Project description
Computing solutions for a sustainable energy future
To meet the EU’s climate goals, greenhouse gas emissions must decrease by 55 % by 2030, with half of all electricity coming from renewable sources. However, as grids rapidly decarbonise new issues are emerging. Managing grid reliability and adapting old power plants to sustainable uses is challenging. Also, future grids will require enormous amounts of data processing. The GRAVITEQA project addresses these challenges by combining gravitational storage, quantum computing and AI-driven analytics. Its approach includes nine innovations, such as converting coal plants into energy storage sites, optimising electric vehicle charging at ports and enhancing grid flexibility. These developments create a stable, eco-friendly energy system ready for the demands of tomorrow.
Objective
The clean energy transition requires at least a 55% reduction in GHG emissions (from 1990 levels) by 2030, according to the ‘Fit for 55’ package. Thus, electricity grids will be called upon to operate in an overall context of 50% electricity production from RES of any scale by 2030. Thus, several challenges will become even more apparent in the following years: (i) reliability issues in electricity grids due to rapid decarbonization, (ii) lack of circularity in conventional power plant’s decommissioning process, (iii) operational issues in sector-coupled systems under mass electrification scenarios, (iv) significant computation and data processing efforts are required to manage the future grid. GRAVITEQA highlights the synergetic benefits of gravitational storage, Quantum Computing (QC) and Quantum Inspired Computing (QIC), and data-driven, trustworthy AI-based analytics services. GRAVITEQA develops and validates 9 components/methodologies up to a TRL 4: (i) QC and QIC for the Facility Location Allocation and Load-side assets management problems, (ii) a generic and holistic methodology to find the optimal energy storage technology or mix of them, to transform a coal power plant and mine into a long duration energy storage plant, (iii) repurposing of available assets case study capable of providing long-term storage and enhancing recyclability of a under-decommissioning thermal power plant and an abandoned coal plant, (iv) conformal prediction for robust energy demand of cold ironing, (v) optimal charging of cold ironing and EVs respecting grid constraints for reliable green port operation, (vi) seaport electrification strategy for seaports: analysis and scenarios planning, (vii) fast nodal flexibility region estimation algorithm for 3-phase grids unlocking the flexibility services procurement from distributed RES, (viii) end-to-end trustworthy learning for non-convex optimization problems, and (ix) a reference design for edge inference in smart grid applications.
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. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology environmental engineering energy and fuels renewable energy
- engineering and technology environmental engineering energy and fuels fossil energy coal
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering computer hardware quantum computers
- natural sciences computer and information sciences data science data processing
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.5 - Climate, Energy and Mobility
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-RIA - HORIZON Research and Innovation Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-CL5-2024-D2-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
105 61 ATHINA
Greece
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.