AI Assisted Digital Twins for Energy Management Systems: Survey and Challenges

Artificial Intelligence–driven Digital Twins (DTs) for energy management offer valuable insights for stakeholders by enabling real-time monitoring, prediction, and optimization of energy systems. This paper first clarifies the DT concept through a concise survey of its different interpretations and applications. As a practical implementation, the ORION EU H2020 project is presented, with its objectives mapped onto a DT-based architecture for sustainable energy management. Key challenges—such as data heterogeneity, scalability, and privacy constraints—are analyzed, and potential solutions are proposed for different use cases. Finally, experimental results from prototype implementations are discussed, demonstrating the feasibility and benefits of AI-enabled DTs in improving energy efficiency and decision-making.