Development of energy storage system for storing regenerative braking energy from train
This research aims to explore the development of energy storage systems in railway projects. Investigate the characteristics of energy generated and/or energy used by the electric train, design an energy storage system to recover the energy from the energy used and evaluate the performance of the sy...
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Format: | Final Year Project / Dissertation / Thesis |
Published: |
2022
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Online Access: | http://eprints.utar.edu.my/4996/1/Faizal_Zamani_Dollah.pdf http://eprints.utar.edu.my/4996/ |
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Summary: | This research aims to explore the development of energy storage systems in railway projects. Investigate the characteristics of energy generated and/or energy used by the electric train, design an energy storage system to recover the energy from the energy used and evaluate the performance of the system developed.Recent research in railways and studies in newspapers and conference papers have highlighted the importance of different technology and operative strategies to optimise the railway system's efficiency, but due to a broad range of interdependent factors, more dedicated studies are required to tackle energy costs and the need for optimised and reliable strategies. Energy from a moving train from static stop to movement has produced significantly excessive energy which can be harvested and reused for train operations or used by the local system, e.g., traction substations, stations, convenience stores and residential townships. In certain scenarios, the non-regenerative braking will be considered since the worst-case scenario is in the design parameter.In this study, and the train operating data are collected to ascertain the current perceptions of energy conservation to railway applications. The information is then used as the parameters for modeling the Mass Rapid Transit System. ETrax software is used for dynamic load flow simulations to obtain an accurate estimation of the energy recovery captured in the system in each operation mode by incorporating train headway interval variations, algorithm and the effects of train schedules on the operating mode. |
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