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Comparison of dynamic models for a DC railway electrical network including an AC/DC bi-directional power station

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  • Almaksour, Khaled
  • Krim, Youssef
  • Kouassi, N’guessan
  • Navarro, Nicolas
  • François, Bruno
  • Letrouvé, Tony
  • Saudemont, Christophe
  • Taunay, Lionel
  • Robyns, Benoit

Abstract

To face environmental issues, SNCF, the French railway, has chosen to improve the energy efficiency of its electrical power system by investigating solutions for regenerative braking. With the contribution of Railenium, a research and test center in railway activities, they aim to recover the braking energy by setting up a reversible inverter in the DC substation ”Masséna”. The issue is to test, implement and compare various control solutions to increase the energy efficiency with minimum impacts on the railway operation. In this paper, a simulation model for studying a reversible power substation is addressed by considering AC and DC equivalent electrical sources. The proposed model provides a reliable tool for analyzing the behavior of the railway electrical network during specially braking mode. In order to validate this model, its simulation results are compared with the ones obtained from Esmeralda, the SNCF professional software. A first configuration is led without the inverter and gives certified Esmeralda results and validates the proposed model despite some gaps in powers and voltages due to differences in input data and models. A second comparison with inverter is presented to highlight the main difference between the proposed model and Esmeralda. In addition, laboratory experimental activities are put forward to investigate the proposed model by using power-hardware-in-the-loop simulations. Finally, a simulation test under MATLAB software with fifty train’s traffic is presented to estimate the energy saving thanks to the installed inverter. For this latter case study, the system sent back to the national AC grid around 6.9% of the total energy consumed by all trains.

Suggested Citation

  • Almaksour, Khaled & Krim, Youssef & Kouassi, N’guessan & Navarro, Nicolas & François, Bruno & Letrouvé, Tony & Saudemont, Christophe & Taunay, Lionel & Robyns, Benoit, 2021. "Comparison of dynamic models for a DC railway electrical network including an AC/DC bi-directional power station," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 184(C), pages 244-266.
    • Handle: RePEc:eee:matcom:v:184:y:2021:i:c:p:244-266
    DOI: 10.1016/j.matcom.2020.05.027
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    References listed on IDEAS

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    1. Pablo Arboleya & Islam El-Sayed & Bassam Mohamed & Clement Mayet, 2019. "Modeling, Simulationand Analysis of On-Board Hybrid Energy Storage Systems for Railway Applications," Energies, MDPI, vol. 12(11), pages 1-21, June.
    2. Yuan, Weichang & Frey, H. Christopher, 2020. "Potential for metro rail energy savings and emissions reduction via eco-driving," Applied Energy, Elsevier, vol. 268(C).
    3. Pankovits, Petronela & Abbes, Dhaker & Saudemont, Christophe & Brisset, Stephane & Pouget, Julien & Robyns, Benoit, 2016. "Multi-criteria fuzzy-logic optimized supervision for hybrid railway power substations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 130(C), pages 236-250.
    4. Yang, Songpo & Liao, Feixiong & Wu, Jianjun & Timmermans, Harry J.P. & Sun, Huijun & Gao, Ziyou, 2020. "A bi-objective timetable optimization model incorporating energy allocation and passenger assignment in an energy-regenerative metro system," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 85-113.
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