## 4 Technological Challenges and Integration Issues
### ICT Infrastructure for Large-Scale Real-Time Operations  
Developing a digital twin of the European electricity grid requires a robust and scalable ICT infrastructure capable of supporting real-time operations, large-scale data integration, and distributed computing [5]. This infrastructure serves as the nervous system of the digital twin, linking the physical grid to its virtual representation and enabling continuous observation, simulation, and forecasting [20]. A critical first step is to enhance observability across the grid. Although transmission networks are typically well instrumented with SCADA systems and phasor measurement units, many distribution networks, especially at the medium and low-voltage levels, remain insufficiently monitored [39]. The rollout of smart meters has improved visibility at the end-user level, but the data they provide often arrives at coarse time intervals and lacks the granularity required for real-time situational awareness [25]. Bridging this sensing gap will require the widespread deployment of new sensors and intelligent devices. However, implementing such deployments involves significant capital investment and integration complexity, particularly when coordination is needed across different regulatory regimes and levels of infrastructure maturity [24]. Real-time operation also depends on a reliable and high-capacity communications infrastructure. TSOs may operate private fiber-optic networks, but DSOs typically rely on heterogeneous combinations of fiber, wireless, and public telecommunications networks [25]. A continental-scale digital twin places additional demands on this infrastructure, particularly for latency-sensitive applications where control decisions must be based on sub-second data flows [5]. Future technologies such as 5G and 6G, cited in the European Commission's Digitalization Action Plan, offer potential improvements, but in the near term, investment in upgrading existing networks and ensuring interoperability across borders will be essential [1]. Communication networks must be secure, standardized, and capable of supporting the cloud-edge continuum that will likely characterize the twin's architecture [20]. In such a hybrid approach, edge devices perform latency-critical computations locally, while cloud platforms aggregate and process system-wide data for broader forecasting and analysis [5]. The digital twin will ingest vast volumes of data, including real-time telemetry, smart meter readings, weather forecasts, market prices, and asset metadata. Managing this data influx requires scalable time-series databases, high-throughput data pipelines, and flexible integration architectures that can align diverse data models and formats [24]. European initiatives such as the Common European Energy Data Space aim to standardize data exchange and promote common reference models, but the responsibility for implementation remains with system operators and developers [13]. Real-time simulation capabilities must also be supported by sufficient computational resources. The digital twin will need to perform power flow calculations, stability assessments, contingency analyses, and probabilistic forecasts across a system that may include millions of nodes [20]. Traditional simulation tools, often built for use by individual utilities, are not designed to handle these computations at the necessary speed or scale. To meet this challenge, federated modeling approaches are being explored. These approaches allow regional or national operators to simulate their respective domains independently while exchanging boundary conditionswith a central coordination layer [3]. This hierarchical strategy helps distribute the computational workload but introduces additional challenges related to synchronization and interface consistency [5]. High-performance computing and cloud infrastructure are indispensable in this context.