Digitalization of transformer substation using QMU and AI-based analytics for fault forecasting

Purpose and goal

The project modernizes substations to handle the increasing complexity of energy systems, driven by the electrification of industry. EcoPhi’s AI-driven Merging Unit (QMU) is installed at Ellevio and Härryda Energi and combined with Eneryields AI-analysis. QMU sampling rate of 1.5 million data points per second improves error detection, reliability and energy efficiency. The project supports energy transition, reduces downtime and environmental impact and promotes the FN Agenda 2030-objective.

Expected effects and result

The project will digitalize substations, enhancing fault forecasting, localization, and root cause analysis through AI and high-frequency data sampling. It ensures scalability, energy efficiency, and cybersecurity while advancing technology readiness from TRL 5 to 7. The project supports Sweden´s energy transition by increasing grid reliability, reducing disruptions, and promoting sustainable industrial electrification, aligning with global goals for clean energy, innovation, and sustainability.

Planned approach and implementation

The project spans during five WPs: WP1 handles hardware installation and QMU setup in four months. WP2 establishes data communication by month 5. WP3 focuses on system integration and testing in one month. WP4, led by Eneryield, optimizes AI and ensures IT security. WP5 finalizes AI deployment with feedback and iteration. Continuous collaboration between EcoPhi, Eneryield, Ellevio, and Härryda Energi ensures data sharing and system improvement throughout.