Data-Driven Robust Passivity-Based Controller Design for Grid-Connected Converters

Due to the integration of renewable-based distributed generation units (DGUs), energy storage systems (ESSs), and electric car charging stations, more and more power electronic converters are connected to the grid. In grids with a high penetration rate of these converters, high-current oscillation may happen, which can damage the grid equipment or cause a blackout. Passivity theory is used to design converter controllers in order to alleviate this problem in a decentralized fashion. However, the proposed methods are mostly model-based and are sensitive to parametric uncertainty. This article presents a robust data-driven frequency-domain grid-connected converter controller design with the possibility of defining robust passivity conditions on a performance channel. In addition to robust passivity, the controller design guarantees tracking and disturbance rejection performance. All performance and passivity conditions are written as constraints on closed-loop sensitivity functions and then changed to frequency-domain inequalities and convexified around an initial stabilizing controller. The controller design problem is converted to a convex optimization problem that can be solved efficiently using available solvers. The proposed method is validated by a power-hardware-in-the-loop (PHIL) experiment, including a switching inverter, real-time simulator, and
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