Annual Load Dataset of Electric Vehicle Charging Stations

Citation Author(s):
Ziyu
Xu
Submitted by:
Ziyu Xu
Last updated:
Sat, 12/28/2024 - 09:50
DOI:
10.21227/rmc8-ve92
Data Format:
License:
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Abstract 

The rapid development of electric vehicles has significantly increased the demand for efficient and reliable charging infrastructure, making the analysis of charging load data essential for urban energy planning. A dataset has been compiled from charging load data collected by a smart energy measurement system deployed in a city center of China. The data covers a one-year period, recorded at hourly intervals, and includes measurements from six electric vehicle charging stations (EVCSs), designated EVCS1 to EVCS6, each characterized by distinct charging power capabilities. This dataset provides a comprehensive view of real-world energy consumption patterns, enabling the analysis of temporal load distribution, energy demand forecasting, and the optimization of urban energy management.

Instructions: 

The charging load dataset are collected by a smart energy measurement system over a one-year period, with hourly data collected from six Electric Vehicle Charging Stations (EVCSs) located in the city center of China. The data provides an annual cycle of charging behavior. The charging stations, labeled EVCS1 through EVCS6, have their loads reported in kilowatts (kW), with values recorded to four decimal places, ensuring high accuracy. Each row in the dataset includes a timestamp in the format of "YYYYMMDD," along with the charging load values for each EVCS, enabling a detailed analysis of temporal variations. The dataset has both daily and hourly granularity, capturing fluctuations in charging load at the individual station level and across all six stations. This comprehensive time series data provides a clear representation of seasonal, daily, and hourly charging patterns. This real-world dataset can be used to analyze EVCS operating patterns, optimize charging infrastructure, and study the impact of EV charging on the distribution networks.

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