The operation of power systems is becoming more intricate due to the energy transition’s effects. This includes a rising share of intermittent and decentralized renewable generation, increased uncertainty in energy supply, and market-driven cross-border electricity transportation in Europe. These changes necessitate improved observability and control of critical system parameters to ensure power system reliability. Additionally, the transition requires enhanced resilience against cyber threats and system stability issues. To address these challenges, innovative approaches like the Digital Twin (DT) concept and data-driven techniques are proposed. The Digital Twin involves virtual representations of systems that mirror physical conditions, connecting the physical and digital realms through sensor data streams. This concept holds potential for applications demanding better observability and predictive capabilities. As power systems evolve towards higher automation, the DT becomes integral to discussions on autonomous systems and advanced power grid operation. This paper introduces the concept of DT-centered Energy Management Systems (EMS) and highlights its advantages in enabling future power grid automation. To implement DT in EMS, high-fidelity analytical models are required for accurate representation of the physical system. Combining DT with analytics allows holistic understanding, enabling novel automation and control methods by linking the physical and digital realms. A Single Source of Truth (SSoT) is foundational for creating a DT of complex infrastructures. The SSoT integrates diverse data sources, eliminating translation issues between software tools and data silos. This consolidates grid data, enhancing efficiency, flexibility, and reliability. SSoT-based DT enables adaptability to changing conditions, supporting efficient market participation and network reliability. The proposed EMS architecture employs DT as the core component for monitoring and control. It combines predictive modeling, dynamic state estimation,, model validation as well as parameter tuning to enhance the model fidelity and simulation accuracy. The ained trust in the decisions derived from the model results facilitates the developement of advanced decision support and operator assistance systems. To address power system stability challenges, Dynamic Security Assessment (DSA) using a DT is introduced. DSA extends beyond traditional Static Security Assessment by considering transient dynamics. DT-based DSA involves real-time and offline components, continuously updating models and assessing grid security against congestions and contingencies. A trust model is introduced to assess the coherence and state of a DT. It encompasses facets like functional correctness, safety, security, reliability, credibility, and usability. By applying trust across subsystems and services, a holistic view of the digitalized energy system’s health and state is achieved. This paper presents the concept of applying the DT as the core instance in the next generation of EMS and discusses the advantages of this prospective novel EMS architecture. It describes the evolutionary development in the power system domain from basic Digital Twin applications to systems that enable automated power grid operation in future. In conclusion, the integration of Digital Twin concept into EMS offers novel opportunities for power system operation and automation. It enhances observability, predictive capabilities, and decision support, enabling resilient and efficient grid management in the context of the energy transition. The presented trust model ensures system reliability and facilitates informed decision-making.
