LF Energy Summit Europe 2026

The increasing complexity of energy systems calls for new approaches to design, develop, and operate secure and interoperable Digital Twins across heterogeneous environments.
Within the IPCEI-CIS AVANT project, DT4ENERGY is developed as an open platform enabling the creation of Digital Twins for energy systems, supporting real-time monitoring, simulation, and data-driven services. It provides a modular and extensible foundation for integrating distributed data, models, and applications, while ensuring interoperability and enabling the scalable deployment of AI capabilities.
In this session we present DT4EC, a real-world implementation for Energy Communities, demonstrating how DT4ENERGY supports operational use cases. DT4EC integrates Machine Learning models for day-ahead production and consumption prediction, as well as self-consumption optimization, combined with Generative AI services for KPI analysis, explainability and decision support.
By sharing implementation insights, this session shows how open Digital Twin platforms can move from architecture to operation, enabling secure, interoperable, and AI-driven energy applications, with DT4EC as a concrete and validated example.