LAPSE:2023.17036
Published Article

LAPSE:2023.17036
The SOC Based Dynamic Charging Coordination of EVs in the PV-Penetrated Distribution Network Using Real-World Data
March 6, 2023
Abstract
A successful distribution network can continue to operate despite the uncertainties at the charging station, with appropriate equipment retrofits and upgrades. However, these new investments in the grid can become complex in terms of time and space. In this paper, we propose a dynamic charge coordination (DCC) method based on the battery state of charge (SOC) of electric vehicles (EVs) in line with this purpose. The collective uncoordinated charging profiles of EVs charged at maximum power were investigated based on statistical data for distances of EVs and a real dataset for charging characteristics in the existing grid infrastructure. The proposed strategy was investigated using the modified Roy Billinton Test System (RBTS) performed by DIgSILENT Powerfactory simulation software for a total 50 EVs in 30 different models. Then, the load balancing situations were analyzed with the integration of the photovoltaic (PV) generation and battery energy storage system (BESS) into the bus bars where the EVs were fed into the grid. According to the simulation results, the proposed method dramatically reduces the effects on the grid compared to the uncoordinated charging method. Furthermore, the integration of PV and BESS system, load balancing for EVs was successfully achieved with the proposed approach.
A successful distribution network can continue to operate despite the uncertainties at the charging station, with appropriate equipment retrofits and upgrades. However, these new investments in the grid can become complex in terms of time and space. In this paper, we propose a dynamic charge coordination (DCC) method based on the battery state of charge (SOC) of electric vehicles (EVs) in line with this purpose. The collective uncoordinated charging profiles of EVs charged at maximum power were investigated based on statistical data for distances of EVs and a real dataset for charging characteristics in the existing grid infrastructure. The proposed strategy was investigated using the modified Roy Billinton Test System (RBTS) performed by DIgSILENT Powerfactory simulation software for a total 50 EVs in 30 different models. Then, the load balancing situations were analyzed with the integration of the photovoltaic (PV) generation and battery energy storage system (BESS) into the bus bars where the EVs were fed into the grid. According to the simulation results, the proposed method dramatically reduces the effects on the grid compared to the uncoordinated charging method. Furthermore, the integration of PV and BESS system, load balancing for EVs was successfully achieved with the proposed approach.
Record ID
Keywords
dynamic charge coordination, electrical vehicles, load balancing, peak loading, wave-form charging
Subject
Suggested Citation
Akil M, Dokur E, Bayindir R. The SOC Based Dynamic Charging Coordination of EVs in the PV-Penetrated Distribution Network Using Real-World Data. (2023). LAPSE:2023.17036
Author Affiliations
Akil M: Department of Electronics and Automation, Aksaray Technical Science Vocational School, Aksaray University, Aksaray 68100, Turkey [ORCID]
Dokur E: Department of Electrical-Electronics Engineering, Engineering Faculty, Bilecik Seyh Edebali University, Bilecik 11200, Turkey; Marine and Renewable Energy Center, University of College Cork, P43 C573 Cork, Ireland [ORCID]
Bayindir R: Department of Electrical-Electronics Engineering, Technology Faculty, Gazi University, Ankara 06500, Turkey [ORCID]
Dokur E: Department of Electrical-Electronics Engineering, Engineering Faculty, Bilecik Seyh Edebali University, Bilecik 11200, Turkey; Marine and Renewable Energy Center, University of College Cork, P43 C573 Cork, Ireland [ORCID]
Bayindir R: Department of Electrical-Electronics Engineering, Technology Faculty, Gazi University, Ankara 06500, Turkey [ORCID]
Journal Name
Energies
Volume
14
Issue
24
First Page
8508
Year
2021
Publication Date
2021-12-17
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14248508, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.17036
This Record
External Link

https://doi.org/10.3390/en14248508
Publisher Version
Download
Meta
Record Statistics
Record Views
198
Version History
[v1] (Original Submission)
Mar 6, 2023
Verified by curator on
Mar 6, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.17036
Record Owner
Auto Uploader for LAPSE
Links to Related Works
(0.43 seconds)
