Reduction Of Total Harmonic Distortion Research Articles

Harmonizing power systems with a 13-level modified Packed U-Cells multi-level inverter: Design and implementation

Traditional multilevel inverter designs often face complexity challenges, prompting the need for a simplified solution. This study introduces and evaluates the performance of a Modified Packed U-Cells (MPUC) inverter in the realm of multilevel inverter technology. The study addresses challenges associated with conventional multilevel inverters and proposes the MPUC inverter as a solution to simplify the design complexity. The MPUC inverter, utilizing three DC sources and eight switches, presents a groundbreaking thirteen-level output waveform. The primary focus lies in assessing the inverter's performance in terms of Total Harmonic Distortion (THD) and output voltage. Utilizing MATLAB/Simulink, the inverter's performance is evaluated with and without Pulse Width Modulation (PWM) strategies. The results reveal a notable reduction in THD, from 26.25% to 9.91% post-filtering when PWM is not employed. Various multi-carrier Level-Shifted PWM strategies, including PDPWM, PODPWM, APODPWM, and COPWM, are explored to enhance output waveform smoothness and efficiency. Unequal Carrier strategies, specifically UEAPDPWM and UEAPODPWM, emerge as superior in THD management at different frequency ranges. The study further incorporates real-time hardware implementation of the proposed 13-level MPUC topology, highlighting the success of the UEAPD-PWM strategy in improving waveform quality. The research aims to establish a multilevel inverter design protocol meeting international standards and emphasizes the pivotal role of PWM techniques in enhancing waveform quality. This comprehensive evaluation contributes to advancing the field of multilevel inverter technology and sets a benchmark for future research in this domain.

Improved Power Sharing Strategy for Parallel Connected Inverters in Standalone Micro-grid

The primary goal of integrating alternative energy systems such as solar and wind turbines into the power grid using power electronic devices is to meet the growing energy demands. Connecting inverters in parallel effectively enhance power capacity, reliability, and overall system efficiency. However, an uneven power distribution among the inverters is a significant limitation in these parallel connected inverters (PCI). This study focuses on a distributed generation (DG) unit comprising a solar photovoltaic system (SPV) and a battery energy storage system (BESS) connected to voltage source inverters (VSI) 1 and 2. The proposed approach aims to achieve uniform load/power distribution among the inverters with power management, maintaining a constant DC link voltage despite variations in solar irradiation and temperature. Additionally, the strategy targets the reduction of total harmonic distortion (THD) in the load current. The conventional droop control method is restricted in its ability to achieve accurate and uniform power distribution during load changes. An enhanced P-f and Q-E-based droop control technique (EDCT) and a fuzzy logic controller (FLC) have been proposed to address these challenges. Performance analysis using MATLAB/Simulink was conducted with two test cases, and a comparative assessment was carried out with a conventional controller, such as a Proportional Integral Controller (PIC) and Sliding Mode Controller (SMC), to showcase the effectiveness of the developed control technique. The proposed control method ensures equal sharing of active power of 2.5 and 4kW, 2.5 and 7.5kW and reactive powers of 2.5 and 4Vars, 2.5 and 7.5Vars among the inverters for the two cases even during the load change at t=0.5seconds. The settling time for DC link voltage and THD is effectively diminished to 0.03 and 0.25 seconds and 1.18% and 2.87% for the two test case studies of the proposed method, which are much lower than those of existing methods available in the literature.

Multiobjective Neuro-Fuzzy Controller Design and Selection of Filter Parameters of UPQC Using Predator Prey Firefly and Enhanced Harmony Search Optimization

This research introduces a unified power quality conditioner (UPQC) that integrates solar photovoltaic (PV) system and battery energy systems (SBES) to address power quality (PQ) issues. The reference signals for voltage source converters of UPQC are produced by the Levenberg–Marquardt back propagation (LMBP) trained artificial neural network control (ANNC). This method removes the necessity for conventional dq0, abc complex shifting. Moreover, the optimal choice of parameters for the adaptive neuro-fuzzy inference system (ANFIS) was achieved through the integration of the enhanced harmony search algorithm (EHSA) and the predator-prey-based firefly algorithm (PPFA) in the form of the hybrid metaheuristic algorithm (PPF-EHSA). In addition, the algorithm is employed to optimize the selection of resistance and inductance values for the filters in UPQC. The primary objective of the ANNC with predator-prey-based firefly algorithm and enhanced harmony search algorithm (PPF-EHSA) is to enhance the stability of the DC-link capacitor voltage (DLCV) with reduced settling time amid changes in load, solar irradiation (G), and temperature (T). Moreover, the algorithm seeks to achieve a reduction in total harmonic distortion (THD) and enhance power factor (PF). The method also focuses on mitigating fluctuations such as swell, harmonics, and sag and also unbalances at the grid voltage. The proposed approach is examined through four distinct cases involving various permutations of loads and sun irradiation (G). However, in order to demonstrate the performance of the suggested approach, a comparison is conducted with the ant colony and genetic algorithms, i.e., (ACA) (GA), as well as the standard methods of synchronous reference frame (SRF) and instantaneous active and reactive power theory (p-q). The results clearly demonstrate that the proposed method exhibits a reduced mean square error (MSE) of 0.02107 and a lower total harmonic distortion (THD) of 2.06% compared to alternative methods.

Performance Analysis of ANFIS-PID Controller based Speed Regulation and Harmonic Reduction in BLDC Motor Application

This study focuses on assessing the performance of a Proportional-Integral-Derivative (PID) controller integrated with an Adaptive Neuro-Fuzzy Inference System (ANFIS) in the context of speed regulation and harmonic reduction in Brushless DC (BLDC) motor applications. Rising BLDC motor speed elevates Total harmonic distortion (THD) due to non-linearity. THD reduction is vital for efficiency, reliability, and compliance in applications like electric vehicles, HVAC, and industrial automation, ensuring optimal performance and longevity. Through simulation-based design and implementation, the effectiveness of the ANFIS-PID controller is evaluated for achieving precise speed control and reducing harmonic distortions in a virtual environment. Various conventional control topologies are considered, with the ANFIS-PID controller demonstrating superior performance. The synergy of adaptive fuzzy logic and classic control components allows the ANFIS-PID controller to outperform others, particularly in dynamic conditions and varying motor characteristics, offering enhanced speed regulation and harmonic reduction in BLDC motor applications. Detailed simulations in MATLAB/Simulink software thoroughly assess the controller's dynamic response and its ability to accurately regulate BLDC motor speed while concurrently reducing harmonic distortions.

Robust adaptive backstepping control of H‐bridge inverter based on type‐2 fuzzy optimization of parameters

AbstractA type‐2 fuzzy logic‐based adaptive backstepping control (T2FABSC) approach is designed for an H‐bridge inverter. This inverter has an LC filter to decrease the level of total harmonic distortion (THD) that can affect the efficiency of the system. Reduction of THD and stability insurance of the filter are challenging trade‐offs, tackled here by a controller design. The performance, however, is not suitable for actual applications under a wider range of disturbances, and the parameters need to be adjusted once more for more dependable operations. Backstepping control is given a Lyapunov definition‐based adaptive mechanism that can improve this scheme's stability and robustness in the face of numerous disturbances. Additionally, the system is viewed as a “Black box” without the need for a precise mathematical model, which might lead to a lighter computing burden and simpler implementation. Moreover, a fuzzy type‐2 structure is adopted that can optimize the gains of the adaptive Backstepping controller (ABSC) in challenging conditions. The antlion optimization algorithm is employed to optimize the parameters of the membership functions in the fuzzy system, hence improving the performance of the controller. In addition, compared with different optimization algorithms, it can more quickly and accurately locate the best solutions. Finally, the findings of both the simulations and the experimental outputs are examined, proving the T2FABSC's significant robustness and faster dynamics in a variety of challenging circumstances.

Comparative study of single-phase multilevel cascaded transformerless inverters with different modulation methods

This paper presents an in-depth exploration of a single-phase multilevel cascaded H5 (CH5) transformerless inverter employing both phase-shifted PWM (PS-PWM) and level-shifted PWM (LS-PWM) methodologies. A comparative analysis is conducted with the conventional multilevel inverter (MLI) topologies, specifically the cascaded H-bridge (CHB) and H5 inverter configurations. The investigation delves into the impact of modulation index variations, load fluctuations, and modulation methods on the inverter's operational performance.While switches in the CHB-MLI operate continuously at the carrier frequency state using PS-PWM and LS-PWM methods, the CH5-MLI exhibits a unique behavior with some switches toggling at high frequency, while others synchronize with the grid frequency. The CH5-MLI topology demonstrates efficiency improvements and a reduction in total harmonic distortion (THD). Notably, employing the LS-PWM method yields more significant efficiency enhancements and THD reduction compared to the PS-PWM method. To analyze power loss characteristics under diverse operating conditions, the PLECS simulation environment is leveraged for calculating conduction and switching losses.The application of phase-shifted and level-shifted carrier-based pulse width modulation strategies to high and low-frequency switching switches results in minimized output harmonics, elevated operator safety, and enhanced overall reliability and efficiency. This work contributes significantly to the field by offering a detailed exploration of the CH5-MLI topology's dynamic behavior, modulation strategies, and their collective impact on performance metrics such as efficiency, THD, and power losses.

Multifaceted Functionalities of Bridge-Type DC Reactor Fault Current Limiters: An Experimentally Validated Investigation

With the ongoing expansion and interconnection of electrical power systems, alongside the rapid proliferation of renewable distributed generations (DGs), the short-circuit extent in the power grid is experiencing a significant rise. Fault current limiters (FCLs) have been introduced in an effort to address this issue, ensuring the robustness and sustainability of expensive power system components when confronted with short-circuit faults. Among the various types of FCLs, bridge-type DC reactor fault current limiters (BDCR-FCLs) have emerged as one of the most promising options. While BDCR-FCLs have shown excellent properties in limiting harmful short-circuit currents, they are also advantageous in other respects. This paper investigates the supplementary functionalities of BDCR-FCLs as a multifaceted device towards the enhancement of the quality of supplied energy in terms of total harmonic distortion (THD) reduction, power factor (PF) correction, peak current reduction for nonlinear loads, and soft load variation effects, as well as their capability to limit fault current. To this aim, the capabilities of BDCR-FCLs have been studied through various simulated case studies in PSCAD/EMTDC software V5.0.1, in addition to experimental tests considering an AC microgrid connected to a DC system. The experimental and simulation investigations verify the superior multifaceted functionalities BDCR-FCLs introduce in addition to their excellent fault current-limiting capabilities. The results show that PF improved by 6.7% and 7%, respectively, in simulation and experimental tests. Furthermore, the current THD decreased by 20% and 18% in the simulation and experiment, respectively.

Power hardware in the loop methodology applied in the integration of wind energy conversion system under fluctuations: a case study

ABSTRACT In this paper, a power hardware in the loop (p-HIL) validation of a wind energy conversion system (WECS) interconnected into the balanced or unbalanced grid is presented. WECS power is obtained from wind fluctuations of the Yucatan Peninsula, Mexico, and transferred through the DC-AC power electronic converter (PEC). A robust control law based on a simple PI regulator and phasor analysis is proposed, having advantages, such as continuous power generation, operating both under balanced and unbalanced grid conditions; total harmonic distortion (THD) reduction less than 3%; power factor (PF) correction close to the unit; balanced grid currents; a simple mathematical analysis. The main objective is to keep the WECS connected to the electrical grid even in the presence of unbalanced three-phase voltages, including contributions such as: i) VDC ripple reduction; ii) Balanced currents; iii) Sinusoidal currents; iv) Free of Sequence calculation; v) Free of dq0 or αβ Transforms; vi) Simple PI Loop control; and vii) Experimental Validation. The WECS efficiency and robustness are assessed by a complete mathematical examination, validated by the simulations in MATLAB-Simulink®, and support with experimental results through the real-time simulator Opal-RT Technologies®, a low-scale laboratory prototype, and p-HIL methodology. The results present a DC link voltage constant at 75 V and optimal and reliable power integration with an efficiency of 95%.

Multi-objective based Hybrid Artificial Intelligence Controlled Parallel Inverter in Islanded and Grid Connected Operations

Background: The Integration of non-conventional energy systems (NCES), like solar, wind, etc., into the grid with power electronic devices is adapted to meet the demand. Parallel connection of inverters (PCI) is an efficient method to boost power handling capacity, reliability, and system efficiency. However, the main drawback is the unequal power sharing among the inverters while using the conventional droop control technique (CDC). In addition, the circulating currents (CC) flow between these PCI, leading to common mode voltage (CMV), current waveform distortion, and reduction in the system's overall performance. Objectives: This work consists of a photovoltaic system (PVS) and battery energy storage system (BES) as the distributed generation (DG) unit to voltage source inverter (VSI) 1 and 2. The multi- objectives of the suggested work are (a) the equal power/load sharing among two inverters, (b) effective minimization of CC and the CMV, (c) maintaining constant DC-link (DCL) voltage during different solar irradiation and constant temperature, and (d) the reduction in total harmonic distortion (THD) of load current. Methods: A novel approach related to the enhanced droop control (EDC) method with an adaptive neuro-fuzzy hybrid controller (ANFHC) was suggested here to overcome the above issues. The performance analysis of the suggested technique was done in the Matlab/ Simulink platform with islanded and grid-connected modes for different loads. Results: A comparative analysis with the available methods like the proportional integral controller (PIC) and sliding mode controller (SMC) was carried out to exhibit the viability of the developed control technique. Conclusion: This study focused on the operation and control of a PCI with ANFHC in islanded and grid-connected modes to address issues such as uniform power sharing and reduction of CC and CMV.

Utilizing Artificial Neural Network For the Regulation Of Electric Springs In Renewable Systems

Now a days the research work is going on to improve the performance of electric springs (ESs) by integrating a current source inverter (CSI) and a neural network controller. A new ES configuration that includes CSIs is introduced to enhance ES functionality. This configuration is accompanied by a control strategy that involves direct current control and mitigation of harmonic distortion, like the methods used in active power filters (APFs). By transitioning from voltage source inverters (VSIs) to CSIs and integrating a neural network controller, a significant reduction in total harmonic distortion (THD) can be achieved. The paper presents two distinct control loops, each equipped with proportional-integral (PI) controllers. One loop is focused on regulating the Critical load voltage (CL voltage), while the other is specifically designed for reactive power compensation.

Minimizing Total Harmonic Distortion of 7-Level Packed U-Cell Multilevel Inverter Using Whale Optimization Algorithm

This paper presents an innovative study introducing a novel design for a single-phase, 7-level inverter. The design combines the modified pulse width modulation (MPWM) technique with the compact packed U-cell (PUC) topology. We evaluate this inverter's performance through comprehensive simulations in the MATLAB Simulink software. Multi-level inverter (MLI) technology is crucial for high-power, medium-voltage energy control. However, using numerous semiconductor switches in traditional MLI setups poses challenges at higher voltage levels, including increased size, costs, and losses. To address these issues, our study proposes a transformative approach, emphasizing reducing active switches within the multi-level inverter architecture. Consequently, we introduce an innovative 7-level PUC-MLI design. This configuration not only reduces harmonic distortion but also addresses cost concerns. Strategically manipulating semiconductor switch sequences significantly enhances the inverter's operational efficiency. A notable contribution is our inventive method to reduce total harmonic distortion (THD) in the inverter's output voltage, achieved through a whale optimization algorithm (WOA). Implementing this algorithm substantially lowers THD levels. Importantly, this approach's effectiveness extends to various inverter topologies and levels, offering a substantial THD reduction without additional expenses.

Total Harmonic Distortion Reduction in Multilevel Inverters through the Utilization of the Moth–Flame Optimization Algorithm

This paper shows the implementation of the Moth–Flame Optimization algorithm in a Cascade-H multilevel inverter with five and seven levels to determine the optimal switching sequence of the inverter’s semiconductor devices. The algorithm was coded in Matlab software, and the obtained switching sequences were implemented in a Cascade-H multilevel inverter laboratory prototype, where the output voltage waveform was obtained using a digital oscilloscope. The experimental Total Harmonic Distortion was obtained using a power quality analyzer. The experimental results show the improvement of the Total Harmonic Distortion in the voltage output. These results were compared with other papers in the literature with different metaheuristic methods concerning the same modulation. These findings demonstrate the feasibility of employing the Moth–Flame Optimization Algorithm to significantly reduce the Total Harmonic Distortion, obtaining a lower value than most analyzed papers.

Design and Performance Analysis of a Neural Network Sliding Mode based Hybrid Controlled Islanded Micro-Grid

The micro-grid fed shunt voltage source converter, also known as a smart Artificial neural network and sliding mode controller (ANN-SMC) based hybrid system, is developed during this research for solar system, wind and battery storage connected shunt filter. Here, phased locked loop utilization is avoided by the self-tuning filter (STF). Move over, apart from producing phase synchronization, STF also distinguishes between the fundamental and harmonic components. Total harmonic distortion (THD) reduction and steady voltage across dc link during load variations with short settling times under both grid and island settings are the key goals of the recommended approach. Four scenarios with various combinations of loads, solar radiation, and wind speeds under islanding conditions are used to illustrate the effectiveness of the study.

Empirical analysis of power quality using UPQC with hybrid control techniques

The Unified Power Quality Conditioner (UPQC), composed of both parallel active filters (PAF) and series active filters (SAF), recognized as a crucial device for enhancing the overall power quality of the system. In context, different control methods are employed to evaluate the performance of UPQC. This study aims to explore the performance of four distinct control techniques: dq, pq, Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) in hybrid combinations to manage both PAF and SAF in UPQC device. Four different hybrid cases are developed for addressing three power quality problems: harmonic distortion, voltage sag, and swell to evaluate the performance of these control techniques. The results revealed a significant reduction in Total Harmonic Distortion (THD) for hybrid ANFIS-ANN control method, achieving a THD value of 4.26 % for load voltage and 0.08 % for source current after compensation in comparison with other methods. Furthermore, this paper concludes by recommending the most suitable combination of control techniques for specific applications.

PLL-based Enhanced Control of Boost PFC Converter for Smart Farming Lighting Application

Controlled environment farming has become an attractive solution to increase the food production with limited use of resources. LED lights are often used in this type of farming to increase plant yield. LED lights are dc load, whereas the grid provides ac power. This necessitates the use of power factor correction (PFC) converter as an interface between the grid and the lights. This paper proposes an innovative control method for the boost PFC converter, where an advanced phase-locked loop scheme is developed that can eliminate measurement dc offset and provide harmonic robust estimation of the grid voltage fundamental component. The applied nonlinear control uses the existing two-loop control architecture. Based on a baseline PI controller, a nonlinear function is added to make the controller react faster when it is far from the reference and vice-versa. Comprehensive simulation studies are conducted to assess the performance of the proposed method under various challenging test scenarios. Compared to the baseline method, the proposed technique achieved 42%∼65% reduction in total harmonic distortion depending on the test cases, which makes the technique a suitable candidate for improving the operational efficiency and, consequently, the running cost of a smart farming lighting system on an industrial scale. Results show the effectiveness of the proposed method over the conventional counterpart.

Sensorless Single-Switch PFC Converter Fed Brushless Direct Current Motor Ceiling Fan

This work deals with the reduction in total harmo-nics distortion, power input, and a supply power factor correction (PFC) of permanent-magnet brushless direct-current motor (PMBLDCM) ceiling fan (CF) to get reduced bills for the consumers. To address these supply power-quality issues in the existing PMBLDCM-CF, a single-stage, single-switch boost-flyback power-factor-correction-converter (S4BF-PFCC) is employed at the front-end. The front-end PFCC is designed in discontinuous conduction mode, which offers inherent supply PFC. The high-frequency-transformer (HFT) auxiliary-voltage is utilized as a feedback to get the controlled PFCC voltage output (VDC), and with this controlled VDC, CF speed is controlled. This method eliminates the required DC-link sensor or sensing circuitry. Moreover, the back-EMF sensorless-control is used to eliminate the Hall sensors and their auxiliary supply. The speed control with a variable output voltage of front-end PFCC allows an inverter to work at a commutation frequency, which offers low switching losses and improves CF efficiency. This CF system is modelled and simulated in MATLAB/Simulink. Its simulation and test results are compared to validate the design. The supply current harmonics distortion of CF meets the IEC standard 61000-3-2.

Application of ANFIS to Minimize Total Harmonic Distortion in Brushless DC Motor

Abstract: Total harmonic distortion provides direct impact on power quality in distributed systems. The work presents reduction of Total harmonic distortion (THD) in Brushless DC motor (BLDC) using adaptiveneuro controller. The configured controller is provided with a rule base, input and output membership functions. The BLDC motor is modelled in MATLAB-SIMULINK with load variation that have direct impact on the functioning of a system. The parameters include load, resistance and inertia of BLDC motor. The work results are obtained after simulating BLDC system under different load configurations. The conclusion is provided with the calculation of THD so produced using Adaptive neuro configured controller

Improved Power Sharing and Energy Management Platform in Microgrid Considering Stochastic Dynamic Behavior of the Electric Vehicles

In this study, an improved model of optimal power sharing and energy management as well as total harmonic distortion (THD) control in AC microgrids in order to control the voltage and frequency parameters by considering the random behavior of electric vehicles (EVs) is presented. The proposed model is developed based on the primary and secondary controller. The primary controller is planned with the purpose of optimal power-sharing, reduction of feeder's impedance mismatch and also THD reduction. The primary controller is modeled with the hybrid Event-Triggered approach and virtual impedance method. The secondary controller has been modeled using the particle swarm optimization (PSO) algorithm with the aim of reducing the power distribution error and optimizing the virtual impedance parameters, as well as considering the participation of EVs in the stochastic power flow equations. In addition to comparing the performance of the proposed model with conventional methods, it has also been compared with other meta-heuristic methods. The results of this have been verified in two software environments (MATLAB/Simulink) and experimental setup (dSPACE model 1202) in different scenarios and also the stability of the proposed model based on the Nyquist stability criterion, the Root Locus method and small signal analysis has been presented.

Performance Analysis of Harmonic-Reduced Modified PUC Multi-Level Inverter Based on an MPC Algorithm

Renewable and distributed energy generation includes wind turbines, fuel cells, solar cells, and batteries. These distributed energy sources need special power converters in order to connect them to the grid and make the generated power available for public use. Solar energy is the most readily available energy source; hence, if utilized properly, it can power up both domestic and industrial loads. Solar cells produce DC power, and this should be converted to an AC source with the help of inverters. A multi-level inverter for an application is selected based on a trade-off between cost, complexity, losses, and total harmonic distortion (THD). A packed U-cell (PUC) topology is composed of power switches and voltage sources connected in a series-parallel fashion. This basic unit can be extended to a greater number of output voltage levels. The significance of this design is the reduced use of power switches, gate drivers, protection circuits, and capacitors. The converter presented in this paper is a 31-level topology switched by a variable switching frequency-based model predictive controller that helps in achieving optimal output with reduced harmonics to a great extent. The gate driver circuit is also optimized in terms of power consumption and size complexity. A comparison of the 9-level and the 31-level PUC inverters is carried out to study the impact of the number of levels on the total harmonic distortion. The simulation results depict that the total harmonic distortion (THD) for a nominal modulation index of 0.8 is 11.54% and 3.27% for the 9-level multi-level inverter (MLI) and the 31-level modified packed U-cell multi-level inverter (MPUC-MLI), respectively. The reduction in THD is attributed to the increased number of steps in the output when using the model predictive controller.

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.