A steel hot strip finishing mill presents significant interactions between variables that considerably reduce performance. Traditionally, the control techniques implemented are based on classical approaches assuming an ideal model. Modelling interactions would allow the opportunity to suppress them by the application of modern multivariable control techniques. In this paper the derivation of a linearized multivariable model of a real-life hot strip mill based on previous schemes is presented as a case study. Linearization of the non-linear static relations around an operating point is performed. The operating conditions are the mill set-up calculations obtained from rolling schedules and non-linear relations used in the plant. Some useful details for practitioners are given. Simulations and experimental model validation are also presented. Since the mill in the real hot rolling line is in closed loop, it is not possible to carry out an experimental validation of the plant itself (i.e. in open loop); therefore, the model was experimentally validated in closed loop. As an example of the use of the multivariable model an H_∞ multivariable optimal controller to attain nominal performance is designed for the looper system and results are presented.

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.

This paper presents a sizing and optimization methodology for LCL filters tailored to high-capacity modular power systems. The approach prioritizes the strategic selection of the resonance frequency, an asymmetric inductance design, and strict harmonic current limits. The methodology is validated through a case study simulation of a 126 MW photovoltaic plant in a region of Mexico, analyzing its 2.34 MW inverter architecture. The simulations show that precise capacitor sizing for reactive power management, combined with a passive resistive damping strategy, ensures compliance with grid interconnection standards (IEEE 1547) and power quality standards (IEC 61000). This approach simplifies practical implementation by eliminating the need for complex active damping control algorithms. Additionally, dynamic decoupling is validated through time-domain step responses, and frequency-domain sensitivity analysis confirms robust stability margins even under ±20% variations in passive parameters. Ultimately, the system achieves voltage total harmonic distortion (THD) levels below 0.18%, demonstrating a scalable solution for maintaining grid stability.