New research published in the International Journal of Information and Communication Technology suggests that so-called knowledge graphs, a form of AI-based data organization, could improve the reliability and maintenance of power communication systems that help keep the lights on and modern electricity grids running smoothly.
The researchers report that such a system works better than a conventional database in query efficiency, fault diagnosis, and operational decision-making. They explain that this technology could be used to help utility operators anticipate equipment failures earlier and manage increasingly complex power networks more effectively.
Power communication equipment functions as the information backbone of electricity grids, enabling substations, sensors and control centers to exchange data in real time. However, as grids are becoming more digitalized through smart sensors, distributed energy systems and private 5G networks, operators are generating far larger volumes of interconnected data that somehow has to be managed.
The researchers argue that conventional relational databases struggle with this level of complex data. Relational databases organize information into rigid tables linked by predefined relationships. While suitable for simpler systems, the researchers say they create information silos in large infrastructure networks, where maintenance records, fault reports, environmental conditions, and operational data are fragmented across separate systems.
