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Optimal Location and Sizing of Energy Storage Systems in DC-Electrified Railway Lines Using a Coral Reefs Optimization Algorithm with Substrate Layers

Author

Listed:
  • David Roch-Dupré

    (Faculty of Economics and Business Administration, Institute for Research in Technology, Comillas Pontifical University, 28049 Madrid, Spain)

  • Carlos Camacho-Gómez

    (Department of Computer Systems, Universidad Politécnica de Madrid, 28031 Madrid, Spain)

  • Asunción P. Cucala

    (Institute for Research in Technology, Comillas Pontifical University, 28049 Madrid, Spain)

  • Silvia Jiménez-Fernández

    (Department of Signal Processing and Communications, Universidad de Alcalá, 28805 Alcalá de Henares, Spain)

  • Álvaro López-López

    (Institute for Research in Technology, Comillas Pontifical University, 28049 Madrid, Spain)

  • Antonio Portilla-Figueras

    (Department of Signal Processing and Communications, Universidad de Alcalá, 28805 Alcalá de Henares, Spain)

  • Ramón R. Pecharromán

    (Institute for Research in Technology, Comillas Pontifical University, 28049 Madrid, Spain)

  • Antonio Fernández-Cardador

    (Institute for Research in Technology, Comillas Pontifical University, 28049 Madrid, Spain)

  • Sancho Salcedo-Sanz

    (Department of Signal Processing and Communications, Universidad de Alcalá, 28805 Alcalá de Henares, Spain)

Abstract

This paper deals with the problem of finding the optimal location and sizing of Energy Storage Systems in DC-electrified railway lines. These devices increment the use of the regenerated energy produced by the trains in the braking phases, as they store the energy to later provide to the catenary the excess of regenerated energy, that otherwise would be lost in the rheostats. However, these infrastructures require a high initial investment that, in some cases, may question their profitability. We propose a multi-method ensemble meta-heuristic to obtain the optimal solution to the problem, with a high level of accuracy. Specifically, the Coral Reefs Optimization with Substrate Layers (CRO-SL) is proposed, an evolutionary-type approach able to run different search procedures within the same population. We will evaluate the performance of the CRO-SL in the problem, and we will show that it performs better than the best known existing meta-heuristics for this problem.

Suggested Citation

  • David Roch-Dupré & Carlos Camacho-Gómez & Asunción P. Cucala & Silvia Jiménez-Fernández & Álvaro López-López & Antonio Portilla-Figueras & Ramón R. Pecharromán & Antonio Fernández-Cardador & Sancho Sa, 2021. "Optimal Location and Sizing of Energy Storage Systems in DC-Electrified Railway Lines Using a Coral Reefs Optimization Algorithm with Substrate Layers," Energies, MDPI, vol. 14(16), pages 1-19, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4753-:d:608656
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    References listed on IDEAS

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    1. Bin Wang & Zhongping Yang & Fei Lin & Wei Zhao, 2014. "An Improved Genetic Algorithm for Optimal Stationary Energy Storage System Locating and Sizing," Energies, MDPI, vol. 7(10), pages 1-25, October.
    2. Huan Xia & Huaixin Chen & Zhongping Yang & Fei Lin & Bin Wang, 2015. "Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm," Energies, MDPI, vol. 8(10), pages 1-23, October.
    3. Pellerin, Robert & Perrier, Nathalie & Berthaut, François, 2020. "A survey of hybrid metaheuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 280(2), pages 395-416.
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    Cited by:

    1. Mihaela Popescu, 2022. "Energy Efficiency in Electric Transportation Systems," Energies, MDPI, vol. 15(21), pages 1-5, November.

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