Quality of service and fairness for electric vehicle charging as a service
Abstract Due to the increasing battery capacity of electric vehicles, European standard electricity socket-outlets at households are not enough for a full charge cycle overnight. Hence, people tend to install (semi-) fast charging wall-boxes (up to 22 kW) which can cause critical peak loads and volt...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-09-01
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| Series: | Energy Informatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42162-021-00175-3 |
| _version_ | 1818915284694597632 |
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| author | Dominik Danner Hermann de Meer |
| author_facet | Dominik Danner Hermann de Meer |
| author_sort | Dominik Danner |
| collection | DOAJ |
| description | Abstract Due to the increasing battery capacity of electric vehicles, European standard electricity socket-outlets at households are not enough for a full charge cycle overnight. Hence, people tend to install (semi-) fast charging wall-boxes (up to 22 kW) which can cause critical peak loads and voltage issues whenever many electric vehicles charge simultaneously in the same area.This paper proposes a centralized charging capacity allocation mechanism based on queuing systems that takes care of grid limitations and charging requirements of electric vehicles, including legacy charging control protocol restrictions. The proposed allocation mechanism dynamically updates the weights of the charging services in discrete time steps, such that electric vehicles with shorter remaining charging time and higher energy requirement are preferred against others. Furthermore, a set of metrics that determine the service quality for charging as a service is introduced. Among others, these metrics cover the ratio of charged energy to the required energy, the charging power variation during the charging process, as well as whether the upcoming trip is feasible or not. The proposed algorithm outperforms simpler scheduling policies in terms of achieved mean quality of service metric and fairness index in a co-simulation of the IEEE European low voltage grid configured with charging service requirements extracted from a mobility survey. |
| first_indexed | 2024-12-19T23:59:50Z |
| format | Article |
| id | doaj.art-7b7af31e17654b8197cc599e7111fbf2 |
| institution | Directory Open Access Journal |
| issn | 2520-8942 |
| language | English |
| last_indexed | 2024-12-19T23:59:50Z |
| publishDate | 2021-09-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Energy Informatics |
| spelling | doaj.art-7b7af31e17654b8197cc599e7111fbf22022-12-21T20:00:52ZengSpringerOpenEnergy Informatics2520-89422021-09-014S312010.1186/s42162-021-00175-3Quality of service and fairness for electric vehicle charging as a serviceDominik Danner0Hermann de Meer1University of PassauUniversity of PassauAbstract Due to the increasing battery capacity of electric vehicles, European standard electricity socket-outlets at households are not enough for a full charge cycle overnight. Hence, people tend to install (semi-) fast charging wall-boxes (up to 22 kW) which can cause critical peak loads and voltage issues whenever many electric vehicles charge simultaneously in the same area.This paper proposes a centralized charging capacity allocation mechanism based on queuing systems that takes care of grid limitations and charging requirements of electric vehicles, including legacy charging control protocol restrictions. The proposed allocation mechanism dynamically updates the weights of the charging services in discrete time steps, such that electric vehicles with shorter remaining charging time and higher energy requirement are preferred against others. Furthermore, a set of metrics that determine the service quality for charging as a service is introduced. Among others, these metrics cover the ratio of charged energy to the required energy, the charging power variation during the charging process, as well as whether the upcoming trip is feasible or not. The proposed algorithm outperforms simpler scheduling policies in terms of achieved mean quality of service metric and fairness index in a co-simulation of the IEEE European low voltage grid configured with charging service requirements extracted from a mobility survey.https://doi.org/10.1186/s42162-021-00175-3Dynamically weighted fair queuingElectric vehicle chargingSmart gridFair charging service allocationQueuing modelQuality of service |
| spellingShingle | Dominik Danner Hermann de Meer Quality of service and fairness for electric vehicle charging as a service Energy Informatics Dynamically weighted fair queuing Electric vehicle charging Smart grid Fair charging service allocation Queuing model Quality of service |
| title | Quality of service and fairness for electric vehicle charging as a service |
| title_full | Quality of service and fairness for electric vehicle charging as a service |
| title_fullStr | Quality of service and fairness for electric vehicle charging as a service |
| title_full_unstemmed | Quality of service and fairness for electric vehicle charging as a service |
| title_short | Quality of service and fairness for electric vehicle charging as a service |
| title_sort | quality of service and fairness for electric vehicle charging as a service |
| topic | Dynamically weighted fair queuing Electric vehicle charging Smart grid Fair charging service allocation Queuing model Quality of service |
| url | https://doi.org/10.1186/s42162-021-00175-3 |
| work_keys_str_mv | AT dominikdanner qualityofserviceandfairnessforelectricvehiclechargingasaservice AT hermanndemeer qualityofserviceandfairnessforelectricvehiclechargingasaservice |