Optimal Control for Robust Dynamic Performance in Inverter-Dominated Power Systems. Part II: Optimization and Results

Part II of this two part paper focuses on solving the robust optimal control problem introduced in Part I, marking the first effective attempt to bring control design optimization into the large-signal domain. To address this problem with high fidelity, transparency, and interpretability, we develop a nonlinear programming-based solution methodology. Specifically, the continuous-time dynamics of the Inverter-Dominated Power System (IDPS) are transcribed using the Hermite–Simpson collocation method, coupled with a mesh refinement procedure. To handle the min-max problem structure, a local reduction strategy is employed, with each iteration validated through electromagnetic transient simulations. The results highlight the critical role of robust control design in ensuring resilient and stable IDPS behavior across a broad set of plausible scenarios. Moreover, the methodology proves effective in capturing key aspects of system dynamics, such as IBR current saturation, thereby reducing the risk of inadvertently introducing undesirable responses through the control design process. Collectively, this two part paper establishes a strong foundation for unlocking the potential of IBRs to enhance power system's performance through centralized control design optimization.