Uncoordinated charging profile of EVs based on an actual charging session data
| dc.contributor.author | Akıl, Murat | |
| dc.contributor.author | Kılıç, Ensar | |
| dc.contributor.author | Bayındır, Ramazan | |
| dc.date.accessioned | 2022-02-17T06:04:55Z | |
| dc.date.available | 2022-02-17T06:04:55Z | |
| dc.date.issued | 2021 | |
| dc.department | Teknik Bilimler Meslek Yüksekokulu | |
| dc.description.abstract | The energy profile of gathered EVs is difficult to determine, as the actual charging data of Electric Vehicles (EVs) cannot be shared among distribution service providers. In this study, a dataset containing weekday and weekend information over a one-day period based on actual EV charging sessions in the Perth and Kinross region is used. This dataset contains the start and end times of EVs charging. Based on these data, a total of 5000 vehicle session data were derived for Monte Carlo Simulation (MCS) at 15-minute intervals. According to the data obtained, uncoordinated (without power reduction, restriction and timing) AC charge load profiles of bulk EVs with 50kWh battery capacity and maximum power up to 22kW in accordance with IEC 61851-1 standards were generated. Accordingly, peak loading and peak loading times of 5000 EVs in the distribution line in case of uncoordinated charging for Perth and Kinross regions were evaluated for weekdays and weekends. The results found provided information on EV load peak times for distribution service providers in the city of Perth, both weekdays and weekends. | |
| dc.description.abstract | Honda R and D Co., Ltd.Power Electronics in Everything (PEiE)TMEiC | |
| dc.identifier.endpage | 462 | en_US |
| dc.identifier.issue | - | en_US |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 459 | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12451/9190 | |
| dc.identifier.volume | - | en_US |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.ispartof | 10th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2021 | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Actual Charging Sessions | |
| dc.subject | Monte Carlo Simulation | |
| dc.subject | Peak Loading | |
| dc.subject | Uncoordinated EV Charging | |
| dc.title | Uncoordinated charging profile of EVs based on an actual charging session data | |
| dc.type | Conference Object |
