Electric Vehicles Charging Algorithm with Peak Power Minimization, EVs Charging Power Minimization, Ability to Respond to DR Signals and V2G Functionality

Grzegorz Benysek, Bartosz Waśkowicz, Robert Dylewski and Marcin Jarnut
Additional contact information
Grzegorz Benysek: Ekoenergetyka Polska S.A., ul. Nowy-Kisielin-Wysockiego 8, 66-002 Zielona Góra, Poland
Bartosz Waśkowicz: Ekoenergetyka Polska S.A., ul. Nowy-Kisielin-Wysockiego 8, 66-002 Zielona Góra, Poland
Marcin Jarnut: Ekoenergetyka Polska S.A., ul. Nowy-Kisielin-Wysockiego 8, 66-002 Zielona Góra, Poland

Energies, 2022, vol. 15, issue 14, 1-16

Abstract: The number of electric vehicles (EV) on the roads, as well as the share of EVs in use, will inevitably increase in coming decades. This creates a number of problems. A large EV fleet is a significant additional load in the power system that is impossible to accurately predict. Another related problem is the limited distribution network capacity, which is not ready for the additional load from the widespread EV infrastructure. There is a need for an EV charging coordination algorithm capable of fulfilling the charging EV needs, while using as low demanded power as possible and using the lowest power values in each EV charging profile. We propose an EV coordinating algorithm that is capable of ensuring that all connected EVs in the considered parking lot will be charged at the user-defined departure time. The algorithm also controls the charging/discharging power of every connected EV in such a way that the parking lot as a whole will use minimal possible peak power while minimizing the charging power of every EV. The proposed algorithm is also capable of responding to demand response (DR) signals. The paper also includes the results of simulation with a statistical summary of the proposed algorithm effectiveness.

Keywords: electric vehicles; demand response signal; EV charging coordination; peak power minimization; charging power minimization; vehicle-to-grid functionality (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/14/5195/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/14/5195/ (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:15:y:2022:i:14:p:5195-:d:865154

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 ().