saving of about 10.40% is obtained.

The application of an energy-efficient driving strategy has been achieved through the development of the SmartDrive package by Tian et al. in [15]. An optimization method for the train trajectory together with the driver training and an awareness package have been developed to be used on trams, metros, and some heavy rail systems. Based on the real daily operations in the Edinburgh Tram Line and field trials, it has been shown that energy savings of 10–20% are achievable.

In the study [16] proposed by Wu et al., the attention is directed, from the point of view of the energy flow, towards the train speed trajectory optimization with the constraints of onboard energy storage devices’ capacity, the initial state of energy, and degradation by using mixed integer linear programming. It is illustrated that more than 11.6% of net energy consumption can be reduced compared to that without onboard energy storage devices.

Roch-Dupré et al. in [17] deal with the problem of finding the optimal location and sizing of energy storage systems in DC railway systems. The use of a multi-method approach named “The Coral Reefs Optimization with Substrate Layers” is proposed to carry out an accurate search for the optimal solution to the problem. The good performance of this method is illustrated for determining the location and sizing of the energy storage system in a real Spanish metro line.

In [18], Morea et al. demonstrated that, by implementing the coasting strategy on board trains with an embedded control system, significant energy savings can be achieved. A simulation model capable of optimizing the coastal strategy was developed based on the dynamic model of a railway convoy. The proposed model is of general purpose and can also be used for other motion phases. It is shown that, by using a coasting-run technique to reach the arrival stations, companies can achieve savings of more than 10%.

Gołebiowski et al. presented in [19] an approach to energy-efficient rail freight planning based on an example of the area of Poland. A method that covers the allocation of railway vehicles dedicated to freight traffic is proposed to fulfill a defined transport task, taking into account evaluation of the energy efficiency of the solution, the route of the train launched in order to carry out the transport task, and determination of the transport conditions for a defined transport task, with consideration of the allocated rolling stock and the route. A decision-making model is proposed, including model parameters, solution quality assessment indicators, and the limitations and boundary conditions of the problem. As a criterion, the function of minimizing the energy consumption required for transport within the railway network is proposed.

Kuzior and Staszen highlighted in [20] the limitations of energy management in railway companies, resulting from the adopted model of market regulation. They also indicated the practical methods used by market participants, so that the energy efficiency is improved and a positive effect on the environment is obtained. The energy management in DB Cargo Polska from Poland is presented and it is shown that, despite the existing limitations, railway companies undertake various activities aimed at improving their energy efficiency and can demonstrate the combined efficiency of their activities.

In [21], Pomykala and Szelag presented an analysis of energy efficiency and the effectiveness of CO₂ reduction due to putting ED250 trains (Pendolino—the first high-speed trains in Poland) into service in the railway network. In order to compare the service parameters on the main railway lines where ED250 trains operate, simulation methods were used for running ED250 passenger trains and equivalent locomotives.

In [22], Restel et al. proposed a method for designing robust and energy-efficient railway schedules by carrying out successive iterations and simulations with undesirable events. As a result, the energy losses in the system are minimized.

A detailed and comprehensive review of modern technologies and projects in the field of renewable energy systems for the railway transport is provided by Mitrofanov et al. in [23]. Different configurations of solar and wind power plants are described and various types of energy storage devices used in projects for the electrification of railway transport are analyzed. Technologies for accumulating and converting hydrogen into electrical energy and hybrid systems are also discussed.

3. Conclusions

The scientific papers referenced in this Special Issue provide new information and findings on the energy efficiency in electric transportation systems. They are mainly related to: the optimal scheduling of the use of the railway system; improvement in power network reliability; energy management strategies; driving style management; timetable optimization; innovative storage system integration (stationary and onboard energy storage systems) to optimally store and reuse the braking energy through proper control algorithms; and power quality conditioning solutions.

I strongly believe that all the information presented will be very useful to the scientific community to deal with various aspects of improving energy efficiency in electric transportation systems. It can also stimulate researchers in the field to make new contributions to the topic.