Optimization of a Mobile Energy Storage Network

Luiz Eduardo Cotta Monteiro, Hugo Miguel Varela Repolho, Rodrigo Flora Calili, Daniel Ramos Louzada, Rafael Saadi Dantas Teixeira and Rodrigo Santos Vieira
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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

Energies, 2021, vol. 15, issue 1, 1-23

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.

Keywords: optimization model; lithium-ion batteries; powerbank network; state of charge; destructive tests (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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