Existing power grids often operate below their maximum potential due to conservative static line ratings that don't account for real-time weather conditions. Building new transmission lines to meet growing electricity demand and integrate renewable energy sources is a slow and expensive process, often taking a decade or more. This lack of transmission capacity leads to bottlenecks, increased power curtailment, and higher energy costs.

Grid Raven offers a sensorless Dynamic Line Rating (DLR) system that optimizes the capacity of existing overhead power lines by utilizing hyper-local weather predictions. The software-based solution, named Claw, leverages machine learning and advanced data sources like satellite imagery and LiDAR to forecast weather conditions with meter-scale precision. By accurately predicting wind speed, ambient temperature, and solar irradiation along each span of a power line, Grid Raven enables grid operators to safely increase transmission capacity by up to 30% without the need for additional hardware. This allows for faster connections of new generation sources, reduced curtailment of renewable energy, and lower electricity prices.

Sensorless DLR system that requires no additional hardware

Hyper-local weather predictions with meter-scale precision

Machine learning models trained on tens of thousands of weather stations

Integration of satellite imagery and LiDAR data for detailed landscape analysis

Span-level monitoring to identify critical sections and ensure safety

Forecast horizon of up to 10 days for operational planning

API integration with SCADA/EMS systems

Capability to cover all overhead lines from 30 kV upwards

Grid Raven targets grid operators, power producers, and energy consumers seeking to maximize the efficiency of existing power grids, accelerate the integration of renewable energy sources, and reduce energy costs.