Electric vehicle charging dataset with 35,000 charging sessions from 12 residential locations in Norway

This data article refers to the paper "A method for generating complete EV charging datasets and analysis of residential charging behaviour in a large Norwegian case study" [1]. The Electric Vehicle (EV) charging dataset includes detailed information on plug-in times, plug-out times, and energy charged for over 35,000 residential charging sessions, covering 267 user IDs across 12 locations within a mature EV market in Norway. Utilising methodologies outlined in [1], realistic predictions have been integrated into the datasets, encompassing EV battery capacities, charging power, and plug-in State-of-Charge (SoC) for each EV-user and charging session. In addition, hourly data is provided, such as energy charged and connected energy capacity for each charging session. The comprehensive dataset provides the basis for assessing current and future EV charging behaviour, analysing and modelling EV charging loads and energy flexibility, and studying the integration of EVs into power grids.

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Publication Details

Journal
Data in Brief
Published
2024-08-30
DOI
https://doi.org/10.1016/j.dib.2024.110883
Citations
6
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
1.25

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article

Electric vehicle charging dataset with 35,000 charging sessions from 12 residential locations in Norway

Inger Andresen, Åse Lekang Sørensen, Karen Byskov Lindberg, Igor Sartori
6 citations
Data in Brief
Electric Vehicles and Infrastructure
1.25
article

Electric vehicle charging dataset with 35,000 charging sessions from 12 residential locations in Norway

Inger Andresen, Åse Lekang Sørensen, Karen Byskov Lindberg, Igor Sartori
article en
6 citations

Abstract

This data article refers to the paper "A method for generating complete EV charging datasets and analysis of residential charging behaviour in a large Norwegian case study" [1]. The Electric Vehicle (EV) charging dataset includes detailed information on plug-in times, plug-out times, and energy charged for over 35,000 residential charging sessions, covering 267 user IDs across 12 locations within a mature EV market in Norway. Utilising methodologies outlined in [1], realistic predictions have been integrated into the datasets, encompassing EV battery capacities, charging power, and plug-in State-of-Charge (SoC) for each EV-user and charging session. In addition, hourly data is provided, such as energy charged and connected energy capacity for each charging session. The comprehensive dataset provides the basis for assessing current and future EV charging behaviour, analysing and modelling EV charging loads and energy flexibility, and studying the integration of EVs into power grids.

Data in BriefVol. 57
SINTEF (NO), Norwegian University of Science and Technology (NO)
Norges Forskningsråd
Openalex Percentile: Top 20%
Electric Vehicles and Infrastructure
1.25
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