In recent years crises and disasters (Eyjafjallajökull and Deepwater Horizon 2010, Fukushima Daiichi 2011) have made it obvious that a more resilient approach to preparing for and dealing with such events is needed. DARWIN will improve response to expected and unexpected crises affecting critical infrastructures and social structures. It addresses the management of both man-made events (e.g. cyber-attacks) and natural events (e.g. earthquakes). The main objective is the development of European resilience management guidelines. These will improve the ability of stakeholders to anticipate, monitor, respond, adapt, learn and evolve, to operate efficiently in the face of crises. Guidelines will be presented in formats for easy usage and maintenance to avoid them being dust-collectors on a shelf. To enable dynamic, user-friendly guidelines the project will adapt innovative tools (e.g. serious gaming, training packages), test and validate the guidelines, and establish knowledge about how organisations can implement guidelines to improve resilience. A multidisciplinary approach is applied, involving experts in the field of resilience, crisis and risk management, social media and service providers in the Air Traffic Management and health care domains. To ensure transnational, cross-sector applicability, long-term relevance and uptake of project results, a Community of Crisis and Resilience Practitioners (CoCRP) will be established, including stakeholders and end-users from other domains and critical infrastructures and resilience experts. The CoCRP will be involved in an iterative evaluation process to provide feedback on the guidelines. The target beneficiaries of DARWIN are crisis management actors and stakeholders responsible for public safety, such as critical infrastructures and service providers, which might be affected by a crisis, as well as the public and media. The project duration will be 36 months, requesting financing of €4.9M.

Renewable Energy Sources Power FOrecasting and SyNchronisation for Smart GriD NEtworks MaNagemenT. Renewable energy sources (RES) play a major role to the EU’s aspiration to transform to a climate-neutral economy. Their integration into the power grid is pivotal to the green transition and to the decarbonisation of the energy sector. However, as the most commonly used RES (solar, wind and hydropower) are also weather-dependent, their power generation capacity varies according to the local microclimatic conditions. This power production variability makes RES difficult to integrate into the power grid and to provide seamless, stable and secure amounts of power. On the other hand, power demand also affects the power grid operation, since there must always be a supply/demand balance in the power grid. Grid power imbalances can cause frequency fluctuations and other unwanted transient phenomena, which can compromise grid stability and operation. For that matter, advanced grid monitoring techniques have been developed, employing phasor measurement units (PMUs) to measure the electrical signals in a precise and synchronised way, based on a reliable timing reference. Yet, currently, no Galileo-based applications on PMU timing exist. In the above framework, RESPONDENT comes to address the challenges of RES power generation forecasting, demand forecasting and smart power grid monitoring and supply/demand balancing. An AI/ML RES power generation forecasting algorithm is proposed, exploiting both Copernicus EO and site-specific weather data, along with renewable energy power conversion models. Furthermore, an AI/ML – multiphysics model for power demand of certain communities is also developed. Lastly, RESPONDENT will build a Galileo-enabled PMU and develop a monitoring module, in order to test and verify the advantages offered from the Galileo timing and synchronization services in smart grid monitoring, power balancing and overall operation.

The current global climate crisis and ongoing shift towards autonomous transport necessitate sustainable and passenger-centric public transport solutions. The goal of OptiPEx is to enhance of sense of comfort and safety of the passengers as well as the security and ease of travelling by co-creating ethical and passenger-aware public transport services together with specific target user groups, such as wheelchair users, passengers with large objects, fragile passengers with limited mobility, tourists and students. To achieve this, OptiPex is built on three fundamental development pillars: measurement, analytics and interaction. OptiPEx partners will develop perception technologies to measure passenger behaviour and situations. Trustworthy analytics is essential in recognising real-time passenger experiences and situations, enabling interaction with services and vehicles. Moreover, OptiPEx partners will develop adaptive and interactive vehicle technologies and digital services in collaboration with target groups and suitable for various public transport modes. These services will optimise the onboard experience, promoting safety, inclusiveness and trust. Ultimately improved passenger satisfaction will drive the adoption of automated public transport technologies and improve the sustainability of mobility services via contribution to the modal shift. A consortium consisting of 3 research organisations, 6 industry members and 2 SMEs will validate the developed solutions together with target groups and other stakeholders in three living labs. The consortium has leading expertise in human behaviour, user-centric design, vehicle technologies, modelling and data analysis, and adaptive and interactive services. The successful adoption of OptiPEx results will be facilitated by efficient dissemination, communication, and exploitation activities in collaboration with the Connected, Cooperative and Automated Mobility (CCAM) partnership.

DELTA proposes a DR management platform that distributes parts of the Aggregator’s intelligence into lower layers of a novel architecture, based on VPP principles, in order to establish a more easily manageable & computationally efficient DR solution, ultimately aiming to introduce scalability & adaptiveness into the Aggregator’s DR toolkits; the DELTA engine will be able to adopt & integrate multiple strategies & policies provided from its energy market stakeholders, making it authentically modular & future-proof. DELTA will also deliver a fully autonomous architectural design, enabling end-users to escape the hassle of responding to complex price/incentive-based signals, while facilitating active, aware & engaged prosumers, based on innovative award schemes, a social collaboration platform & enhanced DR visualisation. Provision of full-scale market & grid services will be made possible by delivering explicit & implicit-based DR elasticity services, while pushing current market regulatory limitations so that they can be surpassed, and satisfying potential grid constraints related to flexibility activation through Multi-Factor Forecasting and Deep Reinforcement Learning Profiling. Furthermore, DELTA will propose & implement novel multi-agent based, self-learning energy matchmaking algorithms to enable aggregation, segmentation & coordination of several diverse supply & demand clusters, designed end-to-end using well-known, open protocols (i.e. OpenADR), for increasing interoperability. DELTA will set the milestone for data security in future DR applications by not only implementing novel block-chain methods & authentication mechanisms, but also by making use of Smart Contracts which would further secure & facilitate Aggregators-to-Prosumers transactions. Two pilots in UK & Cyprus will realise the DELTA concept, covering a wide variety of residential/tertiary loads (>11GWh), RES generation (>14GWh) & energy storage systems (>9MWh) (average annual measurements).