Building Living Digital Twins for Energy Networks: Integrating GIS, AI and Real-Time Data
Energy networks are becoming harder to operate. Decentralized generation, volatile loads, and aging infrastructure are pushing existing systems to their limits.
Most digital twins promise visibility, but in practice, they remain fragmented, static, or disconnected from operations.
We will show how living digital twins, built on geospatial technology, move beyond visualization to become operational systems that continuously integrate real-time sensor data, engineering models, and network intelligence.
Using real-world examples from the energy sector, the presentation demonstrates how utilities are:
- detecting risks such as vegetation encroachment or asset failure before they escalate
- improving decision-making through real-time spatial context
- connecting planning, construction, and operations into a shared, continuously updated model
At the core is a simple idea: location is not just context, it is the integrating framework for the entire digital twin.
By combining 3D data, real-time data and GeoAI, organizations are moving toward digital twins that are not only descriptive, but predictive and eventually adaptive.
The result is more resilient infrastructure, faster response times, and a fundamentally new way to operate energy systems.