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Explore the largest electricity & carbon database

powering the electricityMap Live  

A global and granular database with deep market insights

The electricityMap database contains a vast amount of data related to electricity system dynamics, associated carbon emissions, prices and weather.

Public Data
Public Data
Standardized data collected hourly from over 70 data providers
Electricity Generation  
Electricity Prices  
Electricity Exchanges  
Weather  

available as hourly CSV files,
additionally as API with forecasts

Flow-traced Data
Flow-traced Data
Data based on our proprietary flow-tracing models
Origin of electricity  
(by zone)
Origin of electricity  
(by plant type)
Carbon intensity  

available as hourly CSV files,
additionally as API with forecasts

Marginal Data
Marginal Data
Data based on our proprietary machine-learning models
Marginal origin of power  
(by zone)
Marginal origin of power  
(by plant type)
Marginal Carbon Intensity  

available as hourly CSV files,
additionally as API with forecasts

Multiple dimensions

Physical electricity flows
Marginal origin of power
Consumption-based carbon emissions
Market Prices and Weather

Global coverage

Worldwide coverage
National and sub-national level
Standardized across regions

Long time-span

Several years of historical data
hourly to minute granularity
With real-time forecasts

Explore our data samples

Carbon Intensity
Origin of electricity
more examples soon

Methodology

Read more about our methodology on our blog .

Standardize

Validation and Standardization

We collect data from over 70 different data providers at the rate of 300 datapoints per seconds. This includes generation mixes, imports and exports, market prices and weather data. Those datapoints are then carefully validated and standardized in order to be comparable across regions.

Flow-tracing

Flow-Tracing

Starting from generation and exchange data, we can trace back the physical origin or electricity consumed in each zone using flow-tracing algorithms. This is done in real-time, enabling us to compute the consumption mix of each zone, which takes into account not only local generation but also electricity imports. Using IPCC carbon emission factors, we compute the carbon emissions associated with the consumption of a unit of electricity in a given zone and at a given time.

Flow-tracing

Marginal impacts

We train artificial intelligence algorithms on our historical datasets in order to forecast the whole electricity system over the next 48 hours. Our algorithms also learn how the electricity system reacts to a change in local consumption. This enables us to assess the impact of installating an additional solar panel or smart charging an electric vehicle. As our algorithms extract structured knowledge, we can understand which type of power plant is affected by thoses changes, and where those impacts are the highest.

Partners and Advisors

Usecases

electricityMap Data

Precise carbon accounting of electricity consumption

Hourly carbon intensity data (includes all greenhouse gases)
Regional granularity taking into account electricity imported
Using certified carbon emissions factors for each power plant type

electricityMap Data

Carbon impact analysis of your installation

Choose the best location for your new renewable project
Quantify the carbon avoided by the smart charging of your electric vehicle
Compute GHG emissions avoided using our marginal carbon intensity data
Claim your environmental benefits using carbon offsets
Compliant with the GHG Project Protocol

ShowcasesSmart EV charging (Parker Project)

electricityMap Data

In-depth analyses of electricty sytems

Compare regions using standardized electrictyMap data
Train your machine-learning algorithms on our validated datasets
Extract and publish powerful insights based on our hourly datasets

ShowcasesClimate Leadership Report 2017 Tomorrow's 2017 Summer Report

Available in 126 geographies

And growing.

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