Artificial intelligence (AI) is revolutionising the power industry by improving equipment upkeep predictability, optimising resource allocation, and enhancing efficiency.

GlobalData, a data and analytics company, reports that AI can decrease maintenance costs by up to 30 per cent and increase equipment availability by 20 per cent.

Companies like GE Vernova, Siemens, and Schneider Electric offer advanced predictive maintenance solutions.

Companies like E.ON and Enel have equipped their turbines with sensors to monitor variables like temperature, vibration, wind speed, and output, enabling precise data collection and improved performance.

RWE has deployed condition monitoring systems across its network of wind turbines, while Enel Green Power has implemented a diagnostics software solution to detect irregularities in photovoltaic panels.

Predictive maintenance is also gaining prominence in energy storage systems, such as Enel Green Power’s battery system optimisation strategy and the European Commission’s Horison Europe programme’s TwinEU project.

The WindTwin initiative, funded by Innovate UK, aims to develop digital twins to replicate wind turbines. Montel Energy uses IoT-based predictive maintenance to monitor energy assets in real-time.