Predictive Modelling of XLPE Cable Systems Using Real-Time Monitoring via Distributed Sensing and Edge Integration in the EASY-DC framework

(DAS), vibration monitoring, and Partial Discharge (PD) detection to enable real-time cable condition monitoring and assessment. The work is developed within the EasyDC-FOS project, where advanced XLPE insulation systems for HVDC cables are combined with monitoring technologies to support improved reliability and lifetime estimation.

The paper then extends to describe the practical challenges of installing and integrating these sensor systems within cable corridors. The challenges vary from technicality to communication and infrastructural aspects. Therefore, two real-world use cases are included to illustrate the effectiveness of the proposed solutions. The two cases demonstrate the capabilities of DTS,

DAS, PD and vibration sensors, in XLPE HVDC and XLPE HVAC cable systems in Denmark and Norway, respectively.

With the knowledge above, the study concludes that the integration of advanced sensor technologies, combined with predictive modelling and secure edge infrastructures, provides a robust framework for improving the reliability, lifespan, and operational efficiency of XLPE cable systems. Furthermore, the practical validation through the planned use cases reveals the potential benefits of these technologies in real-world applications, paving the way for futureproof cable networks that support ambitious renewable energy objectives.