Power Quality Enhancement in Hybrid Sustainable Energy Systems Grid-Connected Scheme by Modified Non-dominated Sorting Genetic Algorithm

In modern power systems integrating renewable energy sources like solar PV and wind, ensuring high-quality power delivery is essential. This article addresses the challenge of enhancing power quality in Hybrid Sustainable Energy Systems connected to the grid. We introduce a novel approach centered on the Unified Power Quality Conditioner (UPQC) and a specialized optimization technique, the Modified Non-dominated Sorting Genetic Algorithm (MNSGA-II) with Proportional Integral controllers. Our solution efficiently manages voltage levels, simultaneously reducing power loss and Total Harmonic Distortion. Compared to conventional methods such as PID controllers, Genetic Algorithms, and Particle Swarm Optimization, our approach stands out in terms of performance. We implement this methodology using MATLAB Simulink, conducting a range of comprehensive performance analyses. Our primary objective is to enhance power quality by addressing power loss and Total Harmonic Distortion, especially when dealing with non-linear and irregular loads at the point of common coupling. As a result, our MNSGA-II technique, in conjunction with UPQC compensation, significantly reduces harmonics of various orders, leading to an improved power quality environment with corresponding harmonic values of 0.29, 0.19, 0.13, 0.1, 0.09, 0.06, and 0.05.