Optimization of grid-connected wind energy systems using DSTATCOM controlled by hybrid intelligent techniques

The Wind Energy Conversion system (WECS) integrated into modern power grids introduces significant challenges related to power quality, voltage stability, and harmonic distortion. To address these issues, this study proposes an advanced control strategy for a grid-connected Wind Energy Conversion System (WECS) based on a Permanent Magnet Synchronous Generator (PMSG), supported by a three-phase Distribution Static Compensator (DSTATCOM). The DSTATCOM is controlled using a novel hybrid intelligent algorithm Butterfly Generated Particle Swarm Optimization with PI control (BG-PSO-PI). This controller combines the global and local search capabilities of the Butterfly Optimization Algorithm with the fast convergence properties of Particle Swarm Optimization, ensuring robust performance under varying wind and load conditions. The proposed method effectively regulates DC-link voltage, enhances dynamic response, and provides accurate reactive power compensation. Additionally, it minimizes Total Harmonic Distortion (THD), achieving better power quality than conventional PI controller. The control algorithm dynamically adjusts the reference current by optimizing the fundamental weight values of load current, and generates precise gating signals through a Hysteresis controller. Simulation results demonstrate that the BG-PSO-PI-based DSTATCOM significantly improves voltage stability, reduces THD, and enhances overall power quality in smart grid environments, making it highly suitable for reliable and efficient renewable energy integration.