The scope of AI4REALNET covers the perspective of AI-based solutions addressing critical systems (electricity, railway, and air traffic management) modelled by networks that can be simulated, and are traditionally operated by humans, and where AI systems complement and augment human abilities. It has two main strategic goals: 1) to develop the next generation of decision-making methods powered by supervised and reinforcement learning, which aim at trustworthiness in AI-assisted human control with augmented cognition, hybrid human-AI co-learning and autonomous AI, with the resilience, safety, and security of critical infrastructures as core requirements, and 2) to boost the development and validation of novel AI algorithms, by the consortium and AI community, through existing open-source digital environments capable of emulating realistic scenarios of physical systems operation and human decision-making. The core elements are: a) AI algorithms mainly composed by supervised and reinforcement learning, unifying the benefits of existing heuristics, physical modelling of these complex systems and learning methods, as well as, a set of complementary techniques to enhance transparency, safety, explainability and human acceptance; b) human-in-the-loop decision making for co-learning between AI and humans, considering integration of model uncertainty, human cognitive load and trust; c) autonomous AI systems relying on human supervision, embedded with human domain knowledge and safety rules. The AI4REALNET framework will be validated in 6 uses cases driven by industry requirements, across 3 network infrastructures with common properties. The use cases are focused on critical challenges and tasks of network operators, considering strategic long-term goals, such as decarbonisation, digitalisation, and resilience to disturbances, and are formulated in a unified sequential decision problem where many AI and non-AI algorithms can be applied and benchmarked.

To unlock multi-vendor HVDC grids and foster the transition of the European energy sector at large scale, InterOPERA proposes a coordinated approach between a diverse, high-level group of industries at the forefront of RES development and grid management. 4 HVDC vendors, 8 TSOs, 2 wind turbine vendors and 3 wind park developers bring their industrial knowledge and practical abilities to make future HVDC systems mutually compatible and interoperable by design, and to improve the grid forming capabilities of offshore and onshore converters. Foreseen and planned HVDC projects will be analysed to define a demonstrator case study. The resulting system-level design will be usable as a guidance to coordinate offshore network planning. This new way of framing the European grid architecture and topology will ensure forward compatibility for future seamless system expansion. Interoperability of control and protection systems will be de-risked through the execution of all necessary activities concurring to the implementation of a real-time physical demonstrator. Concrete results will be delivered through this practical work: detailed functional specifications for each subsystem, standardised models, simulation platforms and interaction study processes, multi-vendor cooperation agreements. Those frameworks will be generalised into operational and strategic tools available to all European stakeholders for the development of multi-terminal HVDC grids that will enhance offshore wind development and integration. Solutions for multi-vendor project procurement, compliant with existing and future regulations, standards and laws, integrating the technical specifications and interoperability assessment tender stages, will be provided to pave the way to the first real-life projects in Europe. External stakeholders will be involved in two-way consultation workshops to maximise the uptake of InterOPERA’s key exploitable results. Recommendations to grid codes and standards will be issued.