Advanced Compensation‐Based Power Quality Enhancement and Harmonic Mitigation in Smart Microgrids with Renewable Energy Integration

Renewable energy systems are increasingly adopted for their environmental benefits and ability to meet local electricity needs. This manuscript presents a novel approach to designing a smart‐microgrid (SMG) system that uses advanced power compensation methods to enhance power quality in low‐inertia systems. The proposed system integrates a combination of crested porcupine optimization (CPO) method with the dual‐stream multidependency graph neural network (DMGNN) technique. The adaptive power quality compensator (APQC) used in the proposed system combines shunt and series compensators. Reducing transient voltage fluctuations and stabilizing the dynamic voltage profile are benefits of using a thyristor‐controlled series capacitor (TCSC) as the series compensator. A shunt active power filter (SAPF) is used as a shunt compensator to lower voltage and current harmonics and raise the power factor. The DMGNN predicts the best PID controller parameter. Simulation results validate in MATLAB and the efficiency of the proposed technique in achieving superior PQ and operational efficiency compared to existing approaches such as modified water wave optimization (MWWO), multiobjective grey wolf optimizer (MOGWO), and enhanced bald eagle search (EBES) optimization achieving a total harmonic distortion (THD) of 0.1% and an efficiency of 98.7%, highlighting its effectiveness in improving power quality and system performance.