Fletcher, D.I. orcid.org/0000-0002-1562-4655, Harrison, R.F. and Nallaperuma, S. (2020) TransEnergy - a tool for energy storage optimization, peak power and energy consumption reduction in DC electric railway systems. Journal of Energy Storage, 30. 101425. ISSN 2352-152X
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/). |
Keywords: | Rail traction electricity; Energy Storage; DC power; optimization |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Science Research Council EP/N022289/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Apr 2020 10:45 |
Last Modified: | 18 May 2020 12:52 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.est.2020.101425 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:159168 |