Offset-free Data-Driven Predictive Control for Grid-Connected Power Converters in Weak Grid Faults

Abstract

Grid-connected power converters encounter significant stability challenges during weak grid faults, when conventional PI-based controllers exhibit an oscillatory response and poor fault-ride-through performance. This paper addresses this problem by replacing the conventional outer PI controllers that regulate DC-link and PCC voltages with an offset-free data-driven predictive controller. The developed algorithm leverages either pre-fault or fault-time data to construct input-output predictors, yielding offset-free control without the need for physics-based modelling. Simulation results show that pre-fault offset-free DPC doubles the critical equivalent grid impedance that can be handled and reduces the root mean squared error during faults by a factor of 40, while maintaining computation times comparable to conventional PI control. These findings demonstrate that the developed offset-free data predictive controller offers a simple, robust, and computationally efficient alternative to conventional control, significantly enhancing fault-ride-through capabilities of converters in weak grids.

Figures (8)

• Figure 1: Simulated PCC voltage of a GCPC with a critically weak grid fault. The lines labelled F and FC indicate the start of the fault and the moment it is cleared, respectively.
• Figure 2: Overview of different system components for a GCPC using CC.
• Figure 3: Converter modelling and control components: (a) a converter connected through a filter and transmission cable to the grid, (b) a block scheme of the conventional PI-control.
• Figure 4: Block scheme of an iSPC controller
• Figure 5: Controller structures during the two phases used in iSPC: (a) the identification phase (b) the control phase.