The integration of rapidly expanding renewable energy sources poses significant challenges for modern power grids. The voltage-source converters (VSCs) are commonly employed for grid integration, conventionally using a vector control approach with inner-loop and outer-loop controllers. Effective tuning of these controllers is essential for stable operation. However, much of the existing literature relies on conventional tuning methods for the proportional-integral gains, which often fail to yield optimal performance. This study proposes the moth-flame optimization (MFO) algorithm to optimize the VSC controller parameters. MFO is applied simultaneously to both inner and outer controllers of a grid-connected VSC system. The results are compared with those obtained using the particle swarm optimization, teaching-learning-based optimization, and ant colony optimization algorithms using MATLAB/SimPowerSystems. The robustness of the optimized parameters is evaluated using dynamic models of both a Type-4 wind turbine generator connected to the grid and a VSC-grid connected system, subjected to different disturbances such as load changes, voltage variations, and active power reference changes. Beyond nominal operating conditions, this study further investigates performance under weak-grid scenarios and sub-synchronous oscillations at 20 Hz. The effectiveness of the proposed controller is validated through an OPAL-RT-based real-time experimental setup (OPAL-RT-OP4510) and corresponding simulation studies. Results demonstrate the controller's robustness and improved dynamic response for enhancing stability and control of grid-connected VSC systems in weak-grid conditions.
Gandi et al. (Thu,) studied this question.