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Modelling Charging Infrastructure in V2G Scenario Universita degli Studi di Firenze

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Innocenti, Eleonora, author.
Contributor:
Berzi, Lorenzo
Delogu, Massimo
Kociu, Aljon
Conference Name:
CO2 Reduction for Transportation Systems Conference (2024-06-12 : Turin, Italy)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2024
Summary:
Nowadays, electrification is largely acknowledged as a crucial strategy to mitigate climate change, especially for the transportation sector through the transition from conventional vehicles to electric vehicles (EVs). As the demand for EVs continues to rise, the development of a robust and widespread charging infrastructure has become a top priority for governments and decision-makers. In this context, innovative approaches to energy management and sustainability, such as Vehicle-to-Grid (V2G), are gradually being employed, leading to new challenges, like grid service integration, charge scheduling and public acceptance. For instance, the planned use scenario, the user's behavior, and the reachability of the geographical position influence the optimal energy management strategies both maintain user satisfaction and optimize grid impact. Firstly, this paper not only presents an extensive classification of charging infrastructure and possible planning activities related to different charging scenarios but also indicates the most feasible Point of Interest (POIs) for certain energy strategies and a user's behavior associated with POIs. Secondly, the article proposes a systematic procedure to analyze the potential location using accessible data from OpenStreetMap (OSM), considering different POIs categories and the classifications proposed above. Therefore, this methodology can support future practitioners both in the definition of the suitability of a charging geographical position for specified energy management strategies (e.g., V2G) and the best path planning for a defined charging location. Lastly, the proposed model is applied to a real case study, functional to the XL-Connect Horizon Europe project. The results proposed utilized open-source geographical data and can be obtained for other worldwide case studies
Notes:
Vendor supplied data
Publisher Number:
2024-37-0003
Access Restriction:
Restricted for use by site license

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