yzzpz/Charged-data

CHARGED Dataset Description

Overview

The CHARGED (City-scale and Harmonized Dataset for Global Electric Vehicle Charging Demand Analysis) dataset provides comprehensive electric vehicle charging data and related auxiliary information for six major cities worldwide: Los Angeles, São Paulo, Shenzhen, Amsterdam, Johannesburg, and Melbourne.

Dataset Versions

Each city has two data versions:

• Standard version: Complete dataset with all charging sites
• xxx_remove_zero version: Filtered dataset with charging sites that have zero charge volume, charge duration, and price removed for cleaner analysis

Data Structure

Each city folder contains 10 CSV files. Due to size limitations, some files larger than 100MB are compressed in csv-larger-than-100MB.rar.

File Descriptions

Core Charging Data

volume.csv

• Description: Hourly charging volume (energy consumption) data
• Format: Time series with hourly granularity
• Index: Timestamps (hourly intervals)
• Columns: Site IDs
• Unit: Kilowatt-hours (kWh)
• Use Case: Primary target variable for demand prediction

duration.csv

• Description: Charging duration data representing time spent charging
• Format: Time series with hourly granularity
• Index: Timestamps (hourly intervals)
• Columns: Site IDs
• Unit: Hours (h)
• Note: Values represent charging duration between consecutive time intervals

Pricing Information

e_price.csv

• Description: Electricity charging fees (energy cost)
• Format: Time series with hourly granularity
• Index: Timestamps (hourly intervals)
• Columns: Site IDs
• Units by City:
  • Los Angeles: USD/kWh
  • São Paulo: Brazilian Real (BRL)/kWh
  • Shenzhen: Chinese Yuan (CNY)/kWh
  • Amsterdam: Dutch Guilder/kWh
  • Johannesburg: South African Rand (ZAR)/kWh
  • Melbourne: Australian Dollar (AUD)/kWh

s_price.csv

• Description: Service fees (additional charges beyond electricity cost)
• Format: Time series with hourly granularity
• Index: Timestamps (hourly intervals)
• Columns: Site IDs
• Note: São Paulo, Johannesburg, and Melbourne have no service fees (uniformly set to 0)
• Units: Same as e_price.csv for each respective city

Infrastructure Information

sites.csv

• Description: Comprehensive information about charging sites
• Key Fields:

Field	Description	Unit
site_id	Unique identifier for the charging site	N/A
longitude	Geographical longitude of site location	Degrees
latitude	Geographical latitude of site location	Degrees
charger_num	Number of charging chargers at the site	Count
total_duration	Total charging duration recorded at site	Hours
total_volume	Total charging volume recorded at site	kWh
avg_power	Average charging power per charging record	kW
perimeter	Perimeter of DBSCAN cluster shape	Meters (m)
area	Area of DBSCAN cluster shape	Square meters (m²)

chargers.csv

• Description: Detailed information about individual charging chargers
• Key Fields:

Field	Description	Unit
charger_id	Unique identifier for the charging charger	N/A
longitude	Geographical longitude of charger location	Degrees
latitude	Geographical latitude of charger location	Degrees
site_id	Identifier of the site containing this charger	N/A
total_duration	Total charging duration at this charger	Hours
total_volume	Total energy delivered at this charger	kWh
avg_power	Average charging power per charging record	kW

Auxiliary Data

distance.csv

• Description: Inter-site distance matrix
• Format: Symmetric matrix
• Index/Columns: Site IDs
• Calculation: Geodesic distance based on ellipsoidal Earth model
• Unit: Kilometers (km)
• Use Case: Spatial analysis and clustering

weather.csv

• Description: Hourly weather data from Visual Crossing API
• Source: Visual Crossing Weather API
• Key Fields:

Field	Description	Unit
temp	Temperature	Celsius (°C)
feelslike	Apparent temperature (heat index/wind chill)	Celsius (°C)
humidity	Relative humidity	Percentage (%)
dew	Dew point temperature	Celsius (°C)
precip	Liquid precipitation amount	mm
snow	Snowfall amount	mm
snowdepth	Snow depth on ground	mm
preciptype	Precipitation type	Array (rain/snow/freezingrain/ice)
windgust	Instantaneous wind speed	km/h
windspeed	Sustained wind speed	km/h
winddir	Wind direction	Degrees
pressure	Sea level atmospheric pressure	hPa
visibility	Visibility distance	km
cloudcover	Cloud coverage	Percentage (0-100%)
solarradiation	Solar radiation power	W/m²
solarenergy	Solar energy accumulation	MJ/m²
uvindex	UV exposure index	Scale (0-10)
conditions	Weather conditions	Categorical (see mapping below)

Weather Conditions Mapping:

• 0: Clear
• 1: Overcast
• 2: Partially cloudy
• 3: Rain
• 4: Rain, Fog
• 5: Rain, Overcast
• 6: Rain, Partially cloudy
• 7: Snow
• 8: Snow, Fog
• 9: Snow, Partially cloudy
• 10: Snow, Rain
• 11: Snow, Rain, Overcast
• 12: Snow, Rain, Partially cloudy

poi.csv

• Description: Points of Interest (POIs) from OpenStreetMap
• Source: OpenStreetMap
• Categories: Amenities, buildings, offices, shops, leisure facilities, etc.
• Reference: OSM Wiki - Map Features
• Fields:

Field	Description	Unit
type	Geographic feature category	N/A
longitude	POI longitude	Degrees
latitude	POI latitude	Degrees

Metadata

info.csv

• Description: Dataset metadata and summary statistics
• Key Fields:

Field	Description	Unit
city	City name	N/A
country	Country name	N/A
abbreviation	City code (3-letter)	N/A
total_chargers	Total number of charging chargers	Count
total_sites	Total number of charging sites	Count
DBSCAN_eps	DBSCAN clustering radius parameter	Meters (m)
total_duration	Total charging duration in dataset	Hours
total_volume	Total charging volume in dataset	kWh
avg_power	Average charging power across all records	kW

Data Quality Notes

Preprocessing Applied

• Anomaly Detection: Outliers identified and corrected using IQR method
• Zero Sequence Handling: Zero sequences interpolated
• Site Clustering: Geographic clustering using DBSCAN algorithm

Known Limitations

• Some cities may have missing data during certain time periods
• Weather data availability depends on API coverage
• POI data completeness varies by city and OSM coverage
• Currency exchange rates not provided for cross-city comparisons

Support

For questions about the dataset, please refer to:

• Main project documentation: README.md
• GitHub Issues: Project Issues
• Contact: guozh29@mail2.sysu.edu.cn