How do external factors influence the charging profiles of Electric Vehicles?
How do external factors influence the charging profiles of EVs? A research team from AUAS, UvA and ElaadNL, have estimated the charging profile of individual charge sessions of electric vehicles in The Netherlands.
Find the paper HERE
Read more on Clean Technica HERE
Over recent years, numbers of electric vehicles (EVs) have shown a strong growth and sales are projected to continue to grow. For facilitating charging possibilities for EVs typically two rollout strategies have been applied; demand-driven and strategic rollout. This study focuses on determining the differences in performance metrics of the two rollout strategies by first defining key performance metrics. Thereafter, the root causes of performance differences between the two rollout strategies are investigated. This study analyzes charging data of 1,007,137 transactions on 1742 different CPs by use of 53,850 unique charging cards. This research concludes that demand-driven CPs outperform strategic CPs on weekly energy transfer and connection duration, while strategic CPs outperform their demand-driven counterparts on charging time ratio. Regarding users facilitated, there is a significant change in performance after massive EV-uptake. The root cause analysis shows effects of EV uptake and user type composition on the differences in performance metrics. This research concludes with implications for policy makers regarding an optimal portfolio of rollout strategies.
The ADS Thesis Awards aim to promote excellence in Data Science and AI from students at BSc and Master level. The Awards are open to students from all Amsterdam-based knowledge institutes.
On the 22nd of September LAB42 will host its Grand Opening from 15:00 onwards. LAB42 is an international hub for developing talent in the fields of digital innovation and AI. The building is the result of a partnership between the UvA, the municipality of Amsterdam and the business sector.
The UvA Data Science Centre, part of the University Library, is pleased to host its second yearly Data Science Day on the 13th of October 2022.