Grid-Connected, Data-Driven Inverter Control, Theory to Hardware

TL;DR

This paper demonstrates that a data-driven, model-free control method called Transient Predictive Control (TPC) can be effectively implemented in real-world grid-connected inverters, offering a practical alternative to traditional model-based control.

Contribution

It shows how TPC, originally based on LTI assumptions, can be applied to nonlinear, time-varying inverter systems in real hardware setups.

Findings

TPC runs successfully on standard hardware in real-time.

TPC effectively controls grid-connected inverters in experimental setups.

The approach is validated on a 25 kVA inverter connected to the grid.

Abstract

Grid-connected inverter control is challenging to implement due to the difficulty of obtaining and maintaining an accurate grid model. Direct Data-Driven Predictive Control provides a model-free alternative to traditional model-based control methods. This paper describes how the recently-proposed Transient Predictive Control (TPC) can be used for real-world, plug-and-play inverter control. The following hypotheses were tested: 1) The TPC algorithm can be run online using standard hardware, and 2) TPC, which is derived using Linear Time-Invariant assumptions, is effective for grid-connected inverter control, which is a nonlinear and time-varying system. Experiments conducted on a two-converter benchtop setup and at the CoSES Laboratory on a 25 kVA converter connected to the Munich grid support these hypotheses.