The integration of variable renewable energy sources (VRES) into the Dutch transmission network is imperative for transitioning to a sustainable energy future. However, incorporating large-scale VRES poses significant monitoring and control challenges, such as fluctuating power flows and grid stability concerns. This manuscript examines the role of digital twins as modern tools for supervising and controlling power systems. This work also presents the development of a synthetic digital model of the Dutch extra-high-voltage (EHV) network to analyze steady-state performance under high VRES penetration scenarios for 2030. Using DIgSILENT PowerFactory, automated by Python scripting, this study offers insights into the impacts of VRES and electrolyzers in power networks. By creating and analyzing various future scenarios, this research evaluates the effectiveness of digital models in scenario analysis, marking a significant step toward the implementation of comprehensive digital twins for future energy system planning and optimization.

As electrical systems become increasingly complex with the integration of new electronic loads and variable renewable energy sources (VRES), modern tools are essential for their effective management and operation. This paper discusses an initial step toward the complete implementation of a digital twin for the Dutch electrical power grid: the development of a real-time digital model. This model represents the Randstad region’s electrical grid, which has recently been enhanced by substantial offshore wind power installations, including Hollandse Kust Zuid and Hollandse Kust Noord. The Real-Time Electromagnetic Transient (EMT) model described in this study enables the assessment of the impacts of offshore wind integration on network stability and power quality. Network elements have been modeled using RSCAD and implemented within the Real-Time Digital Simulator (RTDS). Detailed simulations are conducted to evaluate the grid’s capacity to handle the active and reactive power influx from the offshore wind farms. This study highlights the critical role of precise modeling in ensuring the reliability and efficiency of wind power integration into the national grid.