AI for the electricity grid

Utilities in Europe are starting to use predictive maintenance, a system where sensors and software track the condition of grid equipment and flag problems before they cause outages. This is background infrastructure news rather than something that changes what a homeowner does, but it affects how reliable your power supply is and how the grid absorbs solar and wind power over time.

In Finland, utility Helen uses sensors on cables, transformers, and substations to catch early signs of wear, such as gas buildup in transformers or electrical faults in cables, before they cause a blackout. This has let the utility stretch out testing schedules and cut costs, and the company already reports very short average outage times per customer each year. In Ireland, utility ESB is using similar tools on transformers and switchgear, saying it has helped avoid unplanned outages and delayed costly early replacement of equipment. Both utilities note this technology helps manage the growing number of solar and wind installations spread across remote areas, which are harder to inspect in person.

The technology has limits. Sensors sometimes give false readings, retrofitting old equipment with new digital monitoring is difficult, and the upfront cost of sensors and software is significant. The International Energy Agency has also warned that grid investment across Europe is not keeping pace with the fast rollout of renewable power, which can cause delays connecting new solar and wind projects to the grid. Engineers interviewed say the industry still needs clearer shared standards before these AI-based monitoring tools are used more widely.