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| Funder | European Commission |
|---|---|
| Recipient Organization | Epri Europe Dac |
| Country | Ireland |
| Start Date | Oct 01, 2024 |
| End Date | Sep 30, 2027 |
| Duration | 1,094 days |
| Number of Grantees | 20 |
| Roles | Participant; Third Party; Coordinator; Associated Partner |
| Data Source | European Commission |
| Grant ID | 101172952 |
AI-EFFECT will establish a European Testing Experimentation Facility (TEF) for developing, testing, and validating AI applications in the energy sector. It will be distributed across nodes, virtually connecting existing European facilities.
The solution includes a digital platform leveraging European building blocks for interoperability, flexibility, and scalability.
AI-EFFECT aims to be a central hub for testing energy sector AI algorithms, fostering collaboration across utilities, industry, academia, and regulatory authorities.
Resilience is ensured through a decentralized design, aligning with the EU Energy Data Spaces framework.The project involves developing 4 use cases/nodes addressing key energy challenges, focusing on district heating, transmission congestion management, DERs integration, and energy communities.
The framework involves utilities proposing challenges, vendors developing algorithms, and researchers contributing solutions. Each use case has evaluation criteria, baselines, and benchmarks.
AI certification procedures, including interpretability and verification, will be implemented, and the evaluation process will be automated.Benchmarks and certifications are publicly available, encouraging open-source contributions.
The project breaks sector barriers, leveraging existing infrastructures and technologies for cross-sectoral collaboration.
The platform enforces policies for data quality, integrity, and privacy, promoting controlled data sharing and collaboration. Secure APIs ensure controlled interactions, including risk and security assessments.
The consortium explores certification, standardization, and quality requirements in line with the EU AI Act.Governance and business models for the enduring AI-EFFECT will be examined, considering the EU AI Act.
The consortium aims to make AI-EFFECT a sustained business beyond initial funding, seeking input from members, other TEFs, and regulatory authorities for the preferred model.
Rheinisch-Westfaelische Technische Hochschule Aachen; Edistribucion Redes Digitales Sl; Fraunhofer Gesellschaft Zur Forderung Der Angewandten Forschung Ev; Inesc Tec - Instituto de Engenhariade Sistemas E Computadores, Tecnologia E Ciencia; Cooperative Electrica Do Vale Deste Crl; Ikim Ltd; Bornholms Varme As; Enel Iberia Srl; Watt-Is Sa; National University of Ireland Maynooth; Dnv As; Epri Europe Dac; Center Danmark Drift Aps; Hertie School Gemmeinnutzige Gmbh; Danmarks Tekniske Universitet; Tennet Tso Bv; Institut de Recherche Technologique System X; Enel Grids S.R.L.; Enliteai Gmbh; Technische Universiteit Delft
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