Estimating the charging profile of individual charge sessions of electric vehicles in the Netherlands
The mass adoption of Electric Vehicles (EVs) might raise pressure on the power system, especially during peak hours. Therefore, there is a need for delayed charging. However, to optimize the charging system, the progression of charging from an empty battery until a full battery of the EVs based on realworld data needs to be analyzed. Many researchers currently view this charging profile as a static load and ignore the actual charging behavior during the charging session. This study investigates how different factors influence the charging profile of individual EVs based on real-world data of c... Mehr ...
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| Dokumenttyp: | conferenceObject |
| Erscheinungsdatum: | 2017 |
| Schlagwörter: | Charging Infrastructure / charging profile / Electric Vehicles / smart charging / battery charging load |
| Sprache: | Englisch |
| Permalink: | https://search.fid-benelux.de/Record/base-26807893 |
| Datenquelle: | BASE; Originalkatalog |
| Powered By: | BASE |
| Link(s) : | https://research.hva.nl/en/publications/def16713-7fd1-457e-a4b6-326f6397e686 |
The mass adoption of Electric Vehicles (EVs) might raise pressure on the power system, especially during peak hours. Therefore, there is a need for delayed charging. However, to optimize the charging system, the progression of charging from an empty battery until a full battery of the EVs based on realworld data needs to be analyzed. Many researchers currently view this charging profile as a static load and ignore the actual charging behavior during the charging session. This study investigates how different factors influence the charging profile of individual EVs based on real-world data of charging sessions in the Netherlands, enabling optimization analysis of EV smart charging schemes.