Every time you use more electricity, that instantly causes a power plant to make a little more. But… which power plant? Usually, it’s a fossil fuel plant burning coal or gas, which is why using energy creates pollution. Yet as renewable energy keeps growing, there are more and more moments when using electricity instead only activates a clean power plant like wind or solar. To help people understand the emissions caused by when they use electricity and to help them cause fewer emissions, WattTime produces marginal emissions data and makes them available through an API.
What is it?
The Marginal Operating Emissions Rate (MOER) represents the emissions rate of the electricity generator(s) that are responding to changes in load on the local grid at a certain time. The MOER includes the effects of renewable curtailment and import/export between grid regions. The units of MOER are the amount of pollution per unit of energy (lbs/MWh).
How is it used?
The MOER can be used to make decisions that avoid the most emissions. IoT companies use the MOER forecast as an input signal to their device scheduling optimization, or to create a UI element advising users when to run appliances or plug in an EV. Renewable energy purchasers use the historical MOER to select a project that avoids relatively more emissions. In emissions accounting, the MOER is used to account for the avoided emissions of a project as described by the GHGP Project Protocol and the Guidelines for Quantifying GHG Reductions from Grid-Connected Electricity Projects.
Temporal coverage
- Granularity: 5 minutes
- Historical: At least 2 years in the past, published usually within 6 hours
- Forecast: +72 hours (rolling 3-day forecast), published usually within 30 seconds
- Forecast (Historical): At least 2 years in the past
Geographic coverage
- Granularity: MOER regions are typically balancing regions or subregions
- Coverage: Global (200+ countries & territories); MOER Signal coverage can be seen here
Methodology + validation
WattTime builds MOER models based on the empirical technique founder Gavin McCormick published in peer-reviewed academic literature. WattTime’s research group continues to develop the methodology to provide the most impactful and actionable signal possible with available data. WattTime recognizes that any MOER model needs to be validated in order to be confident that its use will reduce emissions. WattTime’s research team performs validation of each model it produces and leads an external coalition for improving the tools used for validating marginal emissions models.
Learn more about WattTime's methodology and validation.
Learn more about WattTime's methodology and validation.