Digital twins (DTs) are data-driven virtual representations of physical assets, processes and systems across the electricity network, from individual components up to system-level views. By combining real-time and historical data with simulation models and advanced analytics, they enable monitoring, diagnosis, forecasting and scenario evaluation across planning, operation and maintenance activities. Rather than a single unified model, Digital Twins for DSOs typically evolve as a federation of purpose-specific twins, supporting different decision horizons (exploratory, planning-grade and operational) and responsibilities. They rely on four core technological enablers: grid sensing and IoT, simulation and system models, AI-based analytics, and scalable cloud–edge computing infrastructures.
Highlights
Digital Twins are becoming a foundational enabler of the digitalisation of European electricity distribution networks. They significantly improve situational awareness, decision quality and resilience across planning and operational timeframes. European initiatives and pilots are progressively validating Digital Twin approaches aligned with the EU Digitalisation of Energy Systems and Grid Action Plan. Their value depends not only on data availability, but also on organisational readiness, governance structures and trust in model outputs.
Challenges and opportunities for DSOs
Opportunities
- Improved decision quality and confidence in planning and operations.
- Faster and more robust scenario analysis under uncertainty.
- Enhanced resilience through predictive insights and anticipation of grid constraints.
- Over time, enabling semi‑automated and adaptive decision support in core DSO processes.
Challenges
- Ensuring sufficient data availability, quality, integration and scalability across heterogeneous systems.
- Managing model validation, change management and organisational adoption.
- Aligning Digital Twin outputs with operational responsibilities and regulatory requirements.
E.DSO considerations
- Digital Twins should be understood as modular, use‑case oriented capabilities, rather than a single monolithic system.
- Clear ownership, validation processes and accountability for decisions are essential to ensure trust and sustained value creation.
- Interoperability, standard interfaces and alignment with existing DSO systems (e.g. ADMS, DERMS, GIS) are critical.
- Adoption should follow a progressive approach, matching maturity levels to operational criticality and regulatory constraints.
- Coordinated knowledge sharing across DSOs can accelerate learning, scalability and replicability.
Potential use cases
- Network planning and hosting capacity assessment.
- Active system management and flexibility assessment.
- Asset health monitoring and predictive maintenance.
- Cyber‑physical grid resilience and security analysis.
- TSO–DSO coordination and system-wide simulations.
- Operator training and preparedness.
- Disaster response and restoration planning.
- Energy efficiency and optimisation studies.
Ongoing projects
- TwinEU – Horizon Europe project developing interoperable Digital Twin concepts, data and model exchange frameworks .
- Enedis – Digital Twin applications supporting asset management, grid operation and planning through advanced simulations and analytics.
- E-REDES – Digital Twin and analytics solutions for network optimisation, power flows, asset health and real-time visualisation.
- EDP – AI‑based Digital Twin initiatives for short‑term forecasting to support operational and planning decisions.
- ORES – Deployment of Digital Twin-related tools for LV grid analysis, DER integration and operational planning.
- UFD (Naturgy) – Deployment of Digital Twins for MV and LV networks supporting planning, operation and DER integration.
Link to relevant E.DSO success cases
| Success case number | Title | Company |
| 31.2025 | LV Advanced Planning | UFD |
| 42.2025 | SOLORMAX | ORES |
Impact on the energy system
Digital twins improve observability and resilience by enabling predictive, data‑driven decisions, better risk anticipation and more efficient integration of distributed energy resources.
Time to scale
- 0–5 years (Progressive scaling already underway for planning-grade and selected operational use cases, with broader deployment expected within this timeframe.)
Link to relevant EU policies
- Digitalisation & Data – Digitalising the Energy System – EU Action Plan (COM/2022/552)
- Flexibility – Increasing Flexibility in the EU Energy System – European Parliament (2025)
- Decarbonisation & System Integration- Energy System Integration Strategy – European Commission
Technology deployment across countries with E.DSO members
Last update: 12 September 2026