As the global shift towards renewable energy accelerates, it is crucial to address the inherent challenges and fully leverage its potential. Electric power systems have undergone significant transformations, transitioning from traditional generation methods to those incorporating renewable energy sources and power electronic interfaces (PEI). This transition necessitates extensive research to ensure future grid stability and reliability. This thesis work aimed to enhance a Root Mean Square (RMS) synthetic model of the future 380 kVDutch power system and conducted comprehensive research using this model. A scenario analysis was conducted to evaluate various future scenarios for the Dutch power system, highlighting deviations and uncertainties. The national scenario from the II3050-2 project was selected as the baseline for further work. This approach ensured a comprehensive understanding of potential future developments and their implications for policy and planning. The synthetic model was developed by updating the existing model with new dynamic models and parameters as defined by IEEE and CIGRE standards and aligning it with future public projections and investment plans for the Dutch power system towards 2050, rooted in the scenario analysis. This included upgrading infrastructure such as transmission lines and substations and incorporating new generation and flexibility resources. The model was designed to enhance the dynamic characteristics and facilitate extensive research by integrating DigSilent PowerFactory, Python, and Excel. Three different case studies were performed using the enhanced synthetic model to analyze the system’s response to various perturbations. These studies evaluated the impact of varying levels of renewable generation and load, the role of grid-forming converters, and the effects of different kinetic energy and inertia constant levels on system stability with respect to frequency and rotor angle stability. The findings underscored the significant potential of grid-forming converters to enhance frequency stability and system damping, the influence of controller parameters on system performance, and the critical role of kinetic energy and inertia in maintaining system resilience. By leveraging the capabilities of PowerFactory, Python, and Excel, the research demonstrated the utility of the enhanced synthetic model in facilitating a broad range of stability studies and other analyses. This work provides a valuable foundation for future research and regulatory planning, contributing to the ongoing efforts of Dr. J.L. Rueda Torres’ team. The findings have been submitted to international journals and conferences, emphasizing the importance of continued technological adaptation and research to ensure stable and resilient power grids. Future work should focus on developing smart control strategies, optimizing dynamic control settings, investigating the impacts of kinetic energy and inertia constants, enhancing the synthetic dynamic model with additional features, and assessing the role of flexibility resources in future scenarios. This research offers crucial insights into the evolving dynamics of power systems and sets the stage for further advancements to ensure their stability and resilience.