The adoption of Microgrids (MGs) assists in evolving the power grid into a more effective, flexible, minimized losses, and less polluted solution for offering the necessities and acquirements of energy consumers. Diverse Renewable Energy Sources (RESs) are incorporated into the MGs owing to their characteristics including the inability and variability for precisely controlling and predicting the created various technical issues. The essential issue in MGs that needs to be handled is achieving the essential Power Quality (PQ) regarding the stabilization in voltages and distortions in harmonic levels. Thus, various types of equipment are recommended for enhancing the challenges regarding the uncertainty in sources and nonlinearity in loads. To mitigate the PQ issue in MGs, a new hybrid meta-heuristic algorithm called Hybrid Tuna-Glow worm Swarm Optimization (HT-GWSO) is suggested in this research work. It is implemented with the integration of both Tuna Swarm Optimization (TSO) and Glowworm Swarm Optimization (GSO) algorithms, where the controller parameters are tuned by HT-GWSO. It focuses on enhancing the PQ by differing active power with reactive power. The objective as the minimization of error function along with reducing the power variants is considered here.