Prompted by the need to comply with environmental and societal concerns, Electrical Power and Energy Systems are undergoing an unprecedented transformation, demanding urgent upgrades to make them more reliable, resilient and secure. Modernization of current grids will greatly reduce the frequency and duration of power blackouts, diminish the impact of disruptive events and restore service faster when outages occur, creating broad benefits to society and economy. eFORT approach will enable the further upgrading of the energy grid without affecting the security of supply and increasing their reliability and resiliency against extreme weather events, man-made hazards and equipment failures. eFORT addresses this complex challenge by gathering a consortium of 24 partners, from 10 EU countries, that provides the needed expertise. The project will put in place a set of solutions at the cyber and physical layers for detecting, preventing and mitigating vulnerabilities and threats. Among them, an interoperable Intelligent Platform will set a common foundation for grid characterization and vulnerability overseeing, as well as gather information from smart grid components and apply heavy-duty algorithms, whereas Asset Management developments will strengthen grid infrastructure robustness, which will be empowered by the addressed Digital Technologies. All these elements will be validated in relevant environments coming from 4 demo cases covering the whole grid value chain: (i) a transmission network (The Netherlands); (ii) a remote distribution grid (Italy); (iii) a digital substation in Ukraine; and (iv) a micro-grid in Spain. Moreover, eFORT relies on several horizontal actions aiming at empowering EPES players by establishing a common regulatory and standardisation framework, performing technical and cost-benefit analysis, and evaluating new related business models and replication potential, in the pathway towards a more sustainable energy system.

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.

In order to unlock the full potential of Europe’s offshore resources, network infrastructure is urgently required, linking off-shore wind parks and on-shore grids in different countries. HVDC technology is envisaged but the deployment of meshed HVDC offshore grids is currently hindered by the high cost of converter technology, lack of experience with protection systems and fault clearance components and immature international regulations and financial instruments. PROMOTioN will overcome these barriers by development and demonstration of three key technologies, a regulatory and financial framework and an offshore grid deployment plan for 2020 and beyond. A first key technology is presented by Diode Rectifier offshore converter. This concept is ground breaking as it challenges the need for complex, bulky and expensive converters, reducing significantly investment and maintenance cost and increasing availability. A fully rated compact diode rectifier converter will be connected to an existing wind farm. The second key technology is an HVDC grid protection system which will be developed and demonstrated utilising multi-vendor methods within the full scale Multi-Terminal Test Environment. The multi-vendor approach will allow DC grid protection to become a “plug-and-play” solution. The third technology pathway will first time demonstrate performance of existing HVDC circuit breaker prototypes to provide confidence and demonstrate technology readiness of this crucial network component. The additional pathway will develop the international regulatory and financial framework, essential for funding, deployment and operation of meshed offshore HVDC grids. With 35 partners PROMOTioN is ambitious in its scope and advances crucial HVDC grid technologies from medium to high TRL. Consortium includes all major HVDC and wind turbine manufacturers, TSO’s linked to the North Sea, offshore wind developers, leading academia and consulting companies.