AI-EFFECT powering the future of energy with smarter testing

Amid rapid digital transformation, the integration of AI into critical infrastructure offers the potential for greater efficiency, resilience, and sustainability, particularly within the energy sector. The EU’s energy system digitalisation action plan highlights the pivotal role of data and AI in shaping the future of energy. 

However, achieving this vision is not without obstacles. Key challenges remain, including ensuring the availability of high quality data, achieving interoperability across diverse systems, and maintaining the security of AI technologies. In addition to these technical challenges, the forthcoming EU AI Act introduces new regulatory considerations related to privacy, ethics, and liability – issues that remain unresolved when it comes to the use of AI in industrial applications for critical infrastructure and system management. 

To overcome these challenges, there is an urgent need for independent and secure testing and experimentation environments that replicate real-world conditions. These environments would enable the validation of AI models in realistic settings and create opportunities for closer collaboration between researchers, industry stakeholders and Europe’s energy utilities.

The AI-EFFECT project (Artificial Intelligence Experimentation Facility for the Energy Sector) seeks to bridge a critical gap: connecting utilities, which hold vast streams of operational data and face complex challenges, with the AI industry and research communities that possess the tools and expertise to solve them. This collaboration is driven by a shared need for a consistent, standardised approach to building trustworthy AI, along with a clear framework to certify solutions based on rigorous security and risk standards established by EU law.

AI-EFFECT objectives

AI-EFFECT is built around four primary objectives that together form the foundation for advancing trustworthy AI in the European energy sector. First, it will develop a series of strategically important use cases at four European research institution nodes, each accompanied by a dedicated testing methodology.

Second, it will design and implement a modular, interoperable and scalable framework architecture that builds on existing EU initiatives such as testing and experimentation facilities, data spaces and digital innovation hubs.

Third, the project will create and validate a complete end-to-end AI-EFFECT solution, enabling seamless interaction with its demonstration nodes and associated use cases.

Finally, AI-EFFECT will establish a robust governance and business model to ensure its long-term sustainability, engaging with European and global energy stakeholders and asset owners to curate relevant use cases, training resources, and test data, while matching innovative concepts to viable datasets.

To achieve its vision, AI-EFFECT will establish a European testing and experimentation facility dedicated to AI applications in the energy sector. This facility will serve as a secure, interoperable digital platform that connects existing European computing and laboratory resources, enabling the development, testing and validation of AI solutions at every stage. Designed with decentralisation at its core, the platform will provide both direct and remote access to distributed nodes across the EU, fully aligned with the EU energy data spaces framework.

At the heart of this infrastructure are four demonstration nodes located in Denmark (for energy heat sector coupling), the Netherlands (for transmission congestion management), Portugal (for microgrids and local energy communities), and Germany (for DER integration). These nodes will act as real-world testbeds for addressing critical energy challenges. By combining real and synthetic datasets, they will enable robust and scalable testing of diverse use cases, ensuring that AI solutions can perform effectively under realistic conditions.

AI Act compliance

Building on this foundation, AI-EFFECT introduces a comprehensive methodology that integrates automated testing processes, strong data security measures, and intellectual property protection to ensure compliance with the EU AI Act. The project promotes open source algorithms and secure platforms to encourage collaboration and innovation across borders. Its framework is designed to create centres of excellence for AI in energy, each specialising in specific use cases.

Through virtual collaboration and interconnected nodes, AI-EFFECT will break down geographic and sectoral barriers, allowing expertise and innovation to flow seamlessly across Europe.

Energy utilities will play a central role by submitting data linked to specific challenges and use cases. This approach provides the industry with secure access for AI model training and solution testing through a transparent, standardised methodology.

Beyond co-developing AI and machine learning models, AI-EFFECT is driving innovation by prioritising high impact use cases and introducing several groundbreaking advancements. These include an end-to-end AI certification process with Shapley values-based interpretability for transparent decision-making, a scalable modular architecture built on the VILLAS framework and physics-informed digital twin components for data generation and augmentation.

AI-EFFECT is set to transform Europe’s energy sector by creating a secure, interoperable platform for developing and validating AI solutions. Through its distributed testing and experimentation facilities, robust testing framework, and strong collaboration with energy utilities, the project will accelerate innovation while ensuring compliance with EU regulations. 

By integrating advanced tools such as AI certification, modular architectures and digital twins, AI-EFFECT will drive smarter grids, enhance renewable energy performance, and position Europe as a global leader in digital and green technologies.

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