Power Quality Enhancement of Solarwind Grid Connected System Employing Genetic-Based Anfis Controller

Abstract

The increasing global demand for electricity has driven the exploration of renewable energy sources to generate power in an environmentally friendly manner. Solar photovoltaic systems and wind-based generators are considered significant sources of renewable energy and are referred to as Distributed Generation units due to their dispersed nature. These units use bidirectional converters to provide auxiliary services on both the grid side and the load side, regardless of the microgrid operation mode. Additionally, DC power generation units are converted into AC systems through inverters. These systems not only introduce voltage and current harmonics and power frequency deviations but also push the distribution system into precarious operating conditions. This underscores the need for advanced control strategies for microgrid architecture.As a result, power electronic converters introduce harmonics into the system, which can impact overall system performance. To address these emerging challenges, the authors have introduced an advanced custom power device called the Distributed Power Flow Controller (DPFC). In this study, the proposed solar-wind hybrid energy system is primarily evaluated using the DPFC mechanism. Subsequently, the system is further assessed using a Genetic Algorithm (GA)-based fuzzy logic controller and a GA-based Adaptive Neuro Fuzzy Inference System (ANFIS) controller for shunt control within the context of the DPFC mechanism. The validity of the results is confirmed through simulations using MATLAB/Simulink software.