If you are a Titanium Dioxide manufacturer dealing with rigid production schedules and high fossil fuel costs — this project developed a Case-Specific Systemic Integrated Solution that allows your plant to adapt its load to volatile renewable energy supply.
AI-Driven Energy Flexibility Tools for Heavy Industrial Plants to Use Renewable Power
Imagine a giant factory that usually needs a steady stream of power, like a light switch that can't be turned off. This project builds a smart brain for the factory that lets it slow down or speed up production based on when wind and solar power are cheapest and most available. It's like a smart thermostat for heavy industry, making sure the plant doesn't crash while switching to green energy.
What needed solving
Energy-intensive industries cannot adjust their production speeds to match the fluctuating supply of renewable energy. This forces them to rely on expensive, carbon-heavy fossil fuels to maintain stability.
What was built
A Generic Systemic Flexibility Solution (GSFS) consisting of AI digital twins, a Flexibility Intelligence Toolbox, and tracking tools like Digital Flexibility Passports.
Who needs this
Who can put this to work
If you are a Copper manufacturer dealing with the inability to integrate variable wind or solar power into heavy smelting — this project developed a Flexibility Intelligence Toolbox that orchestrates operations in real time to lower carbon dependency.
If you are an energy-intensive plant operator dealing with unpredictable energy prices and strict decarbonization targets — this project developed Digital Flexibility Passports to track and prove your plant's ability to shift energy loads.
Quick answers
How much does the solution cost to implement?
Based on available project data, specific pricing or implementation costs are not provided.
Is this tested at an industrial scale?
Yes, the project demonstrates its solutions in two large-scale pilots: a Titanium Dioxide manufacturer (KRONOS) and a Copper manufacturer (HALCOR).
How is the intellectual property or licensing handled?
Based on available project data, specific IP or licensing terms are not mentioned, though a Replication and Exploitation Funnel is planned to drive uptake.
How does this integrate with existing plant software?
The system uses a cyber-physical environment that integrates AI-driven digital twins and advanced control to orchestrate operations in real time.
What is the timeline for deployment?
The project runs from 2026-06-01 to 2030-05-31, indicating that full validation will occur by 2030.
Who built it
The consortium is heavily weighted toward industrial application, with a 44% industry ratio consisting of 7 industrial partners and 2 SMEs. This balance, supported by 6 universities and 1 research center across 6 countries, suggests a strong focus on practical deployment rather than pure theory, specifically targeting the metals and chemicals sectors.
Contact POLYTECHNEIO KRITIS in Greece for technical details on the GSFS.
Talk to the team behind this work.
Contact SciTransfer to identify similar energy-flexibility tools for your specific industrial process.