REEFLEX aims to generate niches of opportunities for new cross-sector energy services provided by SMEs and start-ups in demand side flexibility markets and to increase participation of energy consumers in demand side flexibility markets. The project develops a central interoperability platform and a catalogue of services with the capability of maximising distributed energy resources' flexibility while respecting the different end user profiles and needs along with the physical limitations of existing infrastructures. Additionally, the generation of a common operation market model together with AI-driven intelligence services and automation systems, enabled through the utilization of distributed ledger technologies for enhancing transparency and trust, will reduce market entry barriers and costs and achieve a higher participation from energy consumers. They will benefit from new revenues obtained through data and flexibility transactions, while enjoying innovative, personalized, data (intelligence)-driven services for smart, human-centric control of their assets in the frame of demand response or self-consumption. REEFLEX solutions, they will be demonstrated and cross-tested in 4 main demonstrators (Spain, Greece, Switzerland, Bulgaria) with different characteristics, allowing evaluation of their impact under alternative scenarios and integrating a variety of sectors, such as residential buildings, mobility, commercial establishments, industrial sites or data centres, among others. In addition, the services catalogue will be further replicated in three additional replicators across Europe to achieve wider coverage (Turkey, Portugal, Denmark) and adaptation, ending-up in a total of 7 countries for the whole project execution. These cross-tested demonstrators and additional replication campaigns are structured around 8 different use cases that cover a comprehensive set of consumer groups to participate in up to 12 demand side flexibility services.

BIO4SELF aims at fully biobased self-reinforced polymer composites (SRPC). To produce the SRPCs two polylactic acid (PLA) grades are required: a low melting temperature (Tm) one to form the matrix and an ultra high stiffness and high Tm one to form the reinforcing fibres. To reach unprecedented stiffness in the reinforcing PLA fibres, we will combine PLA with bio-LCP (liquid crystalline polymer) for nanofibril formation. Further, we will increase the temperature resistance of PLA and improve its durability. This way, BIO4SELF will exploit recent progress in PLA fibre technology. We will add inherent self-functionalization via photocatalytic fibres (self-cleaning properties), tailored microcapsules (self-healing properties) and deformation detecting fibres (self-sensing). Prototype composite parts for luggage, automotive and home appliances will be demonstrators to illustrate the much broader range of industrial applications, e.g. furniture, construction and sports goods. Our developments will enable to use bi

VERGE will tackle evolution of edge computing from three perspectives: “Edge for AI”, “AI for Edge” and security, privacy and trustworthiness of AI for Edge. “Edge for AI” defines a flexible, modular and converged Edge platform that is ready to support distributed AI at the edge. This is achieved by unifying lifecycle management and closed-loop automation for cloud-native applications, MEC and network services, while fully exploiting multi-core and multi-accelerator capabilities for ultra-high computational performance. “AI for Edge” enables dynamic function placement by managing and orchestrating the underlying physical, network, and compute resources. Application-specific network and computational KPIs will be assured in an efficient and collision-free manner, taking Edge resource constraints in to account. Security, privacy and trustworthiness of AI for Edge are addressed to ensure security of the AI-based models against adversarial attacks, privacy of data and models, and transparency in training and execution by providing explanations for model decisions improving trust in models. VERGE will verify the three perspectives through delivery of 7 demonstrations across two use cases - XR-driven Edge-enabled industrial B5G applications across two separate Arçelik sites in Turkey, and Edge-assisted Autonomous Tram operation in Florence. VERGE will disseminate results to academia, industry and the wider stakeholder community through liaisons and contributions to relevant standardization bodies and open sources, a series of demonstrations showing progression through TRLs and by creating an open dataspace for enabling public access to the datasets generated by the project.

The demand for electrical energy increases at a steady pace worldwide due to the growing and emerging applications such as server/telecom farms, 5G base station, more-electric aircrafts, consumer electronics, robotics, and electric vehicles. The volume and efficiency of the power converters utilized in these systems play a critical role for the fulfillment of this growth. Higher efficiency translates into more capacity utilization and less cooling efforts, whereas low volume and weight usually reduces the cost of the electronic components. Both of these aspects heavily depend on the innovations on the power topologies, control algorithms, magnetics, thermal substrates, and particularly power semiconductor switches. The power converter topologies in the literature have been invented to overcome or mitigate the large reverse recovery and output charge of Si power devices, while magnetics are optimized for switching frequencies that are achievable with Si power devices. However, the maximum efficiency and power density of Si based converters have already reached to its theoretical limit through innovations on the control and converter topologies. Recently, the adoption of the wide band-gap semiconductors has escalated the expectations from power electronics significantly, and initiated the transformation of the power architecture through new topologies and control innovations, while bringing new challenges in the high frequency domain. This research proposal is intended to innovate, design, and implement a new front-end PFC converter switched at >400 kHz to achieve best in-class efficiency and power density with targets of more than 98.5% peak efficiency and 85W/in3 enclosed power density at 3.7kW output power. The know-how and framework will then be engineered to meet certain industrial specs of various applications including the pre-regulator stage of server/telecom supplies, on-board chargers, industrial drives.

R-PODID (Reliable Powerdown for Industrial Drives) aims to develop an automated, cloudless, short-term fault-prediction for electric drives, power modules, and power devices, that can be integrated into power converters. Thereby, electrical and mechanical faults of machines and of the power converters driving them will become predictable within a limited prediction horizon of 12-24h. This will enable a power-saving shutdown of a larger number of production machines during idle times, because a looming failure during the next power-on cycle can be reliably foreseen. It will also enable reliable mitigation of dangerous faults in applications using modern power-devices like silicon-carbide (SiC) and III/V-semiconductor devices like gallium-nitride (GaN).