Global Hourly Electricity Demand Dataset Segregated by Season and Day Type: Tracking Changes Across COVID-19 Lockdown Phases

Descripción

This dataset provides a cross-country time series of hourly typical electricity usage designed for comparative analysis of consumption patterns before, during, and after the strictest COVID-19 lockdown periods. The dataset aggregates and normalises raw usage data to present the typical hourly demand for 35 countries, segmented by season and day type (weekday vs. weekend). The primary utility of this data is to facilitate standardised analyses of the non-pharmaceutical intervention (NPI) impact on energy consumption globally. The data processing pipeline uses external master data, including government response metrics derived from the Oxford COVID-19 Government Response Tracker (OxCGRT), to precisely define and standardise the "strictest lockdown period" for each country. The dataset is shared in two primary formats to maximise reusability and accessibility: PostgreSQL Database Dump Files (.sql): This is the recommended format for researchers seeking to replicate the full data environment or integrate the data into an existing pipeline. The files were generated from a PostgreSQL 14.22 database. It is recommended to use the same version or higher to minimise compatibility issue…

Descripción de Zenodo, abreviada.

Archivos (13)

• XLSXt_test_result pre vs post.xlsx39 kB
• PYdaytype_calculate.py12 kB
• CSVelectricity_demands_hourly.csv253 kB
• SQLcalculate_lockdown_period.sql408 B
• —dataset_schema_only4,4 kB
• CSVcountry_seasons.csv1,7 kB
• CSVcountries.csv4,5 kB
• CSVcovid_lockdown.csv4,5 kB
• XLSXt_test_result pre vs during.xlsx27 kB
• —dataset_full77 MB
• PYread_data.py16 kB
• CSVcovid_stringencies.csv2,7 MB
• CSVtypical_daily_usage_patterns.csv341 kB

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