AlgoTrading: ENGIE’s Internal AI Engine Powering the Energy Transition

Developed by ENGIE’s algorithmic trading teams, AlgoTrading leverages advanced AI and real-time data to orchestrate renewable generation and battery storage. By transforming complex market signals into instant decisions, this internal project plays a key role in ensuring stable, competitive, and decarbonized electricity across Europe. 

Ioannis Boukas, Head of Algorithmic Trading at ENGIE tells us more.

Could you briefly introduce yourself?

I lead the development of automated, data-driven trading strategies for short-term power markets. My background is rooted in a PhD in Machine Learning with a specialization in energy storage applications.

In one sentence, what problem are you trying to solve? How would you explain your project to someone unfamiliar with your topic?

We maximize the value and efficiency of green energy by automatically predicting market prices and instantly directing renewable power and battery storage to where it is most needed. Think of it as a highly intelligent air traffic control system for electricity: our algorithms ensure that clean energy—like wind and solar—is stored when abundant and released to the grid precisely when demand peaks, completely in real time.

Who are your clients, and who are the users of your solution?

The direct users of our automated frameworks are our internal short-term manual trading desks, analysts, and quants who monitor and co-pilot these strategies.

Ultimately, the broader beneficiaries are B2B and B2C energy consumers across Europe who rely on ENGIE for stable, 24/7 decarbonized electricity, as well as the grid operators who require our flexibility to balance the energy network.

What benefits does your solution deliver?

Our solution delivers the operational scale and precision necessary to manage massive, complex portfolios profitably. We recently achieved full automation of a 2.5 GW renewable energy portfolio in France and successfully scaled our operations to manage over 500MW of Battery Energy Storage Systems (BESS) across Central Western Europe.

This level of automation optimizes our P&L and minimizes the curtailment of green energy. This proactive approach directly supports grid stability and reduces carbon emissions by ensuring clean power outcompetes fossil alternatives.

What will you be showcasing at the ENGIE booth at VivaTech? What key message would you like visitors to take away after meeting you?

I will be showcasing our journey from raw market signals to live algorithms—specifically how we optimize BESS and Renewable Energy portfolios.

The key takeaway for visitors should be that the transition to 100% renewable energy is fundamentally a data and automation challenge. Without advanced algorithms managing the volatility of wind, solar, and batteries, the green transition simply cannot scale.

This year’s VivaTech theme is “AI: Impact, not illusion.” What role does AI already play in your solution, and how do you see it evolving in the future?

AI is fundamentally embedded across every single step of our operational lifecycle. It is not an illusion or a simple add-on; we utilize AI systematically from the ground up—from accelerating software development and automating code documentation, to designing our core algorithmic trading strategies and driving real-time operational monitoring of our assets.

Moving forward, we see this evolving toward even more integrated, autonomous multi-agent frameworks that can dynamically adapt trading logic and process complex market intelligence end-to-end with minimal latency.

What is your next major challenge in the short or medium term?

The immediate challenge is continuously scaling our algorithmic framework to handle an even larger mix of hybrid assets across different European markets, ensuring our underlying infrastructure and pipelines remain robust and operate with minimal latency. We are also highly focused on refining our mixed algo-manual trading strategies, finding the perfect synergy between human trader intuition and high-speed automated execution.

If your innovation fully achieves its goal, what will have changed in the world in five to ten years?

In five to ten years, the volatility and unpredictability currently associated with renewable energy will be completely smoothed out by intelligent storage and algorithmic dispatch. Power grids will run effortlessly on a foundation of wind, solar, and battery assets, delivering 24/7 carbon-free electricity that is both highly reliable and economically optimized, effectively making fossil-fuel baseload generation obsolete.