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Optimization of a Mobile Energy Storage Network

Author

Listed:
  • Luiz Eduardo Cotta Monteiro

    (Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro, Rio de Janeir 22451-900, Brazil)

  • Hugo Miguel Varela Repolho

    (Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro, Rio de Janeir 22451-900, Brazil)

  • Rodrigo Flora Calili

    (Post Graduate Program in Metrology, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro 22451-900, Brazil)

  • Daniel Ramos Louzada

    (Post Graduate Program in Metrology, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro 22451-900, Brazil)

  • Rafael Saadi Dantas Teixeira

    (Post Graduate Program in Metrology, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro 22451-900, Brazil)

  • Rodrigo Santos Vieira

    (Post Graduate Program in Metrology, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro 22451-900, Brazil)

Abstract

This paper introduces the mobile battery network for electronic devices through powerbanks in a city, and proposes an optimization model to find the optimum site and set-up of the network considering costumers demand, logistics components, the batteries degradation, and terminal’s charger regime. To this end, a series of degradation tests were carried out on lithium-ion batteries, in four different charger regimes, in which the battery voltage amplitude and the charging electric current were varied. The results of these tests were incorporated into the optimization model as the depreciation rate and charge time over battery life. The mathematical modeling innovates by including new components designed specifically for this new problem: battery availability according to charging time; different types of customer service; objective function modeling that includes the logistical costs of battery relocation, terminal maintenance, and battery depreciation. The results indicate that the network performance using batteries in the fastest charging configuration tends to have a positive impact on their efficiency and profitability. The model can be used as a reference for other applications that require recharge points that enable the use of mobile batteries, such as electric scooters, electric bicycles, and drones, among others.

Suggested Citation

  • Luiz Eduardo Cotta Monteiro & Hugo Miguel Varela Repolho & Rodrigo Flora Calili & Daniel Ramos Louzada & Rafael Saadi Dantas Teixeira & Rodrigo Santos Vieira, 2021. "Optimization of a Mobile Energy Storage Network," Energies, MDPI, vol. 15(1), pages 1-23, December.
    • Handle: RePEc:gam:jeners:v:15:y:2021:i:1:p:186-:d:712924
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    References listed on IDEAS

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    1. Yang, Jun & Guo, Fang & Zhang, Min, 2017. "Optimal planning of swapping/charging station network with customer satisfaction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 174-197.
    2. Ho-Yin Mak & Ying Rong & Zuo-Jun Max Shen, 2013. "Infrastructure Planning for Electric Vehicles with Battery Swapping," Management Science, INFORMS, vol. 59(7), pages 1557-1575, July.
    3. Frade, Ines & Ribeiro, Anabela, 2015. "Bike-sharing stations: A maximal covering location approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 216-227.
    4. Maximilian Schiffer & Grit Walther, 2018. "An Adaptive Large Neighborhood Search for the Location-routing Problem with Intra-route Facilities," Transportation Science, INFORMS, vol. 52(2), pages 331-352, March.
    5. Peter Lacy & Jakob Rutqvist, 2015. "The Product as a Service Business Model: Performance over Ownership," Palgrave Macmillan Books, in: Waste to Wealth, chapter 0, pages 99-114, Palgrave Macmillan.
    6. Nie, Yu (Marco) & Ghamami, Mehrnaz, 2013. "A corridor-centric approach to planning electric vehicle charging infrastructure," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 172-190.
    Full references (including those not matched with items on IDEAS)

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