CHRONOPIA evolves Bamboo Platform towards a hybrid operational intelligence model, combining the speed of machine learning with the robustness of deterministic mathematical optimisation. The goal is to manage thousands of assets automatically and safely, with response times under one minute. The project is built on four pillars:

• Optimiser acceleration: AI models propose starting solutions (warm-start) so the optimiser converges faster, with a fallback that always guarantees a valid solution.
• Interpretable physical modelling: ​ Physics-Informed Machine Learning (SINDy) uncovers the real thermal dynamics of each asset to accurately predict the rebound effect after a flexibility activation.
• Scaling from “day 0”: transfer learning lets new assets be operated without waiting months for historical data, building on knowledge from similar assets already managed.
• Data governance: a secure, traceable data infrastructure, aligned with ISO 27001 and the EU AI Act, that allows models to be trained without compromising client confidentiality.

The solution is validated step by step: first in simulation, then in parallel with live operations (shadow mode), and finally in production on the Bamboo Energy platform.