An Enhanced Control of Grid-forming Converters for Systems with High Penetration of Renewable Energies

Abstract

Renewable energies (REs) are increasingly important to provide a clean, reliable, and cost-effective energy system to meet the growing electricity demand. REs comprise a growing number of components that connect to the grid via power converters. Even current consumption levels present a considerable challenge in terms of just energy balance, but the near future is highly likely to contain significant load growth. In addition to the energy balance challenge arising from the increased load, larger frequency deviations coupled with the loss of inertia and voltage regulation problems will also appear in future power grids. Besides, phasing out the synchronous generators (SGs) leads to larger equivalent impedance and lower short-circuit current levels, resulting in a weaker grid, with an increased risk of instability. The thesis aims to enable the grid-forming (GFM) converters to offer power grid support functions and ancillary services in a way similar to or more advanced than the conventional SGs do both in steady-state and in dynamic/transient operating conditions. GFM converters are the more reliable choice to be employed for the future converter-dominated power grid with high penetration of renewable energy sources (RESs), so the focus is on this type of converter. The thesis contribution is mainly related to improving the performance of the GFM converters as follows: First, the inertia and oscillation-damping features of SGs are emulated in the control of the GFM converters to work as grid-supporting GFM virtual synchronous generators (VSGs). The employed parameters for implementing the VSG-based converter are adaptive to the mode of operation, so the best performance for both islanded and grid-connected modes of operation as well as the transition between these modes of operation are obtained, resulting in the plug-and-play capability of the VSG. A detailed small-signal model for each mode of operation is provided, and the small-signal analysis is used to identify the required parameter for the best performance in each mode of operation. Second, the fault ride-through (FRT) capability, i.e., the ability of the converter to stay connected and continue working at a lower voltage level under fault conditions, is added to the control of the GFM converter. A PI-based FRT control is proposed at first and then model predictive control (MPC) as a superior control concept is employed in the control of the GFM converter for both normal and fault-mode conditions. The MPC-based FRT protects the GFM converter from overcurrent while keeping its voltage mode functionality. Both the VSG and FRT capability of the GFM converter are validated through simulation results in MATLAB/Simulink as well as hardware-in-the-loop (HIL) test results.