DSO integration of digital twins remains limited - report

The report, from the DSO Entity led DSO4DT project, finds that many DSOs are actively strengthening foundational capabilities such as data integration, observability, and modelling, with an increasing focus on delivering demonstrable operational value.

However, fully integrated, dynamically updated, interoperable digital twin environments remain limited to a very limited number of DSOs, representing isolated exceptions rather than an identifiable group.

Digital twin development across Europe can therefore be characterised as progressive and evolutionary, the study states.

The report, a first iteration and key project deliverable, is based on assessment of four outcome categories:

1. Strengthened observability and controllability of the grid;
2. Optimised infrastructure and network planning;
3. Joint modelling for a more resilient grid;
4. Increased use of active system management and forecasting.

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In parallel, the DSO Entity and ENTSO-E are jointly analysing the role of digital twins for the European electricity grid through a structured technical cooperation.

This joint work highlights that the future European digital twin landscape is likely to consist of interoperable digital twins operating at different system levels rather than a single centralised model.

From this perspective DSOs develop digital twins reflecting distribution system characteristics and TSOs operate digital twins reflecting transmission system dynamics, while interoperability mechanisms enable coordinated modelling and structured information exchange.

DSO landscape

The report finds that despite heterogeneity, several strengths are consistently observable across the European DSO community.

There is a high level of technical expertise in network planning and system operation. The ongoing energy transition has accelerated digitalisation efforts, particularly in areas related to renewable integration and flexibility. Regulatory transparency obligations and European level collaboration platforms have further stimulated data exchange and coordination.

These strengths provide a solid foundation for progressive digital twin adoption. At the same time, recurring structural challenges and gaps affect the pace of digital twin deployment.

These include fragmented data architectures, limited availability of specialised digital modelling expertise, organisational silos between IT and grid operation functions, and regulatory uncertainty regarding cost recovery for advanced digital investments.

Uneven low voltage observability is also identified as a gap.

Initial roadmap

The report also introduces an initial roadmap, including achievable short-term steps and an outline of an implementation support framework.

The first phase focuses on enabling conditions that are achievable within a relatively short time horizon and that provide immediate value for DSOs.

Priority areas include strengthening data governance and integration, improving model consistency across planning and operations, targeted enhancement of observability and clarifying the internal use cases.

Once the foundational capabilities are strengthened, DSOs may progressively expand digital twin functionalities. Medium-term development pathways include introduction of more advanced scenario simulation tools, integration of forecasting models directly into planning and operational workflows, embedding resilience and stress scenario modelling and gradual alignment with evolving interoperability standards.

At this stage, digital twins begin to move from enhanced digital models toward more dynamic and decision-oriented tools, the report states. Federated or cross organisational modelling environments may become relevant for some DSOs at this stage, but only where internal digital twin maturity is sufficiently developed.

The report also notes that the roadmap provides a modular orientation framework to be adaptable to the diversity of DSOs in Europe.

For example, for DSOs with advanced digital integration, the priority may lie in enhancing dynamic modelling capabilities and resilience simulations. For DSOs at earlier stages of digital maturity, the focus may be on structured data governance and model consolidation.

For smaller DSOs with limited internal digital expertise, collaboration, shared platforms and knowledge exchange mechanisms may represent more efficient pathways than isolated in-house development.

Alongside structured support mechanisms to be provided by DSO4DT include knowledge dissemination, peer exchange and community building, guidance and orientation materials and integration into the knowledge platform.