Design of Total Harmonic Distortion Reduction Using Quantum Coyote Optimization Algorithm for Hybrid Power Generation Systems

The usage of various inverters in various industries has gained considerable attention in the power electronics industry in recent years. The harmonic distortion that is induced by various renewable energy sources, along with the growing use of nonlinear loads and power electronic devices, has a significant impact on the distribution system. This is because of the rise in penetration of various renewable energy sources and the usage of nonlinear loads and power electronic devices. In addition, distributed generation (DG) units with inverters (such as solar (PV) and wind turbines) that are integrated into distribution networks are viewed as significant harmonic producers that have substantial adverse effects on power quality. The power quality in the system suffers because of these generators. This study proposes a method of harmonic mitigation for addressing power quality problems that are present in distribution systems as a solution to the challenges that have been found. These concerns have been brought to light as a result of previous research. The standard two-level and three-level inverters were the basis for the development of the multilevel inverter (MLI), which was meant to address their shortcomings. One of the effective technologies that can maintain constant performance is the hybrid power generating system. A hybrid energy system has several benefits, including high dependability, cheap cost and minimal emissions. When used in a hybrid power production system, the reduction of total harmonic distortion (THD) becomes absolutely necessary (HPGS). In this context, the research provides a novel approach for high-performance quantum computing called quantum coyote optimization algorithm-based THD reduction (QCOA-THDR). The QCOA-THDR approach that has been presented has been tested with several converters, including SEPIC, buck–boost and Cuk converters. Additionally, the proportional as well as the integral gain variables of the proportional integral (PI) controller are set in order to achieve decreased total harmonic distortion (THD). In addition, the QCOA system is formed by combining the ideas of quantum computing (QC) with the traditional COA. This is how the QCOA system comes to exist. A limited number of simulations were run, and the results are being analyzed from a variety of perspectives in order to investigate the improved effects that the QCOA-THDR approach has on data. The QCOA-THDR method was shown to have superior results than the more modern techniques, as shown by the comparison research.