Project description
Developing AI solutions for the energy sector
AI is essential for optimising, testing, and maintaining innovative energy solutions and the energy sector as a whole. However, despite its advantages, extensive testing and validation are necessary to ensure the safety and durability of these systems. This testing often requires expensive and difficult-to-access tools. The EU-funded AI-EFFECT project aims to improve access to the tools and facilities needed for developing, testing, and validating AI solutions in the energy sector. To achieve this, the project will establish a novel European testing and experimentation facility, composed of distributed, virtually connected existing European facilities. Additionally, it will develop a digital platform that provides interoperability, scalability, and flexibility for users and resources.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Keywords
Programme(s)
Funding Scheme
HORIZON-IA - HORIZON Innovation ActionsCoordinator
D01 C4E0 Dublin
Ireland
See on map
Participants (18)
4200 465 Porto
See on map
2800 Kongens Lyngby
See on map
2628 CN Delft
See on map
91120 Palaiseau
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
80686 Munchen
See on map
52062 Aachen
See on map
D6WP267 DUBLIN
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
W23 Maynooth
See on map
1363 Hovik
See on map
1010 WIEN
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
2560 275 Torres Vedras
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
4760-563 Louro Vila Nova De Famalicao
See on map
3700 Ronne
See on map
00198 Roma
See on map
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
28042 Madrid
See on map
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
28042 Madrid
See on map
10117 Berlin
See on map
7000 Fredericia
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partners (1)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
6812AR Arnhem
See on map