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

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2024-08-30 DOI:10.1016/j.dib.2024.110883

Åse Lekang Sørensen , Igor Sartori , Karen Byskov Lindberg , Inger Andresen

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引用次数: 0

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.

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来自挪威 12 个住宅区的 35,000 次电动汽车充电数据集

本数据文章引用了论文 "挪威大型案例研究中生成完整电动汽车充电数据集和分析居民充电行为的方法"[1]。电动汽车（EV）充电数据集包括超过 35,000 个住宅充电时段的插入时间、拔出时间和充电能量的详细信息，涵盖挪威成熟电动汽车市场 12 个地点的 267 个用户 ID。利用文献[1]中概述的方法，数据集中集成了现实预测，包括电动汽车电池容量、充电功率以及每个电动汽车用户和充电时段的插电充电状态（SoC）。此外，还提供了每小时的数据，如每个充电时段的充电能量和连接能量容量。该综合数据集为评估当前和未来的电动汽车充电行为、分析和模拟电动汽车充电负荷和能源灵活性以及研究电动汽车与电网的整合提供了基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

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