SMIGHT GmbH and retoflow GmbH are working together to further develop a dynamic twin for distribution system operators. In a joint project with Stadtwerke Fellbach, measurement data and grid data are being used to create a digital representation of the low-voltage network. By continuously comparing real measurement data with the grid model, this representation evolves into a dynamic twin that supports grid planning, network operation and future grid management applications.

Many distribution system operators already have extensive information from GIS systems, ERP applications, load profiles and measurement technology. In practice, however, these data are often stored in separate systems.

The collaboration between SMIGHT and retoflow addresses precisely this challenge. SMIGHT contributes its expertise in grid transparency, monitoring and grid management. Based on GIS, ERP and other grid data, retoflow creates a cross-voltage-level, calculation-ready grid model as a digital representation of the electricity network. The combination makes it possible to integrate measurement data and grid data into a consistent representation of the low-voltage network. The calculation-ready grid model is based on the open-source standard pandapower. This creates a shared data foundation for planning, operation and future applications.

Fig. 1: Integration of grid operation and grid planning with SMIGHT and retoflow.

First joint project with Stadtwerke Fellbach

The joint project with Stadtwerke Fellbach demonstrates how the collaboration works in practice. The utility has been using SMIGHT measurement technology since 2020 and has now equipped 76 of its 161 secondary substations with sensors.

retoflow is currently using this measurement data to create a calculation-ready grid model. Grid data from different source systems, including the geographic information system, are combined with measurement data from the SMIGHT system and continuously validated.

Just two weeks after the complete data set had been provided, Stadtwerke Fellbach was able to evaluate the first results and carry out automated data quality checks. These initial analyses already demonstrate the value of the approach. By comparing measurement data with calculation results, anomalies were identified and the quality of the grid model was improved. For example, deviations between the model and the actual behaviour of the network became visible, providing valuable information for the further optimisation of the dynamic twin.

Measurement data turns a grid model into a dynamic twin

Grid models represent the topology of a network. However, it is only through continuous comparison with real measurement data that they become a dynamic twin. Deviations between the model and reality are identified, while the grid model is continuously validated and calibrated. As a result, the dynamic twin represents the actual behaviour of the network with increasing accuracy.

“Fellbach demonstrates that developing a dynamic twin does not have to be a major project lasting several years. By combining existing grid data with real measurement data, valuable insights were gained and data quality improved within a short period of time,” says Oliver Deuschle, Managing Director of SMIGHT GmbH.

“Many grid operators already have the necessary data. The next step is to use it to create a digital representation of the network that can be continuously compared with actual grid conditions. That is exactly what we are implementing together with SMIGHT,” says Dr.-Ing. Leon Thurner, Managing Director of retoflow.

Foundation for future applications

The Fellbach project demonstrates how existing grid data and real measurement data can be combined to create a dynamic twin. retoflow and SMIGHT are pursuing a technology-open approach. Grid operators can flexibly combine grid models and measurement data and gradually develop the dynamic twin in line with their individual requirements.