## 5 Discussion  
From the different ways to provide damping to LFOs using a GFM inverter, those based on reactive power are not specially affected by the change in the control paradigm from GFL to GFM.  
This paper, therefore, focuses on active-power-based damping strategies, presenting the analytical and theoretical background for both the inherent damping capability of GFM control and the role of active power setpoint dynamics. By appropriately tuning the inertia and droop parameters, GFM inverters can effectively provide damping. Inertia is synthesized using two parameters (\(m_{p}\) and \(\tau_{f}\)), and the proper selection of these can be sufficient for most applications. However, this technique has inherent limitations: increasing damping performance often results in heightened sensitivity of the GFM control to frequency perturbations. Nonetheless, if system conditions allow for the use of a reduced droop coefficient, this method remains the simplest, most robust, and effective option.  
When tuning droop parameters alone does not achieve sufficient damping, a higher-level POD-P algorithm can be implemented. So, in recent years, many POD-P solutions have appeared for GFM-controlled inverters. However, few of these approaches evaluate the influence of the POD-P control structure on inherent GFM functionalities, such as inertia, damping, or synchronizing power. Given the potential of POD-P algorithms to significantly alter these characteristics, it is essential to assess and verify the behavior of GFM systems when such controllers are introduced.  
Unlike GFM inverters, GFL-controlled inverters do not possess intrinsic dynamic characteristics, as they merely follow current setpoints. Consequently, in GFL systems, the application of POD-P control does not alter the device's nature. In contrast, with GFM inverters, integrating a POD-P controller requires a revised methodology to ensure core dynamic properties remain unaffected. This study addresses these concerns by analyzing the impact of the POD-P structure on GFM behavior using a NPF method.  
Figure 16: \(\Delta P/\Delta\omega_{g}\) NFP Bode plot for the base case (without POD, H = 2.5 s, \(m_{p}=0.015\), and \(T_{f}=0.075\)) compared to the proposed POD with the overlapping measurements (dots).  
The NFP method, based on perturbations generated by an infinite bus, does not take into account grid details, so the verification is not grid-oriented. However, from the perspective of system operators (or inverter manufacturers who must comply with grid codes), the NFP method is very interesting as it guarantees GFM core functionalities for specific equipment.  
Several techniques exist to improve damping in GFM inverters by adapting the PSL. While many of these strategies are either tailored to specific grid configurations or provide general tuning frameworks, the reality is that the power grid is a dynamic and evolving system. Changes in demand, generation, or operator actions can alter grid characteristics over time. In this context, the simplicity of the proposed POD-P method becomes an advantage. Its simplicity allows us to reconfigure the targeted frequency band, offering a form of user-supervised adaptability.  
Taking all the above into consideration, and recognizing that droop tuning remains the most straightforward and preferred method for providing damping, the proposed POD-P algorithm demonstrates that additional damping can be introduced into GFM-based inverter-based resources (IBRs) without compromising their inherent capabilities. Furthermore, the control strategy can be easily configured without requiring prior knowledge of grid parameters.