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

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 postfault 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.

Reviewing Control Paradigms and Emerging Trends of Grid-Forming Inverters—A Comparative Study

“…Compatible with renewable energy integration Model predictive control (MPC) [30,31] The system uses mathematical models to predict system behavior and optimize control actions, offering adaptive and efficient operation under varying grid conditions. Adaptive control algorithms (ACAs) [32,33] The system adapts control parameters based on sensor feedback, ensuring stability and reliability in dynamic grid environments and offering flexibility and robustness.…”