This study presents the recent application of energy storage devices in electrified railways, especially batteries, flywheels, electric double layer capacitors and hybrid energy storage devices. The storage and reuse of regenerative braking energy is managed by energy storage devices depending on the purpose of each system. The advantages resulting from the use of energy storage devices are presented by observing the results of both verification tests and practical applications in passenger services. Several real installations of energy storage for railways are shown and compared by using the Ragone plot. The effect of the use of energy storage devices on electrified railways of the future is discussed. Finally, a discussion on the recent applications and developments of energy storage devices is presented in this study. The effective use of energy storage devices is characterised on the basis of the specific applications and current trends of the research undertaken by public bodies and manufacturers.

A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration. If this power is reduced, substation peak power will be significantly decreased. This paper presents a study on optimal energy saving in DC-electrified railway with on-board energy storage system (OBESS) by using peak demand cutting strategy under different trip time controls. The proposed strategy uses OBESS to store recovered braking energy and find an appropriated time to deliver the stored energy back to the power network in such a way that peak power of every substations is reduced. Bangkok Mass Transit System (BTS)-Silom Line in Thailand is used to test and verify the proposed strategy. The results show that substation peak power is reduced by 63.49% and net energy consumption is reduced by 15.56% using coasting and deceleration trip time control.

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This paper presents a methodology to design the optimal capacitances and locations of stationary supercapacitors for light DC railways based on a single train simulator. The objective function of the optimisation problem takes into account the energy consumption of the substations and the total line energy loss. The problem includes an isoperimetric constraint to maintain to zero the net energy supplied by supercapacitors at the end of each cycle. The suitable fitting weight coefficients employed in the objective functions can be obtained by the Genetic Algorithm and Particle Swam Optimisation. The learning process of the optimisation procedure studies the effect of the energy storage capacity for different positions of supercapacitors along the track. From the optimisation algorithm it has been found that the minimal capacitance for each section is obtained when supercapacitors are located around the middle between two adjacent substations. Finally, the examples of the practical design of the supercapacitors modules have been presented by using commercially available modules.

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