The proposed methodology can be extended to handle larger power systems with more complex dynamics by implementing a hierarchical approach. In this approach, the power system can be divided into subsystems or components, each with its own set of dynamics. PINNs can then be trained to model the dynamics of each subsystem individually. By integrating these PINN models into the numerical solvers for each subsystem, the overall system dynamics can be accurately captured. This hierarchical modeling approach allows for scalability to larger systems by breaking down the complexity into manageable parts. Additionally, incorporating domain knowledge and system-specific features into the PINN training process can enhance the accuracy and efficiency of the models for larger power systems.