Live Carbon Intensity
Live Power breakdown
Live Carbon Intensity
Live Power breakdown
Live + Forecasted Carbon Intensity
Live + Forecasted Power breakdown
Live + Forecasted + Marginal Carbon Intensity
Live + Forecasted + Marginal Power breakdown
Historical Average + Forecasted + Marginal Carbon Intensity
Historical Average + Forecasted + Marginal Power Breakdown
Broadly speaking, we offer hourly electricity production, consumption, and carbon intensity data in over 100 geographies around the world, including breakdowns of fuel sources used and imports/exports of power between countries and regions. You can learn more about the data we offer, including a sample output CSV and the specific units of each column here.
The raw data comes into our system from a variety of public data sources, which are listed here. Our system then standardizes and aggregates these data sources to account for imports and exports of power between countries and uses this data to train our marginal and forecast models.
The emission factors we use to calculate our carbon intensity data are from the Intergovernmental Panel on Climate Change (IPCC) 5th assessment report. However, since our API returns power production/consumption data as well as carbon intensity data, the user can use their own emission factors and come to their own carbon intensity calculations if they would like.
All of our API data is updated every hour for that hour, while our historical data is only updated if we are made aware of a data quality issue (though we periodically monitor for these issues). Our forecasts are also updated every hour, meaning that at any given time, our Forecast API returns forecasted values for the next 24 hours.
Yes, we have an extensive historical database for most areas on the electricityMap. You can learn more about how many years back our datasets go for a given area here under the “Zone covered” tab.
We offer our historical data as a paid product either in the form of our Historical API or in the form of CSV files. If you’re interested, please reach out with the contact form and specify that you’re interested in our historical datasets, along with the time period you are interested in.
In addition to writing extensive on our public Github repo about our methodology, we have also published a paper in collaboration with the Technical University of Denmark, Real-time carbon accounting method for the European electricity markets.
Finally, if you’d like to learn more about our Marginal methodology specifically, this post and this post from our blog will be helpful.
When a consumer is asking for more electricity from the grid, that additional electricity will come from the cheapest power plant that still has spare capacity at that time. This power plant is called the marginal power plant. Typically the marginal plant is a system that can react quickly to changes in electricity demand, such as a gas turbine. It however cannot be a wind turbine or solar cells, as you can’t command them to produce more (unless you command the weather that is). The carbon footprint of that additional electricity represents the consumer’s marginal emissions, and via our Marginal API we have built a model to estimate this. To learn more about the marginal methodology and how to use it, read our blog post about it.
We have set ourselves a data standard - we currently only show live, hourly-updated data on the electricityMap that is derived from hourly (or even more frequently updated) publicly available data from trusted sources. When a country or zone doesn’t have any data on the map, this is either because our data source was not reporting up to our standards or because we have not found a public data source that fits our standards.
Much of the data on the electricityMap can be attributed to our amazing community of enthusiastic contributors who have found public data sources - join us and help fill in the blanks at our public Github repo!
You can see our starting pricing for each API tier here. Our pricing varies depending on how many “zones” on the electricityMap you’d like data from, and our standard pricing is charged per month. Each tier of the API includes services from the cheaper tiers in it, except for the Historical API, which is a separate service that must be subscribed to separately.
As an example with starting pricing: If I’d like to subscribe to the Forecast API for France and Germany (each count for 1 zone on the electricityMap), it would cost me 300€/month.
It’s important to note that this is our starting pricing for basic internal study use cases. For heavier users or those looking to display our data to a number of end customers, our pricing varies. Please reach out to learn more.
The electricityMap is divided into “zones” which are represented from the boundaries depicted on electricityMap.org. These zones correspond to zones in the electricityMap API.
Often, one country equals one zone, but there are many instances where this is not the case. Countries are sometimes split into several zones, mainly because our data sources show a significant difference in power production/consumption in different regions of a country (usually this means the country is running on several distinct grids) and we have access to the public data needed to depict this.
If you are a student or from a non-profit or academic institution, let us know and we can give you a generous discount on our data or API. Additionally, anyone paying upfront, committing to a longer license, or subscribing to a large number of zones for API data will be eligible for a slight discount.
Sure! Please reach out to us via the contact form.
Sure! Reach out to us with your request via the contact form.
Please note that we only offer 1 month trials for zone of any of our API tiers, except the Historical API for which we do not offer trials. We can also provide very limited samples of our historical data for evaluation purposes (for example: 1 month from 1 zone).
For larger commercial arrangements or for institutions with strict payment constraints such as universities, we will work with you to find the payment arrangement that best fits your constraints.