An Integrated Grid Hybrid System to Improve Power Quality

Abstract

The frequent operation of one-phase loads in three-phase systems and the growing demand for nonlinear demands are major contributors to grid-connected systems' power quality issues. It consequently results in an undesired Power Quality Issue that is characterized by changes in the electrical system's waveforms, voltage levels, and current. Compared to power quality issues connected to current, normal voltage-related issues cause a major interruption in the network. Through a sequential process, the integrated series Active Pass Filter provides the grid with the required voltage while efficiently reducing the harmonics caused by nonlinear demands that are connected to the grid. This project focuses on the creation of an adaptive neurofuzzy inference system for the controller. The purpose of this controller is to minimize the active filter rate while producing the reference voltage signals. The MATLAB 2020b/Simulink platform was used for the simulation analysis, which compared the effectiveness of the proposed ANFIS controllers to a conventional controller. Voltage quality problems such as voltage drop, flickering, voltage rise, zero currents, and reactive energy are successfully reduced by this grid-connected technology. By incorporating green energy sources into its DC-link, the system's overall performance is improved by reducing both short-term and long-term voltage swings. A working model was successfully validated to demonstrate the effective operation of the power distribution system under various situations, adhering to the parameters established by IEEE standard 519-1992. The overall harmonic distortion was significantly reduced by the working model by about 30%, which is much less than the allowed 5% threshold.