Renewables & Flexibility Forecasting for Distribution Operators
Rooftop solar, heat pumps and charging points have turned distribution feeders into two-way networks. Operators need to forecast local congestion and activate flexibility, but the models live in spreadsheets and the smart-meter data they need cannot leave the country.
What stands in the way
How Scrydon solves it
How this plays out
A distribution operator's problem is no longer whether the grid has enough capacity in total but whether a specific feeder will overload at 14:00 on a sunny Sunday. Answering that needs metering data at feeder resolution, weather forecasts, the current state of every switch and transformer, and the flexibility contracts available in that area, combined continuously rather than in a monthly study.
The platform's ontology models feeders, substations, connections and contracts as one graph, and the analytics layer keeps forecasts current as meter and weather data arrive. Decision intelligence turns a predicted overload into a recommended action, such as activating a specific battery or curtailing a specific generator, with the expected effect and the cost, and hands it to the operator's approval workflow.
Smart-meter data is personal data under GDPR and operationally sensitive under NIS2. Running the forecasting on the operator's own sovereign cluster keeps it inside the jurisdiction and produces the activation record the regulator expects.
- Congestion is managed with contracted flexibility instead of connection refusals, and the reasoning behind every activation is recorded for the regulator.
Prefer to write? Email hello [at] scrydon.com and we will get back to you.
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