The Multiphysics Digital Twin.

A Multiphysics digital twin is a virtual replica of a power grid, continuously updated with real data so it mirrors how the physical asset behaves in real time. It recreates the thermal, electrical, and mechanical condition of lines and towers, plus the electrical state of the surrounding network. Utilities use it to monitor conditions remotely, run what-if simulations, forecast future states, and receive automated alerts.

Enline combines several data types into each digital twin: asset records utilities already maintain (conductor specs, tower geometry, coordinates); weather data from on-site stations, third-party providers, or Enline's own cloud aggregation layer; satellite and LiDAR imagery; SCADA/RTU substation measurements; GIS and topographic data; and any existing line sensors. Together, these build a real-time, predictive view of your assets.

Enline delivers software, not a "no-measurement" model. Every monitoring product needs some input data - what sets Enline apart is flexibility. Our digital twin draws on whatever is available: satellite-based weather models, substation SCADA measurements, and field sensors where they exist. Instead of requiring specific hardware from specific vendors, the platform adapts to any environment or technology level.

Measurements already exist in the system - voltage and current sensors in substations, weather services, satellite imagery. Enline builds physics-based electromagnetic and thermal models that extend these point measurements along the entire line, span by span. This eliminates the need for additional field hardware, along with its installation downtime and maintenance burden.

GridSight® adapts to whatever sensor infrastructure a client already has. Where line sensors exist, their readings are fused into the model to sharpen accuracy further. Where none exist, the platform runs entirely on asset design data and weather forecasts, with no connection to operational systems required. Either way, the underlying physics model - and the outputs it produces - stay consistent.

The digital twin monitors the entire asset and the whole grid - not just the points where hardware is installed. As a physics-based model governed by electromechanical laws and industry standards, it estimates conditions down to the temperature of a single conductor, and its state estimation computes voltages and currents at every node and branch, closing the blind spots point sensors leave behind.

GridSight's alert engine ingests ambient temperature, wind speed and direction, solar irradiance, humidity, and precipitation, aligns them in time, and feeds consistent values into the thermal, mechanical, and electrical models. Alerts fall into six categories - weather, electrical, thermal, mechanical, vegetation, and wildfire - prioritised and geographically clustered. The three domains are physically linked: current drives Joule heating, heat changes resistance and sag, and that geometry shifts the surface electric field. GridSight resolves this electro-thermo-mechanical link on every cycle, so each alert reflects a physically consistent state.