## 5 Discussion
It highlights the importance of assessing inertia requirements accurately and implementing strategies to mitigate the decline in frequency response, particularly in systems with increased levels of renewable energy penetration. It is crucial to emphasize the significant importance of effectively monitoring, controlling, and managing the power system, particularly in scenarios involving the integration of converter-interfaced generation, especially during large system disturbances. To adequately respond to imposed changes, understanding the system and accurately predicting key parameters such as the inertia constant is essential. Therefore, the prediction process today represents a significant and intricate task, requiring reliable and relevant input data, as well as a thorough analysis and differentiation of the parameters within predictive models that have the most significant impact on the outcome. The future modernization of power systems will rely on predictions of system parameters critical for efficient system operation in conditions dominated by renewable energy generation. If the approach presented in the paper considered solar or hydro energy, the dynamic inertia estimation of the power system could change. Solar and hydropower sources have different characteristics compared to traditional sources. Solar energy, being intermittent and dependent on weather conditions, could introduce greater variability and uncertainty in the inertia estimation process. Conversely, hydroelectric systems share similarities with traditional power plants in terms of mechanical inertia. Therefore, when integrating solar or hydro resources, adjustments in the modeling approach and stability assessment are crucial. These adjustments must account for the unique operational behaviors and characteristics of solar and hydro energy sources, which significantly differ from conventional generation methods. Future work is essential to underscore the importance of a tailored approach in system modeling and stability evaluation, particularly in the context of the non-dispatchable and intermittent nature of renewable resources. This nuanced understanding is essential for developing effective strategies for grid management and policy implications, especially in relation to inertia and frequency regulation in a renewable-dominant energy landscape. Adapting and expanding the MEMD/RoCoF methodology for modern power systems involves an approach that acknowledges the unique characteristics of various generation types and the evolving nature of power systems. By integrating more diverse data sources, such as those from renewable energies like solar and wind, and leveraging real-time data analytics, the methodology becomes more robust in handling the variability and intermittency of these sources. Incorporating advanced forecasting techniques enhances the system's ability to anticipate and respond to disturbances or inertia changes. This approach requires scalability and flexibility to manage complex and large power systems and a collaborative framework among stakeholders for effective data sharing and decision-making. Such an approach ensures that the MEMD/RoCoF methodology remains relevant and effective in the face of the dynamic challenges posed by modern power systems. To adapt and expand the MEMD/RoCoF methodology for diverse power system configurations and challenges, it is necessary to enhance the MEMD model to better handle the variability and intermittency of renewable energy sources like wind and solar. Also, real-time data from various power generation sources can be used to improve the accuracy and responsiveness of the RoCoF calculations. It is essential to ensure that the methodology is scalable to handle large and complex power systems, and flexible enough to adapt to new technologies. By focusing on these areas, the MEMD/RoCoF methodology can be effectively adapted to meet the evolving challenges and configurations of modern power systems.