A Model Predictive Approach for Enhancing Transient Stability of Grid-Forming Converters

TL;DR

This paper introduces a model predictive control method to improve the transient stability of grid-forming inverters during post-fault conditions by optimizing their trajectory through corrective phase and power adjustments.

Contribution

The paper develops a novel MPC-based control strategy that enhances post-fault stability of GFM inverters by actively managing phase and power references during current saturation.

Findings

Significant improvement in transient stability demonstrated in simulations.

Effective mitigation of oscillations between saturation and normal modes.

Outperforms existing control strategies in stability enhancement.

Abstract

A model predictive control (MPC) method for enhancing post-fault transient stability of a grid-forming (GFM) inverter based resources (IBRs) is developed in this paper. This proposed controller is activated as soon as the converter enters into the post-fault current-saturation mode. It aims at mitigating the instability arising from insufficient deceleration due to current saturation and thus improving the transient stability of a GFM-IBR. The MPC approach optimises the post-fault trajectory of GFM IBRs by introducing appropriate corrective phase angle jumps and active power references where the post-fault dynamics of GFM IBRs are addressed. These two signals provide controllability over GFM IBR's post-fault trajectory. This paper addresses the mitigation of oscillations between current-saturation mode and normal mode by forced saturation if conditions for remaining in the normal mode do not hold. The performance of the proposal is tested via dynamic simulations under various grid conditions and compared with other existing strategies. The results demonstrate significant improvement in transient stability.