Operational Challenges of Digital Real-Time Simulation (DRTS) for the Management of Distributed Energy Resources (DERs)

The transition toward active and converter-dominated distribution networks is increasing the need for Digital Real-Time Simulation (DRTS) platforms capable of supporting the validation, operation, and planning of modern power systems with high penetrations of Distributed Energy Resources (DERs). This review aims to critically examine the technological and methodological barriers that continue to limit the evolution of DRTS from a validation tool toward an operational cyber–physical infrastructure for future intelligent power systems. Particular attention is devoted to computational scalability, communication latency, Hardware-in-the-Loop (HIL), model conversion, proprietary “black-box” devices, digital twins, and the computational strategies required to preserve deterministic real-time execution. The reviewed literature indicates that maintaining real-time determinism while preserving high-fidelity electromagnetic transient (EMT) models remains one of the principal technological challenges for future DRTS platforms. The analysis further shows that many of the current limitations associated with digital twins, grid-forming technologies, and large-scale industrial deployment originate not from isolated technological deficiencies, but from the interaction among computational, communication, interoperability, synchronization, and model-management constraints. The evidence indicates that overcoming these limitations requires coordinated advances in computational architectures, communication infrastructures, model automation, interoperability, and cyber–physical integration rather than isolated hardware improvements. Overall, this review argues that the future impact of DRTS will depend not only on improvements in simulation performance, but also on its evolution into an interoperable and experimentally oriented cyber–physical infrastructure capable of supporting phenomenological analysis and the next generation of intelligent, resilient, and autonomous power systems.