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A Dual-Stage Modeling and Optimization Framework for Wayside Energy Storage in Electric Rail Transit Systems

Author

Listed:
  • Oindrilla Dutta

    (Department of Electrical Engineering, The City University of New York, City College, 160 Convent Avenue, New York, NY 10031, USA)

  • Mahmoud Saleh

    (Department of Electrical Engineering, The City University of New York, City College, 160 Convent Avenue, New York, NY 10031, USA)

  • Mahdiyeh Khodaparastan

    (Department of Electrical Engineering, The City University of New York, City College, 160 Convent Avenue, New York, NY 10031, USA)

  • Ahmed Mohamed

    (Department of Electrical Engineering, The City University of New York, City College, 160 Convent Avenue, New York, NY 10031, USA
    Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia 61512, Egypt)

Abstract

In this paper, a dual-stage modeling and optimization framework has been developed to obtain an optimal combination and size of wayside energy storage systems (WESSs) for application in DC rail transportation. Energy storage technologies may consist of a standalone battery, a standalone supercapacitor, a standalone flywheel, or a combination of these. Results from the dual-stage modeling and optimization process have been utilized for deducing an application-specific composition of type and size of the WESSs. These applications consist of different percentages of energy saving due to regenerative braking, voltage regulation, peak demand reduction, estimated payback period, and system resiliency. In the first stage, sizes of the ESSs have been estimated using developed detailed mathematical models, and optimized using the Genetic Algorithm (GA). In the second stage, the respective sizes of ESSs are simulated by developing an all-inclusive model of the transit system, ESS and ESS management system (EMS) in MATLAB/Simulink. The mathematical modeling provides initial recommendations for the sizes from a large search space. However, the dynamic simulation contributes to the optimization by highlighting the transit system constraints and practical limitations of ESSs, which impose bounds on the maximum energy that can be captured from decelerating trains.

Suggested Citation

  • Oindrilla Dutta & Mahmoud Saleh & Mahdiyeh Khodaparastan & Ahmed Mohamed, 2020. "A Dual-Stage Modeling and Optimization Framework for Wayside Energy Storage in Electric Rail Transit Systems," Energies, MDPI, vol. 13(7), pages 1-26, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1614-:d:340205
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    References listed on IDEAS

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    1. Ng, Kong Soon & Moo, Chin-Sien & Chen, Yi-Ping & Hsieh, Yao-Ching, 2009. "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries," Applied Energy, Elsevier, vol. 86(9), pages 1506-1511, September.
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    Cited by:

    1. Meishner, Fabian & Ünlübayir, Cem & Sauer, Dirk Uwe, 2023. "Model-based investigation of an uncontrolled LTO wayside energy storage system in a 750 V tram grid," Applied Energy, Elsevier, vol. 331(C).
    2. Gustavo Navarro & Jorge Torres & Marcos Blanco & Jorge Nájera & Miguel Santos-Herran & Marcos Lafoz, 2021. "Present and Future of Supercapacitor Technology Applied to Powertrains, Renewable Generation and Grid Connection Applications," Energies, MDPI, vol. 14(11), pages 1-29, May.

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