A Set-Theoretic Adaptive Current Control Design for Grid-Following Inverter-Based Resources to Tackle Practically Non-Ideal Control Inputs

Three-phase grid-following (GFL) inverter-based resources (IBRs) play a vital role as an interface for integrating renewable energy resources and flexible loads, such as electric vehicles, into the power grid. This paper introduces a novel set-Theoretic adaptive control scheme for the primary control of three-phase GFL IBRs, designed to mitigate the impacts of uncertainties or non-ideal conditions affecting the control layer. These uncertainties will risk losing the stability and intended operation of three-phase GFL IBRs by potentially influencing the control commands transmitted to pulse width modulators. In order to address this issue, this study proposes an add-on control signal generated through an adaptive architecture to retrofit the existing (pre-designed) state feedback controller of GFL IBRs. As the name implies, this retrofit control strategy entails upgrading or modifying the existing feedback control instead of completely replacing it. The proposed control scheme is based on a set-Theoretic adaptive controller design that employs generalized restricted potential functions. A notable aspect of this framework is its ability to ensure that the reference tracking error bound remains below a user-defined threshold, making it "computable"by providing the control design parameters. The stability of the closed-loop system and the approximate reference tracking performance of the proposed control scheme for GFL IBRs are validated through a theoretical analysis employing the Lyapunov theory. Simulation-based and experimental results further confirm the efficacy of the proposed GFL IBR controller. Note to Practitioners-Given the strive to focus on renewables-intensive and modern power grids, inverters must exhibit enhanced intelligence and versatility to accommodate various functionalities. However, uncertainties or non-ideal conditions originating from diverse sources significantly threaten the optimal operation of inverter-based resources. These uncertainties introduce errors into the control loop of ...