Optimizing Grid-Forming Controls using Relay-based Extremum Seeking to Enhance Transient Performance

TL;DR

This paper introduces a real-time adaptive control method using Extremum Seeking to optimize grid-forming inverter parameters, improving stability and transient response in power systems with high inverter penetration.

Contribution

It develops a novel ESC-based framework for dynamic tuning of GFM droop gain, balancing multiple performance objectives without needing an explicit grid model.

Findings

The cost function is convex with respect to the droop parameter.

The ESC algorithm tracks the optimal droop coefficient in real-time.

Simulation results show improved transient stability and robustness.

Abstract

Grid-forming (GFM) inverters are essential for enhancing stability in modern power systems with high penetration of inverter-based resources (IBRs). However, their performance highly depends on control parameters tuning, particularly the active power-frequency droop coefficient. This parameter presents a trade-off among competing objectives, including damping, settling time, rate of change of frequencies (RoCoF) and frequency nadirs. This paper proposes a real-time, adaptive optimization framework based on Extremum Seeking Control (ESC) to dynamically tune the GFM droop gain. A multi-objective cost function balances conflicting performance goals such as oscillation energy, frequency nadir, RoCoF, and post-disturbance settling performance. The approach is validated through numerical simulations on a modified IEEE 68-bus system. Results demonstrate that the cost function is convex with respect to the droop parameter, justifying gradient-based optimization. Furthermore, the ESC algorithm successfully tracks the time-varying optimal droop coefficient in real-time as network conditions change, thereby ensuring robust and near-optimal system performance without requiring an analytical grid model.