Collection of ENEA technology and expertise
Digital Twin for Electrical grids
Renewable Energy trainer
Application sectors
Problem to solve
The increasing complexity of electrical energy systems requires advanced tools to support their design, management, and evolution in an efficient and sustainable way. To address this need, a Digital Twin (DT) has been developed to support the design of new energy systems, the optimization of existing plant management, and the integration of new technologies, while balancing economic aspects, performance, and environmental impact.
Description
The infrastructure is based on the use of a digital twin (DT), which combines advanced modeling and computational procedures to optimize the planning and management of electrical energy systems. The DT is intended to be connected to an experimental infrastructure including devices for the emulation of different energy entities, such as electrical generators and storage systems, enabling improved testing of representative scenarios for electrical energy systems through the measurement of relevant physical quantities, as well as local control and automation. The main functionalities provided include: Design of new electrical energy systems: enables the creation of an integrated system using energy generation, conversion, and storage technologies, optimizing solutions according to specific requirements; Management of energy systems: allows monitoring and optimization of the operation of complex systems, improving efficiency and reducing operating costs; Integration of new technologies: facilitates the integration of innovative technologies into existing systems, ensuring continuous improvement. These three functionalities will be supported by environmental and economic optimization models and algorithms, enabling the platform to meet different user requirements while balancing costs and sustainability.
Innovative aspects and advantages
- Possibility to test methodological approaches, models, and technological solutions for electrical networks within operational contexts consistent with real-world scenarios.
Admissible applications
- Enables real-time monitoring, predictive diagnostics, and balancing between generation and consumption, optimizing the integration and storage of energy from renewable sources.
- Implements advanced simulation and real-time control solutions to optimize the sustainability, operability, and resilience of electrical networks.
- Provides a secure environment for technology validation, specialized training, and the simulation of critical scenarios, supporting the enhancement of system resilience.
- The infrastructure includes tools for emulating energy entities, measuring physical parameters, and automating processes, integrating models and algorithms to plan and test eletrical Smart Grids and Microgrids.
Research group involved
Revision date
15-05-2026
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