The carbon intensity forecast you see on this dashboard is produced by the National Energy System Operator (NESO). It predicts how "clean" or "dirty" Great Britain's electricity will be up to 48 hours ahead, measured in grams of CO₂ per kilowatt-hour (gCO₂/kWh). Here's how it works, explained simply:
Multiple ML models are trained on historical data — how much gas, wind, solar, nuclear, and coal have been used, combined with weather forecasts, time of day, and season.
Instead of relying on one model, NESO uses an "ensemble" — like asking several expert forecasters and blending their answers into one optimised meta-model (a "super-prediction").
To work out carbon intensity per region, they simulate how electricity actually flows through the GB grid — a simplified model of the entire national transmission network.
This accounts for real physics: power losses in cables, how power splits at junctions, and import flows from France, Netherlands and Ireland. It's about what arrives at your region, not just what's generated.
Every 30 minutes, the forecast is refreshed using nowcasting — taking the latest real-time grid measurements and nudging the forecast to stay accurate short-term.
Think of it like GPS recalculating your route — the long-range plan stays, but the next few steps get fine-tuned with live data.
Grid is extremely clean. Lots of wind/solar/nuclear. Best time for EV charging or running heavy appliances.
Good conditions. Renewables and nuclear doing most work. Still a great time for flexible energy use.
Mix of clean and fossil. Gas plants ramping up. Shift heavy usage to a greener window if possible.
Fossil fuels dominant. High demand or low renewable output. Reduce non-essential consumption.
Grid is very carbon-heavy. Coal/gas working hard. Peak demand. Postpone heavy usage if possible.
Carbon intensity directly affects carbon credit costs and emissions trading schemes. Higher intensity = higher carbon cost exposure for energy-intensive businesses.
Companies tracking Scope 2 emissions need real-time grid carbon data to calculate their electricity-related carbon footprint accurately.
Forecast carbon intensity helps predict wholesale electricity prices — high renewable output means lower prices and lower carbon, creating trading opportunities.