AI tool to boost National Grid ESO solar forecasts

The project will see the ESO, which balances Britain’s electricity system second-by-second, work with the OCF team to develop a solar ‘nowcasting’ service for its national control room. Nowcasting involves a machine learning model forecasting the near future in minutes and hours rather than days, and has historically found use in predicting rainfall.

Co-founded by former DeepMind researcher Jack Kelly, OCF applies a similar approach to predicting where sunlight will fall, by training a machine learning model to read satellite images and understand how and where clouds are moving in relation to solar arrays below.

Uncertainty in forecasts and around location of many solar panels, most of which are connected to regional networks, make changes in solar generation difficult for grid operators to anticipate.

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Work is underway to map Britain’s solar panels but previously there has been no way to anticipate short-term swings in solar generation caused by cloud cover. To cover that uncertainty, and make sure any dip or rise in solar generation does not nudge the electricity system out of balance, the ESO keeps reserve power (often flexible gas plants) ready to respond to unexpected changes in supply and demand.

OCF’s nowcasting service could bring increased certainty resulting in fewer carbon-emitting generators held in reserve.

“Accurate forecasts for weather-dependent generation like solar and wind are vital for us in operating a low carbon electricity system,” said Carolina Tortora, head of innovation strategy and digital transformation at National Grid ESO.

“We’re increasingly using machine-learning to boost our control room’s forecasts, and this latest nowcasting project with Open Climate Fix — whose work could have real impact for grid operators around the world — will bring another significant step forward in our capability and on our path to a zero carbon grid.”

OCF’s Jack Kelly added: “We plan to adapt the amazing work done by the global machine learning community to solar electricity forecasting. All our work will be open-source, so others will be free to use the technology to help reduce emissions globally as rapidly as possible.”