Clean energy production needs to expand in order for Europe to achieve its net-zero emission goals of 2050. UPWIND aims at the “massive” and “rapid” upscaling of the current onshore wind turbine stock in order to address the highly challenging sustainable energy targets and mitigate climate crisis. 38GW of existing onshore wind structures will reach their end-of-life in Europe by 2025 and new wind farms typically take about 13 years from concept to operation. Upscaling existing structures is the only reliable strategy to immediately increase wind energy installations as it can double generation capacity (in MW) of existing onshore wind farms within a very short period. UPWIND aims to develop an innovative machine learning-assisted upscaling framework for existing onshore wind structures to be converted to new-age powerful ones. This will be achieved by replacing old turbines with more efficient and powerful new-age turbines, increasing the height of the existing onshore tubular steel wind turbine towers, enhancing the load-bearing capacity of the towers and by extending their operational life. The research output of UPWIND will enable decision-making for innovative repowering strategies focusing on upscaling the existing support towers to bear the new loads (increased self-weight, fatigue vibrations) caused by heightening and new turbines installation, by selecting suitable strengthening schemes. New upscaling methods and strengthening schemes will be implemented and a new digitalized decision-making framework for repowering old wind turbine towers will be developed. UPWIND will introduce a gamechanger strategy that will directly increase energy production from wind structures, taking advantage of the already used best onshore locations and existing permissions, avoiding non-economic and non-environmental friendly total tower replacements, thus significantly contributing to a fully circular net-zero future for the european energy sector.

AMBROSIA aims to provide the foundations for a multi-sensing future-proof Point of Care Unit for sepsis diagnosis offered by a CMOS compatible toolkit and enhanced by on-chip photonic neural network technology to provide an accurate and rapid diagnosis. AMBROSIA will be investing in the established ultra-small-footprint and elevated sensitivity of integrated plasmo-photonic sensors reinforced by the well-known on-chip slow-light effect and micro-transfer printed lasers and photodiodes on Si3N4, as well as the functional processing and classification portfolio of integrated photonic neural network engines, towards painting the landscape of the next-coming disruption in sensor evolution, tailoring them in System-in-Package prototype assemblies, with the sensors being cheap disposable pluggable modules that can rapidly and accurately diagnose sepsis at the bedside in clinical environments. AMBROSIA targets to demonstrate a Point of Care Unit incorporating: i) a switchable sensor area array, with each sensor area facilitating a pluggable, 8-channel label-free plasmo-photonic sensor for sepsis diagnosis with a sensitivity over 130.000nm/RIU and a Limit of Detection below 10-8 RIU for each interferometric sensor, ii) an embedded Si3N4 photonic neural network processing and classifying at the same time the data from at least 7 biomarkers with zero-power providing in the first minutes an accurate and rapid diagnosis for sepsis, iii) Micro-transfer printed lasers and photodetectors on chip that will drastically decrease costs of both the sensing and neural network modules, and render the sensor arrays disposable.

Primary prevention of cancer through behaviour changes in adolescence – a critical period in which many risk behaviours are initiated –, is a huge health and societal challenge in Europe. In alignment with this need, SUNRISE will co-create, implement and evaluate an innovative digitally-enhanced life-skills programme for primary prevention of cancer through sustainable health behaviour change in adolescents, tailored to their socio-economic, cultural and environmental diversities. SUNRISE will combine an established, evidence-based digital solution for smoking prevention, with novel intervention approaches such as peer social media campaigns, advertising literacy training, educational games, and social robot platforms, to take cancer prevention approaches for adolescents in the EU to the next level. The digitally-enhanced programme and its components will be developed through co-creation with schools-as-living-labs methods involving multiple societal actors such as educators, adolescents, parents, public health experts, and policy-makers. The programme will be implemented and evaluated at large scale across 154 schools and 7500 students in urban and rural regions of 8 European countries - Greece, Switzerland, Slovenia, Spain, Cyprus, Italy, Belgium, Romania -, including socially disadvantaged groups such as migrants and ethnic minorities. The effectiveness of both methods for achieving long-term health behaviour change, as well as the implementation strategy for solution adoption and multi-country sustainability, will be evaluated. This action is part of the Cancer Mission cluster of projects on “Prevention & early detection (behavioural change).

The stability and security of the traditional electrical power systems is largely based on the inherent properties of synchronous generators (SGs). Such properties are: the grid-forming capability, the inertia, the damping of transients, and the provision of large currents during faults. The growing penetration of converter-interfaced (thus inertia-less) Distributed Renewable Energy Sources (DRES) will eventually replace dispatchable SGs and increase power volatility, causing large frequency deviations and voltage regulation problems. The increase of SG spinning reserves, the grid reinforcement and the use of central electric energy storage systems are some solutions proposed to tackle this problem. However, due to their centralized approach and high cost, these actions can be undertaken only centrally by TSOs and DSOs. By adopting a unified bottom-up approach, EASY-RES will develop novel control algorithms for all converter-interfaced DRES, to enable them to operate similarly to conventional SGs, providing to the grid inertia, damping of transients, reactive power, fault ride through and fault-clearing capabilities, and adaptable response to primary and secondary frequency control. These new functionalities will be transparent to all grid voltage levels. The EASY-RES approach is based on the distribution network segmentation into small Individual Control Areas, where the DRES and properly sized storage systems will be optimally coordinated via suitably designed ICT infrastructure to provide Ancillary Services (AS) such as inertial response, reactive power support, power smoothing, and contribution to fault-clearing in a bottom-up approach: prosumers and independent RES producers to DSOs, and DSOs to TSOs. By evaluating the costs and benefits of the developed functionalities, viable business models will be developed for the aforementioned stakeholders. Finally, modifications to the existing grid codes will be suggested for the implementation of the developed AS.