End User
SWW
Description
The AI-based Grid Topology Identification service provides automated detection and validation of electrical connectivity relationships within distribution networks by analysing correlations in measurement data. By reconstructing the most likely topology from operational data, the service improves digital grid model accuracy and enhances the reliability of state estimation, load flow simulations, and congestion management tools.
Core Capabilities
Monitoring & Anomaly Detection
Predictive & Prescriptive Analytics
Business Need
Documented network topology in asset management systems frequently does not reflect the real operational configuration due to switching changes, undocumented modifications, and incomplete records. Topology discrepancies reduce the accuracy of grid analysis tools and can lead to incorrect flexibility dispatch. The service continuously monitors for connectivity changes and alerts operators to discrepancies requiring verification.
Key Performance Indicators
Topology reconstruction accuracy against known ground-truth networks
Edge-identification precision and recall
Phase-identification accuracy in LV networks
Change detection success rate following simulated switching events
Data Provided
Node-to-node connectivity relationships, feeder assignments, and phase identification results
Confidence scores per inferred connection and discrepancy alerts vs. existing network model
Outputs in formats compatible with common power-system modelling tools
Inputs: smart meter time-series, feeder monitoring, substation measurements, voltage, current, power flows
TEF
TEF DSO