Optimized Strategy for Energy Management in an EV Fast Charging Microgrid Considering Storage Degradation

Joelson Lopes da Paixão (), Alzenira da Rosa Abaide, Gabriel Henrique Danielsson, Jordan Passinato Sausen, Leonardo Nogueira Fontoura da Silva and Nelson Knak Neto
Additional contact information
Joelson Lopes da Paixão: Graduate Program in Electrical Engineering, Federal University of Santa Maria—UFSM, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Alzenira da Rosa Abaide: Graduate Program in Electrical Engineering, Federal University of Santa Maria—UFSM, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Gabriel Henrique Danielsson: Graduate Program in Electrical Engineering, Federal University of Santa Maria—UFSM, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Jordan Passinato Sausen: Graduate Program in Electrical Engineering, Federal University of Santa Maria—UFSM, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Leonardo Nogueira Fontoura da Silva: Graduate Program in Electrical Engineering, Federal University of Santa Maria—UFSM, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Nelson Knak Neto: Graduate Program in Electrical Engineering, Federal University of Santa Maria—UFSM, Santa Maria 97105-900, Rio Grande do Sul, Brazil

Energies, 2025, vol. 18, issue 5, 1-34

Abstract: Current environmental challenges demand immediate action, especially in the transport sector, which is one of the largest CO 2 emitters. Vehicle electrification is considered an essential strategy for emission mitigation and combating global warming. This study presents methodologies for the modeling and energy management of microgrids (MGs) designed as charging stations for electric vehicles (EVs). Algorithms were developed to estimate daily energy generation and charging events in the MG. These data feed an energy management algorithm aimed at minimizing the costs associated with energy trading operations, as well as the charging and discharging cycles of the battery energy storage system (BESS). The problem constraints ensure the safe operation of the system, availability of backup energy for off-grid conditions, preference for reduced tariffs, and optimized management of the BESS charge and discharge rates, considering battery wear. The grid-connected MG used in our case study consists of a wind turbine (WT), photovoltaic system (PVS), BESS, and an electric vehicle fast charging station (EVFCS). Located on a highway, the MG was designed to provide fast charging, extending the range of EVs and reducing drivers’ range anxiety. The results of this study demonstrated the effectiveness of the proposed energy management approach, with the optimization algorithm efficiently managing energy flows within the MG while prioritizing lower operational costs. The inclusion of the battery wear model makes the optimizer more selective in terms of battery usage, operating it in cycles that minimize BESS wear and effectively prolong its lifespan.

Keywords: EV microgrid; EV fast charging in highway; energy dispatch in MG; energy management optimization; energetic transition; operational cost minimization (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: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/5/1060/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/5/1060/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:5:p:1060-:d:1596892

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().