Building an accurate and robust Grid Twin for low-voltage networks starts with addressing common data quality issues, such as incorrect phase assignments, incomplete cable mapping or misconnected electrical points. From there, the approach relies on three key steps: properly mapping network topology, monitoring the grid in real time and applying advanced power flow simulations. In addition, continuous sensor data and advanced algorithms can automatically correct inconsistencies in the network inventory, improving flexibility, resilience and the integration of DERs, EVs and heat pumps.
Low Voltage (LV) network Grid Twins have become essential tools for effectively integrating Distributed Energy Resources (DER), Electric Vehicles (EV), and heat pumps (HVAC). This digital transformation improves the quality of the power supply, reduces operational costs, and ensures the resilience of the network in an increasingly dynamic energy environment.
However, their implementation presents significant technological challenges that must be addressed strategically.
To perform reliable simulations on an LV network, it is essential to have a complete, accurate, and up-to-date asset database. Currently, it is estimated that between 10% and 30% of asset databases contain errors such as:
Accurate LV topology (line and phase).
• Incorrect or missing meter and feeder phase assignments
• Unknown or incorrect LV cable mapping
• Misconnected electrical points
LV power flow simulation (GTA Network Digital Twin).
These errors hinder accurate power flow simulations, load planning, and the integration of new technologies.
Creating an effective Digital Twin requires a structured strategy in three fundamental phases:
1. Mapping Network Topology and Cable Routing
Use Case: LV Network Topology (Line/Phase Detection)
• Portable devices with GIS and GPS technology enable precise mapping of cable locations, connections, and phases in the field.
Field mapping and cable tracing using the GridGIS Digital Twin.
• Phase and feeder connection identification: Specific tools help identify which phase and feeder each user is connected to.
• A precise database of the LV topology facilitates network planning, DER integration, and strategic decision-making.
2. LV Network Real-time Monitoring
• Installing monitoring sensors at Transformation Centres and reading data from smart meters provides updated information on network behaviour.
• This helps detect overload points, phase imbalances, and non-technical losses.
3. Advanced Power Flow Simulation
• With a correctly mapped network and deployed sensors, accurate energy flow simulations can be performed.
• Grid Twin Ariadna (GTA)– Power Flow Simulation
At Ariadna, we believe the true revolution of Grid Twins in the electrical distribution networks lies in fully leveraging continuous sensor data and the power of advanced algorithms.
Real-time data can automatically correct inventory databases and network topology, detecting and fixing inconsistencies without sending personnel to the field. This process not only reduces costs and intervention times but also increases the reliability of the digital model.
For digitalisation to have a real impact on the power grid, distribution companies must first build an accurate and robust digital model of their physical LV networks. Only then can they:
• Accommodate a higher number of DER, EV, and HVAC.
• Ensure the safety of technical personnel.
• Ensure the quality of the supply.
• Minimise infrastructure investment costs.
Launching a complete, error-free Grid Twin, built to boost the network’s flexibility and resilience, is not only achievable but essential to tackle the challenges of the new energy landscape.
Article presented at the CIRED 2024 conference alongside Merytronic:
