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A novel modular designing for multi-ring flywheel rotor to optimize energy consumption in light metro trains

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  • Rastegarzadeh, Sina
  • Mahzoon, Mojtaba
  • Mohammadi, Hossein

Abstract

In this paper, a multi-ring flywheel rotor is chosen as a basic module for modular designing an optimized energy storage system to reduce the energy consumption in light metro trains by finding the best capacity and the number of optimized-flywheel rotor module for each train car. After finding the adequate capacity and optimizing the geometric characteristics of rotor rings, the effect of using the modular Flywheel energy storage system (FESS) on reducing the energy consumption of light urban trains is investigated. Four different rotors with various energy storage capacities are chosen, so that results can be used for a wide range of light trains with a power demand range of 1620–3420 kW. In the optimization algorithm, the energy per unit volume is considered as the cost function. The presented general modular designing is examined for Shiraz urban train system by using real-time speed and acceleration data. A three-layer flywheel with an energy storage capacity of 500W.h serves as a practical example. Finally, the effects of the number of passengers, peak, and off-peak hours in the energy storage capacity of the system are also studied. Using 15-FESS modules results in 35.1% energy saving for this line.

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  • Rastegarzadeh, Sina & Mahzoon, Mojtaba & Mohammadi, Hossein, 2020. "A novel modular designing for multi-ring flywheel rotor to optimize energy consumption in light metro trains," Energy, Elsevier, vol. 206(C).
    • Handle: RePEc:eee:energy:v:206:y:2020:i:c:s0360544220311993
    DOI: 10.1016/j.energy.2020.118092
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    1. Kuriqi, Alban & Pinheiro, António N. & Sordo-Ward, Alvaro & Garrote, Luis, 2019. "Flow regime aspects in determining environmental flows and maximising energy production at run-of-river hydropower plants," Applied Energy, Elsevier, vol. 256(C).
    2. Barelli, L. & Bidini, G. & Bonucci, F. & Castellini, L. & Fratini, A. & Gallorini, F. & Zuccari, A., 2019. "Flywheel hybridization to improve battery life in energy storage systems coupled to RES plants," Energy, Elsevier, vol. 173(C), pages 937-950.
    3. Suzuki, Y. & Koyanagi, A. & Kobayashi, M. & Shimada, R., 2005. "Novel applications of the flywheel energy storage system," Energy, Elsevier, vol. 30(11), pages 2128-2143.
    4. Spiryagin, Maksym & Wolfs, Peter & Szanto, Frank & Sun, Yan Quan & Cole, Colin & Nielsen, Dwayne, 2015. "Application of flywheel energy storage for heavy haul locomotives," Applied Energy, Elsevier, vol. 157(C), pages 607-618.
    5. Pan, Deng & Zhao, Liting & Luo, Qing & Zhang, Chuansheng & Chen, Zejun, 2018. "Study on the performance improvement of urban rail transit system," Energy, Elsevier, vol. 161(C), pages 1154-1171.
    6. Rupp, A. & Baier, H. & Mertiny, P. & Secanell, M., 2016. "Analysis of a flywheel energy storage system for light rail transit," Energy, Elsevier, vol. 107(C), pages 625-638.
    7. Stern, Martin O., 1988. "Energy storage in magnetic fields," Energy, Elsevier, vol. 13(2), pages 137-140.
    8. Zhao, Pan & Dai, Yiping & Wang, Jiangfeng, 2014. "Design and thermodynamic analysis of a hybrid energy storage system based on A-CAES (adiabatic compressed air energy storage) and FESS (flywheel energy storage system) for wind power application," Energy, Elsevier, vol. 70(C), pages 674-684.
    9. Bolund, Björn & Bernhoff, Hans & Leijon, Mats, 2007. "Flywheel energy and power storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(2), pages 235-258, February.
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    Cited by:

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    2. Abdulilah Mohammad Mayet & Seyed Mehdi Alizadeh & Karina Shamilyevna Nurgalieva & Robert Hanus & Ehsan Nazemi & Igor M. Narozhnyy, 2022. "Extraction of Time-Domain Characteristics and Selection of Effective Features Using Correlation Analysis to Increase the Accuracy of Petroleum Fluid Monitoring Systems," Energies, MDPI, vol. 15(6), pages 1-19, March.
    3. Cipek, Mihael & Pavković, Danijel & Krznar, Matija & Kljaić, Zdenko & Mlinarić, Tomislav Josip, 2021. "Comparative analysis of conventional diesel-electric and hypothetical battery-electric heavy haul locomotive operation in terms of fuel savings and emissions reduction potentials," Energy, Elsevier, vol. 232(C).
    4. Abdul Ghani Olabi & Tabbi Wilberforce & Mohammad Ali Abdelkareem & Mohamad Ramadan, 2021. "Critical Review of Flywheel Energy Storage System," Energies, MDPI, vol. 14(8), pages 1-33, April.

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