Optimized PI based fuzzy controller for power quality assessment in autonomous microgrid using novel hybrid bio-inspired optimization technique

The increasing penetration of nonlinear loads (NLLs) in three-phase distribution systems introduces significant harmonic distortion, leading to degraded power quality (PQ), increased losses, and potential voltage instability. To overcome these challenges, this paper proposes an enhanced shunt active power filter (SAPF) control strategy based on a hybrid Sand Cat Swarm Zebra Optimization tuned Second-Order Generalized Integrator with Fuzzy Logic Controller (SCS-ZO). The proposed approach effectively identifies phase angle variations, extracts fundamental signal components, and regulates compensating signals under dynamic operating conditions. The Second-Order Generalized Integrator (SOGI) module ensures accurate signal decomposition, while the fuzzy logic controller (FLC) provides robust voltage regulation and fast dynamic response. Furthermore, the hybrid Sand Cat Swarm Zebra Optimization optimization algorithm is employed to optimally tune controller parameters, improving convergence speed and overall system performance. The proposed controller is evaluated using a MATLAB/Simulink-based three-phase microgrid under balanced, unbalanced, and nonlinear load conditions. The results demonstrate that the proposed SCS-ZO significantly improves power quality by effectively mitigating harmonics, voltage fluctuations, and other disturbances, thereby enhancing system stability and reliability.