KOPR
A living AI twin of an entire electricity grid — every consumer, producer and asset, modelled and forecast in near real time. Built on GreyCat and in production for Creos Luxembourg.
Install GreyCat free Open KOPR ↗
The problem
A distribution grid is structure, 15-minute meter streams and geography all at once — spread across GIS, ERP, metering infrastructure and real-time sensors that never quite line up. Planning, what-if studies and power-flow at national scale mean heavy ETL and overnight batches, so the answers often arrive too late to act on.
How GreyCat solves it
KOPR aggregates, visualises, analyses and learns from data across every source — GIS, ERP, smart meters and live sensors — in one engine, then turns it into real-time monitoring, simulation and forecasts.
One unified model
Assets, their time-series and their location — from GIS, ERP and metering — live in one graph and one transaction.
Forecasts for every asset
ML models forecast each consumer and producer across the whole grid, to up to 95% accuracy.
Instant power-flow
Compute power flow at any point in time, in any real or simulated scenario.
Runs on-prem
One binary on your own hardware — no cloud, no third-party stack.
KOPR runs in production for Creos Luxembourg on GreyCat. Open KOPR ↗ · See the reference ↗
People tend to take electric energy for granted. But managing its effective distribution is, in fact, a constant technical challenge, especially when the grid is experiencing more and more turbulences in terms of production (solar panels, wind turbines) and consumption (heat pumps, electric vehicles). KOPR allows us to manage our electricity grid more efficiently by integrating data from various systems. It enables a better understanding of the behaviour of the electricity grid and ultimately enables precise live monitoring, simulations, and prediction capabilities.
