GraphSight

Accurate renewable energy forecasts using graph-based AI

Problem

Every day, electricity traders and grid operators lose significant money due to inaccurate renewable energy forecasts, which lead to inefficiencies, imbalances, and penalties. The challenge of integrating intermittent solar energy into grids is compounded by the complexity of managing multi-site portfolios and the variability of power generation.

Solution

GraphSight addresses this challenge by delivering highly accurate day-ahead and intraday energy forecasts. Using historical data and advanced AI, their solution generates data-driven predictions without relying on complex physical models. By improving forecast precision, GraphSight helps traders optimise operations, reduce financial losses, and integrate renewable energy seamlessly into the grid.

Core technology

GraphSight leverages graph-based AI algorithms to model the relationships within multisite solar portfolios typical of electricity traders. By capturing spatial and temporal dependencies, this approach scales efficiently to handle large datasets and complex energy market scenarios, enabling precise, reliable, and scalable renewable energy forecasts.