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Electricity mix

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Electricity mix

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About this data

Total electricity generation
Total electricity generated in each country or region, measured in .
Source
Ember (2026); Energy Institute - Statistical Review of World Energy (2026); Pinto et al. (2023); Department for Business, Energy & Industrial Strategy of the UK (2023) – with major processing by Our World in Data
Last updated
June 30, 2026
Next expected update
June 2027
Date range
1900–2025
Unit
terawatt-hours

Related research and writing

Energy

Hannah Ritchie and Pablo Rosado

Global renewables are growing, but have been partly offset by a decline in nuclear production

Hannah Ritchie

Sources and processing

This data is based on the following sources

Ember – Yearly Electricity Data Europe

This dataset contains yearly electricity generation, capacity, emissions, imports and demand data for European countries.

You can find more about Ember's methodology in this document.

Retrieved on
April 24, 2026
Retrieved from
https://ember-energy.org/data/yearly-electricity-data/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Ember - Yearly Electricity Data Europe (2026).
Most of the data is taken from the European Commission's Eurostat annual data.

This dataset contains yearly electricity generation, capacity, emissions, imports and demand data for European countries.

You can find more about Ember's methodology in this document.

Retrieved on
April 24, 2026
Retrieved from
https://ember-energy.org/data/yearly-electricity-data/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Ember - Yearly Electricity Data Europe (2026).
Most of the data is taken from the European Commission's Eurostat annual data.

Ember – Yearly Electricity Data

This dataset contains yearly electricity generation, capacity, emissions, import and demand data for over 200 geographies.

You can find more about Ember's methodology in this document.

Retrieved on
April 24, 2026
Retrieved from
https://ember-energy.org/data/yearly-electricity-data/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Ember - Yearly Electricity Data (2026).
The data is collected from multi-country datasets (EIA, Eurostat, Energy Institute, UN) as well as national sources (e.g China data from the National Bureau of Statistics).

This dataset contains yearly electricity generation, capacity, emissions, import and demand data for over 200 geographies.

You can find more about Ember's methodology in this document.

Retrieved on
April 24, 2026
Retrieved from
https://ember-energy.org/data/yearly-electricity-data/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Ember - Yearly Electricity Data (2026).
The data is collected from multi-country datasets (EIA, Eurostat, Energy Institute, UN) as well as national sources (e.g China data from the National Bureau of Statistics).

Energy Institute – Statistical Review of World Energy

The Energy Institute Statistical Review of World Energy analyses data on world energy markets from the prior year.

Retrieved on
July 2, 2026
Retrieved from
https://www.energyinst.org/statistical-review/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Energy Institute - Statistical Review of World Energy (2026).

The Energy Institute Statistical Review of World Energy analyses data on world energy markets from the prior year.

Retrieved on
July 2, 2026
Retrieved from
https://www.energyinst.org/statistical-review/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Energy Institute - Statistical Review of World Energy (2026).

Pinto et al. – Global historical electricity

Global historical electricity, from 1900 to 2017. The data was extracted from the supplementary materials of Pinto et al. (2023), "The rise and stall of world electricity efficiency:1900–2017, results and insights for the renewables transition".

Retrieved on
February 6, 2026
Retrieved from
https://doi.org/10.1016/j.energy.2023.126775
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Ricardo Pinto, Sofia T. Henriques, Paul E. Brockway, Matthew Kuperus Heun, Tânia Sousa,
The rise and stall of world electricity efficiency:1900–2017, results and insights for the renewables transition, Energy, Volume 269, 2023, 126775, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2023.126775.

Global historical electricity, from 1900 to 2017. The data was extracted from the supplementary materials of Pinto et al. (2023), "The rise and stall of world electricity efficiency:1900–2017, results and insights for the renewables transition".

Retrieved on
February 6, 2026
Retrieved from
https://doi.org/10.1016/j.energy.2023.126775
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Ricardo Pinto, Sofia T. Henriques, Paul E. Brockway, Matthew Kuperus Heun, Tânia Sousa,
The rise and stall of world electricity efficiency:1900–2017, results and insights for the renewables transition, Energy, Volume 269, 2023, 126775, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2023.126775.

Department for Business, Energy & Industrial Strategy of the UK – UK's historical electricity data

The historical electricity data in the United Kingdom comes from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy (BEIS).

Retrieved on
December 12, 2023
Retrieved from
https://www.gov.uk/government/statistical-data-sets/historical-electricity-data
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
The historical electricity data in the United Kingdom (2023) comes from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy (BEIS).

The historical electricity data in the United Kingdom comes from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy (BEIS).

Retrieved on
December 12, 2023
Retrieved from
https://www.gov.uk/government/statistical-data-sets/historical-electricity-data
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
The historical electricity data in the United Kingdom (2023) comes from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy (BEIS).

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator
  • Electricity data from 2000 onwards (and from 1990 onwards for European countries, including Turkey) comes from Ember. Earlier data comes from the Energy Institute.
  • For the World, data before 1965 (going back to 1900) comes from a historical reconstruction by Pinto et al. (2023).
  • For the United Kingdom, data for earlier years comes from the UK's Department for Business, Energy & Industrial Strategy (BEIS).

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Total electricity generation”, part of the following publication: Hannah Ritchie, Pablo Rosado, and Max Roser (2023) - “Energy”. Data adapted from Ember, Energy Institute, Pinto et al., Department for Business, Energy & Industrial Strategy of the UK. Retrieved from https://archive.ourworldindata.org/20260807-080945/grapher/electricity-mix.html [online resource] (archived on August 7, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Ember (2026) and other sources – with major processing by Our World in Data

Full citation

Ember (2026); Energy Institute - Statistical Review of World Energy (2026); Pinto et al. (2023); Department for Business, Energy & Industrial Strategy of the UK (2023) – with major processing by Our World in Data. “Total electricity generation” [dataset]. Ember, “Yearly Electricity Data Europe”; Ember, “Yearly Electricity Data”; Energy Institute, “Statistical Review of World Energy”; Pinto et al., “Global historical electricity”; Department for Business, Energy & Industrial Strategy of the UK, “UK's historical electricity data” [original data]. Retrieved August 7, 2026 from https://archive.ourworldindata.org/20260807-080945/grapher/electricity-mix.html (archived on August 7, 2026).

Download

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Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/electricity-mix.csv?v=1&csvType=full&useColumnShortNames=false&frequency=annual&metric=per_capita&source=gas
Metadata URL (JSON format)
https://ourworldindata.org/grapher/electricity-mix.metadata.json?v=1&csvType=full&useColumnShortNames=false&frequency=annual&metric=per_capita&source=gas

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/electricity-mix.csv?v=1&csvType=full&useColumnShortNames=false&frequency=annual&metric=per_capita&source=gas")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/electricity-mix.csv?v=1&csvType=full&useColumnShortNames=false&frequency=annual&metric=per_capita&source=gas", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/electricity-mix.metadata.json?v=1&csvType=full&useColumnShortNames=false&frequency=annual&metric=per_capita&source=gas").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/electricity-mix.csv?v=1&csvType=full&useColumnShortNames=false&frequency=annual&metric=per_capita&source=gas")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/electricity-mix.metadata.json?v=1&csvType=full&useColumnShortNames=false&frequency=annual&metric=per_capita&source=gas")
Stata
import delimited "https://ourworldindata.org/grapher/electricity-mix.csv?v=1&csvType=full&useColumnShortNames=false&frequency=annual&metric=per_capita&source=gas", encoding("utf-8") clear