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.

"DECISO - DEVELOPERS OF CIRCULAR SOLUTIONS” aims to support the delivery of services to induce investments projects for developing circular economy at local and regional scale in the following regions: Hamburg. Northwest Germany, West Macedonia, Alentejo. This is in line with implementing the European Green Deal and the EU circular economy action plan. DECISO will accompany the actions aiming to provide assistance for promoters in the development of financial schemes/programs for projects on Circular Economy, based on the concept of Circular Economy Ecosystem (CEE), which implies mobilizing local stakeholders and, when necessary, citizens, and scaling up the results from the local, to the national and European levels. The CEE approach will make it possible to deal with economic, organizational and cultural change through systemic solutions that involve all the players in the value chain of an asset and all those who can influence, even indirectly, its value. This approach also allows reducing risks for investors, because ecosystems with all their key factors, including geographic location, cultural factors and institutional support, actively help an innovation become successful. Since the paradigm of the Circular Economy Ecosystems can be declined in different ways, based on the objective of the initiative, the local context, the type of actors and the sector, the DECISO approach will be implemented in different local contexts and topics in order to produce guidelines that can facilitate the replicability of the initiatives put in place considering all the technical, economic, legislative, and social factors that can determine the success or failure of the initiatives.

It is evident that the process of green transition reshapes national, regional, and local economic landscapes, and triggers change in ecosystems of various industries, thereby highlighting the urgent need to plan efficient and fair strategies to minimise the costs of job destruction and maximise the benefits of job creation in a socially fair way and a geographically equal way, in the wider patterns of reskilling. ISABEL's main objective is to provide a threefold solution to the aforementioned problem related to JCD with the use of new technologies such as AI and Large Language Models (LLM) that will 1) enrich our understanding of the socially and geographically uneven implications of this process across Europe, 2) broaden our knowledge on the factors underlying this process, and 3) highlight pathways of minimising the effects of job destruction and maximising the benefits of job creation, in a socially and spatially fair way. The latter include upskilling and reskilling of workers and the reallocation of labour, based on existing and forecasted skills shortages, using AI technologies to support these tasks. To achieve its main goal, ISABEL will examine the above elements at 3 different levels: i) the aggregate European level, among the EU, UK and Serbian Nomenclature of Territorial Units for Statistics 2 regions (NUTS2), using secondary data, ii) at 6 countries of focus -Denmark, Greece, Poland, UK, Serbia, Spain, collecting and analysing primary data, and iii) Living Labs focusing on 6 regions with diverse socio-economic features.

Artificial intelligence (AI) has lately proved to be a coin with two sides. On the one hand, it can be leveraged as a powerful defensive mechanism to improve system preparedness and response against cyber incidents and attacks, and on the other hand, it can be a formidable weapon attackers can use to damage, compromise or manipulate systems. AI4CYBER ambitions to provide an Ecosystem Framework of next-generation trustworthy cybersecurity services that leverage AI and Big Data technologies to support system developers and operators in effectively managing robustness, resilience, and dynamic response against advanced and AI-powered cyberattacks. The project will deliver a new breed of AI-driven software robustness and security testing services that significantly facilitates the testing experts work, through smarter flaw identification and code fixing automation. Moreover, the project will provide cybersecurity services for comprehension, detection and analysis of AI-powered attacks to prepare the critical systems to be resilient against them. Incident response support by AI4CYBER will offload security operators from complex and tedious tasks offering them mechanisms to optimize the orchestration of the most appropriate combination of security protections, and continuously learn from system status and defences’ efficiency. The AI4CYBER framework will ensure fundamental rights and values-based AI technology in its services, through the integration of demonstrable explainability, fairness and technology robustness (security) capabilities in the AI4CYBER components. The ecosystem will be validated in three scenarios: i) Detection and Mitigation of AI-powered Attacks against the Energy Sector, ii) Robustness and autonomous adaptation of Banking applications to face AI-powered attacks and iii) Resilient hospital services against advanced and AI-powered cyber-physical attacks.

The EVOSST project aims to improve the efficiency and understanding of social services within the European Union, aligning with the European Pillar of Social Rights and the EU's long-term budget for social inclusion and cohesion. The project focuses on developing advanced models for a comprehensive life-course impact assessment, providing insights into the long-term effects of social services, and covering healthcare, childcare, long-term care, education, and inclusion. This aligns with the EU's ambition for sustainable development and inclusive growth, moving towards a 'beyond GDP perspective'. The integration of well-being metrics reflects the EU's emphasis on improving the quality of life, including health and education, and enhancing societal well-being and social cohesion, along with the development of an integrated policy framework for social services echoes the EU's strategic direction for streamlined and effective social service delivery. EVOSST's integration of technological impact and digital technology in social services is an applied vision aligning with the European Commission's Digital Education Action Plan (2021-2027). The project applies this directive to the broader realm of social services, utilizing technologies to enhance service delivery, assessment, and user experience. The project's ambition is not only to enhance the effectiveness of social services but also to revolutionize the way their impacts are measured and understood, informing more effective policies and practices.