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Data

How quickly did each electricity source scale up?

See all data and research on:
Energy

What you should know about this indicator

  • Each electricity source is tracked from the first year in which its global electricity production surpassed 100 TWh. For example, wind power surpassed 100 TWh in 2005, and hence the first data point (on year zero) corresponds to wind power's global electricity production in 2005; the next data point is wind power's production in 2006, and so on.
  • This means that year zero corresponds to different calendar years for different electricity sources. For example, year zero corresponds to 2005 for wind power, but to 2013 for solar power.
How quickly did each electricity source scale up?
Measured in .
Source
Ember (2026); Pinto et al. (2023) – with major processing by Our World in Data
Last updated
February 6, 2026
Next expected update
February 2027
Date range
0–106
Unit
terawatt-hours

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
January 26, 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
January 26, 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
January 9, 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
January 9, 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).

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.

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
  • We combine historical estimates from Pinto et al. (2023) with Ember's Yearly electricity data. Where data from both sources is available, data from Ember is prioritized.
  • For each electricity source, we identify the first year in which global electricity production surpassed 100 TWh, and track the evolution of global electricity production from that year onward.

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: How quickly did each electricity source scale up?”, part of the following publication: Hannah Ritchie, Pablo Rosado, and Max Roser (2023) - “Energy”. Data adapted from Ember, Pinto et al.. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/electricity-source-scale-up.html [online resource] (archived on March 4, 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); Pinto et al. (2023) – with major processing by Our World in Data

Full citation

Ember (2026); Pinto et al. (2023) – with major processing by Our World in Data. “How quickly did each electricity source scale up?” [dataset]. Ember, “Yearly Electricity Data Europe”; Ember, “Yearly Electricity Data”; Pinto et al., “Global historical electricity” [original data]. Retrieved April 6, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/electricity-source-scale-up.html (archived on March 4, 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-source-scale-up.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/electricity-source-scale-up.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

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

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

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

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

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/electricity-source-scale-up.csv?v=1&csvType=full&useColumnShortNames=false")

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