Effective smart planning, operation and control of the electricity grid and numerous distributed devices – including smart electricity meters, smart bi-directional charging networks for electric vehicles, and smart building platforms – are essential. These efforts must be underpinned by markets for flexibility and demand response, along with seamless data exchange between actors and devices.

On-going innovation in the energy data space, smart Internet of Things (IoT) solutions, and digital twins for energy systems, coupled with energy price and market considerations, provide the foundation for advanced energy system intelligence. This intelligence will be further enhanced by leveraging generative artificial intelligence and the emerging AI Factories.

The scope is to develop and pilot prototypes of a generative AI-powered digital spine that enhances the digitalisation and decarbonisation of the EU energy system.

The overall scope is the development of a prototype of an automated, AI-powered, software-defined smart energy system leveraging and further developing existing (open-source) digital solutions of lower TRLs developed in EU and national research, innovation- and deployment-programmes, as well as AI algorithms and tools provided by the AI Factories, namely to:

• Develop and test the potential for generative AI to develop apps/programmes for local system optimisation and for system planning and operation;
• Develop and test generative AI that can identify sources of flexibility and provide solutions for interoperability and data exchange to enable decentralised optimisation of distributed assets. This includes the integration with various data sources and sectors, such as mobility, to promote decentralisation, energy-efficiency, and cost-efficiency and to enable interoperability across different parts of the energy system;
• Explore the potential of generative AI for system optimisation through scenario generation, simulation, and time series forecasting, while also developing optimisation tools for both supply-side and demand-side management using forecasts and data for renewable energy, transmission assets, storage, and energy-saving applications for consumers;
• Propose tools and control systems to apply generative AI solutions developed in a high-risk use-case (as defined in the AI act).

The developed solutions should be dynamic, flexible, offering reconfigurable automated management, control and data exchange to ensure seamless operations across decentralised a setting.

Projects are expected to:

• Demonstrate AI-powered energy services, tools for power system planning and operation, and smart grid functionalities, such as flexibility, and electric vehicle (EV) charging as well as possibly transmission system operation across at least three EU member states and/or associated countries to enhance demand flexibility and drive innovative capabilities for decarbonisation and energy efficiency;
• Indicate which generative AI basic tools, including available tools from the AI Factories, will be used and demonstrate how energy sector users will be involved in the development and the testing (and possible uptake) of the generative AI tools by the project;
• Indicate what types of assets and what data sources will be used and involved in the project;
• Involve both traditional energy stakeholders and new entrants, such as energy service companies, aggregators, digital infrastructure providers, system integrators, energy asset manufacturers, energy communities, and active consumers;
• Leverage relevant European and international standards and technical specifications, and actively engage with standards development organisations;
• Contribute to the BRIDGE initiative, actively participate in its activities;
• Make use of the AI Factories and solutions, open-source where relevant, building on developments in previous Horizon Europe projects, particularly those related to flexibility markets and data exchange, Internet of Things and edge-cloud computing, adhering to relevant standards and engaging with standards development organisations to further develop these standards;
• Demonstrate how the new solutions can be integrated into and/or replace (parts of) existing legacy systems, including (for projects that focus on DSOs) demonstrate how the new solutions can integrate core functions of grid operations including SCADA systems functionality;
• Jointly provide a diverse set of applications of generative AI.