Data-Adaptive Retrofit Control for Power System Stabilizer: Refinement with Park Model of Synchronous Generators

In this paper, we extend the design of data-adaptive retrofit control for power system stabilizers (PSS) from the one-axis generator model to the Park generator model, which is the most detailed representation of synchronous generators. The data-adaptive retrofit control allows individual sub-controller designers to design and implement PSS, using only a local subsystem model and local measurements. The data-adaptive PSS can also adapt to the variation of grid characteristics through the process of real-time estimation of intricate dynamical feedback effects between the main grid and the generator states. This paper presents the details of an extended retrofit control method that accounts for the higher order dynamics and increased parameters of the Park generator model. In addition, we perform a multi-objective optimization for online identification of grid characteristics to improve the performance of the PSS. Finally, we demonstrate the efficacy of the proposed data-adaptive PSS by conducting a detailed numerical simulation on the IEEE 68-bus power system model composed of the Park generator models, resulting in a large-scale complex nonlinear differential algebraic equation system.