Power Quality Challenges Research Articles

End-to-end deep learning on classification of neutral-to-ground voltage in secondary distribution systems

Neutral-to-ground voltage (NTGV) abnormalities in secondary distribution systems (SDS) pose significant power quality (PQ) challenges, including safety hazards, power losses, and equipment damage. Despite their importance, these abnormalities remain relatively understudied. Accurate classification of NTGV events is crucial for effective mitigation strategies. Existing research primarily relies on machine learning (ML) models trained on manually extracted features from simulated or real-world signals. This paper introduces a novel end-to-end deep learning approach that leverages Gate Recurrent Units (GRU) to bypass manual feature extraction, directly utilizing real-world signals from three NTGV event categories: ground fault, lightning strike, and normal conditions. This is first time that GRU has been used for NTGV classification using raw data. The model's generalizability is assessed through 5-fold cross-validation. A comparative analysis with baseline models and traditional ML techniques demonstrates the proposed model's superior performance and computational efficiency due to its ability to directly process raw data.

Performance analysis of hybrid metaheuristic assisted collateral FO controller for HRES system integrated UPQC

Due to the fluctuating characteristics of the environment, it is advisable to connect a minimum of two renewable energy sources (RES) to the grid to mitigate unreliable power supply. The integration of Hybrid Renewable Energy Storage (HRES) with nonlinear loads introduces harmonics and other power quality issues, which are significant concerns for both utility providers and customers. Power quality challenges, such as real power fluctuations, voltage interruptions, and reactive power imbalances, can be mitigated through the use of a Unified Power Quality Conditioner (UPQC). For optimal performance, the series and shunt compensators within the UPQC rely on precise PWM signals to control the converters' outputs. These signals are correctly tuned by controllers using updated algorithms. The paper develops an optimized Hybrid Metaheuristic assisted Collateral Controller for the improvement of the 3-phase HRES system-based Distribution Grid incorporated with UPQC. It consists of a Fractional order Proportional Integral derivative (FOPID) controller combined with a proportional integral (PI) controller. As a consequence, the DC link voltage regulation and controller optimization are achieved with the optimal tuning of gain parameters by using a hybrid Metaheuristic Algorithm named Amplified Slime Mould with WildeBeest Herd Optimization (ASM-WHO) Algorithm. The optimization of the weights (W1 and W2) and parameters of the Collateral Fractional Order Controller is achieved using an innovative hybrid metaheuristic method that combines the Wildebeest Herd Optimization (WHO) and Slime Mould Algorithm (SMA). The proposed system is implemented in MATLAB Simulink to analyze the compensation efficiency during voltage sag/swell. The proposed controller showcases robust performance, emphasizing its potential for enhancing power quality and distribution stability in Three-Phase Hybrid Renewable Energy Storage systems integrated with UPQC, outperforming or matching the performance metrics of conventional methods such as PI, FOPID controller, FOPID-PI with various optimization algorithms (CSO,SOA, WHO, SMA, AQO, HBA). The settling minimum and maximum of 170.5668 and 189.4736 for the proposed FOPID-PI controller with ASM – WHO is notably superior to that of the controller without optimization, the proposed collateral controller method (using SOA or CSO), WHO optimization, and the PI controller, improving by 1.7 %, 13.78 %, 1.338 %, and 13.66 %, respectively. The ASM-WHO algorithm shows robust performance and improved convergence, as validated by benchmark function tests, and surpasses competing algorithms.

Optimizing dynamic voltage restorers with Bee Optimization Algorithm for enhanced power quality in modern hydro turbine grids

ABSTRACT This study explores the optimization of dynamic voltage restorers (DVRs) within hydro turbine systems using the Bee Optimization Algorithm (BOA), focusing on enhancing power system stability and quality through advanced control strategies. Emphasizing total harmonic distortion (THD) minimization, the research addresses power quality challenges prevalent in hydroelectric power generation. Detailed simulations demonstrate how BOA effectively reduces THD, optimizing DVR performance in response to grid disturbances typical in renewable energy integrations. Findings validate the BOA's efficacy in improving voltage stability and underscore the potential of bio-inspired algorithms for smart grid applications in hydro settings. This approach not only supports the reliability of hydroelectric power systems but also opens new avenues for employing multi-objective optimization techniques to advance DVR functionality, contributing to the sustainable management of energy infrastructures.

Optimal design of hybrid green energy powered reduced switch converter based shunt active power filter using horse herd algorithm

Renewable energy sources are playing a leading role in today's world. However, integrating these sources into the distribution network through power electronic devices can lead to power quality (PQ) challenges. This work addresses PQ issues by utilizing a shunt active power filter in combination with an Energy Storage System (ESS), a Wind Energy Generation System (WEGS), and a Solar Energy System. While most previous research has relied on complex methods like the synchronous reference frame (SRF) and active-reactive power (pq) approaches, this work proposes a simplified approach by using a neural network (NN) for generating reference signals, along with the design of a five-level reduced switch voltage source converter. The gain values of the proportional-integral controller (PIC), as well as the parameters for the shunt filter, boost, and buck-boost converters in the WEGS and ESS, are optimally selected using the horse herd optimization algorithm. Additionally, the weights and biases for the neural network (NN) are also determined using this method. The proposed system aims to achieve three key objectives: (1) stabilizing the voltage across the DC bus capacitor; (2) reducing total harmonic distortion (THD) and improving the power factor; and (3) ensuring superior performance under varying demand and PV irradiation conditions. The system's effectiveness is evaluated through three different testing scenarios, with results compared against those obtained using the genetic algorithm, biogeography-based optimization (BBO), as well as conventional SRF and pq methods with PIC. The results clearly demonstrate that the proposed method achieves THD values of 3.69%, 3.76%, and 4.0%, which are lower than those of the other techniques and well within IEEE standards. The method was developed using MATLAB/Simulink version 2022b.

Analysis and improvement of power quality in the onboard electrical power systems within a self-propelled floating crane

This research addresses electromagnetic compatibility and power quality (EMC and PQ) challenges in shipboard electric power systems (SEPS) with dynamic positioning (DP) capabilities, focusing on the self-propelled floating crane (SPFC) “EXPERT 3.” Our goal is to enhance methodologies for evaluating power quality indicators (PQI) related to voltage and current waveform distortions, specifically in converter-based propulsion complexes (CBPCs) featuring variable-frequency regulated asynchronous drives (VFDs). We investigate harmonic current and voltage distortions, reactive power generation, and power factor (PF) in SEPS “EXPERT 3″ during the operation of VFDs with conventional semiconductor power converters (SPCs). A refined MATLAB model considers equipment and cable network parameters, validating distortion indicators at ship synchronous generators (SGs). PQI compliance with international maritime standards is verified at the point of common coupling (PCC) for various VFD configurations with pulse width modulated (PWM) SPCs and filter-compensating devices (FCDs). We propose an improved controlled FCD (CFCD) incorporating a resonance filter (RF) and a controllable reactor compensator (CRC). CFCD efficiency in various VFD configurations is experimentally validated. We analyze harmonic distortions of voltage and current, including high-frequency (HF) commutations in VFDs with input thyristor-based rectifiers (TBRs), considering parasitic ”phase-hull“ capacitances of cable line segments (CLS). Our study examines harmonics in CBPC-based SEPS in two sub-frequency ranges: low-frequency (LF) − 0 to 2 kHz and high-frequency (HF) − 2 kHz to 500 kHz.© 2017 Elsevier Inc. All rights reserved.

Integration of Distributed Generations and electric vehicles in the distribution system

Power quality challenges are a major problem these days because of the significant increase in load demand and the existence of various reasons for disruptions in the distribution system. A voltage sag or a decrease in the magnitude of the line voltage can be brought on by rapid fluctuations in load or distribution system issues. Enhancing the grid current profile, reducing grid voltage sag, and improving other performances can all be achieved through the combination of electric vehicles with distribution generation systems. In this paper, the integration of Distributed Generation with Electric Vehicles in the distribution system has been done to enhance system performances such as true power loss index, imaginary power loss index, voltage deviation index, short circuit current index, cost function, and environmental impact reduction index for 16 bus distribution system in constant impedance, constant current, and constant power load models, or ZIP load models through proper location, sizing, coordinated controlling, and types of Distributed Generation and Electric Vehicle pairs for both charging and discharging modes by adopting Hybrid Genetic Algorithm - Monte Carlo Simulation optimization methodologies. This study's primary goal is to determine the optimal distribution generation and electric vehicle pairing to improve the aforementioned parameters, which will assist researchers in their future planning. Researchers, industry professionals, scientists, and individuals working with Distributed Generation and Electric vehicles in the smart grid will find this statement to be of great use.

A Mathematical Framework for Simultaneous Voltage and Frequency Regulation in Distributed Generator (DG) Grid-Interfaced Systems

Recent advancements in distributed generation (DG) systems interfaced with microgrids necessitate robust regulatory mechanisms to manage inherent power fluctuations, particularly from renewable sources like photovoltaics. These fluctuations can significantly impact the stability and efficiency of microgrids. This paper introduces a novel mathematical framework for simultaneous voltage and frequency regulation, aimed at addressing power quality and stability challenges in DG-grid interfaced systems. Utilizing a combination of algebraic topology and dynamical systems theory, we develop a model that incorporates an adaptive virtual frequency-impedance control loop. This mathematical approach allows for the analytical examination of the stability properties of the system and the design of control strategies that guarantee optimal operational thresholds. We extend the conventional droop control mechanisms with a rigorously defined Simultaneous Voltage and Frequency Correction Scheme (SVFCS), providing a theoretical underpinning that supports experimental observations. The efficacy of the proposed model is validated through numerical simulations that demonstrate adherence to the IEEE 519 standard, ensuring reduced harmonic distortion and enhanced system reliability. Our results highlight the potential for these mathematical methods to provide foundational insights into the control and optimization of microgrid operations.

A Joint Logarithmic based nonlinear Adaptive filter for load balancing in electric power distribution system

When nonlinear loads are introduced to a distribution system, various power quality challenges emerge, such as load unbalance, harmonic distortion, and reactive power mismatch. This study presents a novel solution utilizing a joint logarithmic hyperbolic cosine adaptive filter-operated distribution static compensator to mitigate these issues. The cost function of the adaptive filter is designed to be smooth for minor errors and resilient to significant errors. The proposed control technique computes fundamental active and reactive currents, generating reference signals for the distribution static compensator. A comparative analysis with conventional adaptive control techniques is also conducted. The distribution system undergoes comprehensive testing under various dynamics to ensure compliance with IEEE-519 standards. Real-time simulation-based experiments are employed to showcase the algorithm's performance.

A dSPACE-based implementation of ANFIS and predictive current control for a single phase boost power factor corrector

This paper presents an innovative control scheme designed to significantly enhance the power factor of AC/DC boost rectifiers by integrating an adaptive neuro-fuzzy inference system (ANFIS) with predictive current control. The innovative control strategy addresses key challenges in power quality and energy efficiency, demonstrating exceptional performance under diverse operating conditions. Through rigorous simulation, the proposed system achieves precise input current shaping, resulting in a remarkably low total harmonic distortion (THD) of 3.5%, which is well below the IEEE-519 standard threshold of 5%. Moreover, the power factor reaches an outstanding 0.990, indicating highly efficient energy utilization and near-unity power factor operation. To validate the theoretical findings, a 500 W laboratory prototype was implemented using the dSPACE ds1104 digital controller. Steady-state analysis reveals sinusoidal input currents with minimal THD and a power factor approaching unity, thereby enhancing grid stability and energy efficiency. Transient response tests further demonstrate the system’s robustness against load and voltage fluctuations, maintaining output voltage stability within an 18 V overshoot and a 20 V undershoot during load changes, and achieving rapid response times as low as 0.2 s. Comparative evaluations against conventional methods underscore the superiority of the proposed control strategy in terms of both performance and implementation simplicity. By harnessing the strengths of ANFIS-based voltage regulation and predictive current control, this scheme offers a robust solution to power quality issues in AC/DC boost rectifiers, promising substantial energy savings and improved grid stability. The results affirm the potential of the proposed system to set new benchmarks in power factor correction technology.

Assessment of Power Quality Enhancement in a Grid-tied PV Network via ANN-based UPQC

Background: Microgrid is the recent decade terminology that surpasses the long-run issues associated with the public and utility grids. Among the renewable energy sources, solar PV units have gained greater importance owing to their huge potential availability and laidback operating characteristics on technological grounds. Conversely, it offers pollution-free electricity and perhaps the dependability is volatile in most situations. The literature study accumulates the foresaid setback and presents the fluctuation-less and controlled standard quality of power outputs. Objective: The aim of this particular research is to propose an assessment of Power Quality enhancement in a Grid-tied photovoltaic (PV) network via ANN-based UPQC. The novel idea behind this proposed approach is the UPQC component which deliberately regulates and controls the power system to achieve higher levels of power quality, ultimately meeting the recent IEEE standards. Method: This particular research enhances the performances of UPQC employed in the microgrid unit by replacing the traditional PI controller with a multi-layered feed-forward-type ANN controller for the current regulation of the series active filter. Additionally, a training algorithm for the ANN controller is built, trained and simulated via MATLAB/Simulink platform. The ANN-based UPQC is proposed to alleviate the power quality challenges like sag and swell in voltage, harmonic distortion, the time required for voltage compensation, and power factor. Therefore, UPQC is equipped to enrich the standard of power transfer at the point of common coupling inside the power frameworks, respectively. Result: Finally, the simulation results are presented to validate the operation of the grid-tied PV network via an ANN-based UPQC system. To show the enriched performance of the proposed topology, a comparative analysis is made with PI controller-based UPQC, and outcomes infer to be in agreement with the theoretical discussions. Also, the ANN-based proposed approach reduces the restoration time and THD as well under both sag and swell conditions, respectively. Conclusion: In this articulated work, a PV power system network with a DC-DC converter and three-phase inverter is employed for grid integration. The peak power extraction is ensured via a DC-DC converter with an incremental conductance algorithm. Both UPQCs are analysed and experimented via MATLAB/Simulink platform with inconstant nonlinear loads to investigate the indices mentioned above and corroborate the same within the operating regions.

Investigations on solar PV integration and associated power quality challenges in distribution systems through the application of MCS and GA

In the forthcoming decades, significant advancements will shape the construction and operations of distribution systems. Particularly, the increasing prominence of photovoltaic (PV) systems in the power industry will impact the security of these systems. This study employs Monte Carlo Simulation (MCS) in conjunction with genetic algorithm (GA) and differential evolution (DE) to address uncertainties. The probability density functions (pdf) for total voltage harmonic distortion (UTHD), individual voltage harmonic distortion (UIHDh), and RMS voltage (URMS) have been determined for utilization in chance constrained framework. In addition, the uncertainty effects of PV systems on grid losses for various solar radiation conditions are also investigated. Specifically, the paper aims to evaluate these impacts within the context of stochastic limits. The PV system sizing problem has been addressed inside the distribution system using a chance-constrained framework. A key contribution is the integration of GA, DE, and MCS into a cohesive approach, and the study evaluates the benefits of this approach through an analysis of outcomes derived from the stochastic method. The simulation results illustrate the advantages of the proposed stochastic GA methodology.

Hybrid optimal-FOPID based UPQC for reducing harmonics and compensate load power in renewable energy sources grid connected system.

Integration of renewable energy sources (RES) to the grid in today's electrical system is being encouraged to meet the increase in demand of electrical power and also overcome the environmental related problems by reducing the usage of fossil fuels. Power Quality (PQ) is a critical problem that could have an effect on utilities and consumers. PQ issues in the modern electric power system were turned on by a linkage of RES, smart grid technologies and widespread usage of power electronics equipment. Unified Power Quality Conditioner (UPQC) is widely employed for solving issues with the distribution grid caused by anomalous voltage, current, or frequency. To enhance UPQC performance, Fractional Order Proportional Integral Derivative (FOPID) is developed; nevertheless, a number of tuning parameters restricts its performance. The best solution for the FOPID controller problem is found by using a Coati Optimization Algorithm (COA) and Osprey Optimization Algorithm (OOA) are combined to make a hybrid optimization CO-OA algorithm approach to mitigate these problems. This paper proposes an improved FOPID controller to reduce PQ problems while taking load power into account. In the suggested model, a RES is connected to the grid system to supply the necessary load demand during the PQ problems period. Through the use of an enhanced FOPID controller, both current and voltage PQ concerns are separately modified. The pulse signal of UPQC was done using the optimal controller, which analyzes the error value of reference value and actual value to generate pulses. The integrated design mitigates PQ issues in a system at non-linear load and linear load conditions. The proposed model provides THD of 12.15% and 0.82% at the sag period, 10.18% and 0.48% at the swell period, and 10.07% and 1.01% at the interruption period of non-linear load condition. A comparison between the FOPID controller and the traditional PI controller was additionally taken. The results showed that the recommended improved FOPID controller for UPQC has been successful in reducing the PQ challenges in the grid-connected RESs system.

Meta Heuristic Algorithm Based Novel Dstatcom Architecture for Power Quality Improvement

Electric utility systems are increasingly favoured as local energy systems due to their ability to integrate renewable energy, improve energy efficiency, and enhance the resilience of the power grid. However, while these benefits are significant, they also present certain complexities related to control and power quality (PQ). PQ is crucial within utility systems to ensure the proper functioning of connected devices and the overall health of the system. Therefore, both voltage quality and current quality are of utmost importance. Control strategies combined with advanced power electronics devices (PED) provide a robust framework to address PQ challenges. This paper introduces a novel approach for constructing a distributed Static Synchronous Compensator (DSTATCOM) utilizing innovative 125-level asymmetric multilevel DC link inverters to enable multilevel operation. A modified 125-level multilevel inverter aimed at enhancing power quality is proposed herein. By employing a minimal number of components, this inverter can generate 125-level voltages per phase, serving as a DSTATCOM to address power quality issues such as sag, swell, and harmonics. Bidirectional DC-DC converters are employed for purposes other than just providing power to the inverter's DC connections replacing DC sources. Additionally, the Coati Optimization Algorithm (COA), a newly introduced metaheuristic approach inspired by observed behavioural patterns in coatis in their natural habitat, is presented. COA is designed to emulate two primary behaviours of coatis: (i) their hunting strategy when pursuing iguanas and (ii) their evasion tactics when confronted by predators. To validate the effectiveness of the Coati Optimization algorithm, simulation is carried out with Matlab Simulink, and the outcomes of the simulation for the proposed scheme are provided in this paper. The efficacy of Solar-PV integrated 125-level asymmetric multilevel DC link inverter in enhancing power quality by adhering to the IEEE-519 Standards is demonstrated.

Examining Power Quality Challenges in Photovoltaic-Grid Integration: A Critical Review

With the massive growth of photovoltaic (PV) installations worldwide, the impact of integration between PV and the grid is becoming a serious issue and requires immediate attention. This is due to the intermittent power that the PV itself generates. The quality of the power can affect the stability of the system, the protection equipment, and the energy efficiency, which imposes a financial issue. This literature review will present the most frequently encountered problems when PV integrates with the grid, namely power quality issues, particularly on the distribution network. Problem-solving will also be presented as a reference for future PV development. It discusses several ways to handle power quality problems, depending on the factors influencing power quality. One of the proven ways is to use a modern inverter equipped with features that suit the system's needs. However, the discussion in this paper is limited to the issues of power quality and voltage generated by PV integrated into the grid. Future studies can discuss other technical issues, such as protection, feeder losses, and other problems that may arise in the future.

Energy Storage Systems: Technologies and High-Power Applications

Energy storage systems are essential in modern energy infrastructure, addressing efficiency, power quality, and reliability challenges in DC/AC power systems. Recognized for their indispensable role in ensuring grid stability and seamless integration with renewable energy sources. These storage systems prove crucial for aircraft, shipboard systems, and electric vehicles, addressing peak load demands economically while enhancing overall system reliability and efficiency. Recent advancements and research have focused on high-power storage technologies, including supercapacitors, superconducting magnetic energy storage, and flywheels, characterized by high-power density and rapid response, ideally suited for applications requiring rapid charging and discharging. Hybrid energy storage systems and multiple energy storage devices represent enhanced flexibility and resilience, making them increasingly attractive for diverse applications, including critical loads. This paper provides a comprehensive overview of recent technological advancements in high-power storage devices, including lithium-ion batteries, recognized for their high energy density. In addition, a summary of hybrid energy storage system applications in microgrids and scenarios involving critical and pulse loads is provided. The research further discusses power, energy, cost, life, and performance technologies.

Control and mathematical design of PV-based renewable energy systems for LCL-SR filter-based power quality improvement

Power quality challenges arise when photovoltaic (PV) systems are integrated into power networks. This research work examines the control and mathematical design of an LCL-SR (series resistance) filter for power quality improvement in PV-based sustainable energy systems to meet this difficulty. Power quality may be improved via an LCL filter in grid-connected systems. A non-linear load-connected PV system incorporates a variety of power electronics controllers, including an MPPT controller, battery controller, and inverter current controller, which introduce harmonics into the grid. A passive filter, LCL-SR, is suggested for PV applications that interact with voltage source inverters and the utility grid or electric load to reduce harmonics. A detailed mathematical modeling is presented to design an LCL-SR filter, and its performance is evaluated under different load conditions in terms of THD (Total Harmonics Distortion) and efficiency. LCL-SR filter has 4.32% THD but in the case of LCL filter with parallel R is less THD, which is 3.61%. In terms of efficiency and THD LCL-SR is best among all compared filters which have THD is 4.32% along with an efficiency is 75.95%. The results are compared without a filter, and different configurations of LCL-SR are simulated to show the effectiveness of the proposed filter for PV & residential applications.

Research on Grid-connected Voltage Improvement Technologies for High-penetration Photovoltaic Power Generation

The degradation in power quality due to the high penetration of grid-connected photovoltaic (PV) systems is a critical issue that urgently needs to be addressed in the field of renewable energy generation. Solar PV systems typically lack mechanical inertia, which means that they are unable to provide additional mechanical inertia to maintain voltage and frequency stability when the power system is subjected to external disturbances. Therefore, to ensure stable operation of the power system, alternative measures need to be relied on to maintain voltage stability. This article first analyzes the mechanism of voltage fluctuations when photovoltaic power generation is connected to the grid. It then delves into the challenges of power quality brought about by the grid integration of renewable distributed generation systems, as well as the current research status of mainstream voltage improvement technologies, customized power devices, and energy storage systems. Finally, the paper presents recommendations for improving grid voltage quality, enhancing the stability and reliability of the power system, and promoting the widespread application of renewable energy in power systems.

Investigation and Reduction of Harmonic in Grid Connected PV Fed DSTATCOM System

The utilization of a photovoltaic-based distribution static compensator (PV-DSTATCOM) stands out as a prominent solution for addressing energy demand deficits and power quality challenges within contemporary power systems. This article focuses on enhancing the performance of PV-DSTATCOM to facilitate grid integration and elevate power quality standards. In the envisioned system, the power from the photovoltaic array is harnessed through the utilization of the sliding mode control, ensuring the extraction of maximum power. The performance of the PV-DSTATCOM is analyzed by using a Packed U cell 5 inverter. The control signals for the voltage-source inverter are generated using PQ control scheme. The efficacy of the proposed system is substantiated through MATLAB simulation results. The outcomes presented in this article highlight the accomplished improvement in the performance of PV-DSTATCOM, ensuring concurrent advancements in current THD.

Distributed Generation (DG) system using COPRAS method

Distributed Generation (DG) system. Distributed Generation (DG) power systems, Expansion of power systems in remote areas, and Very recently as a sustainable way of electrification popular. Depletion of conventional fossil fuels, Fuel price volatility, and emissions Awareness environment about reduction, Due to this its demand is increasing. DG systems have additional power quality challenges. There are many types of DG power sources that produce electrical power with different voltages at various frequencies. RES-Based Distributed Generation (DG) Systems are conventional energy systems In finding new modern solutions for planning have contributed Widespread use of DG is old and Defines new views, Current delivery system The only way to deal with the project Calling for more complex defenses. COPRAS (Complex Proportionality Assessment) is very Multiple criteria used in decision-making methods is one. This technique is different Decision making by researchers Used to solve problems. Investment cost, operating cost, Primary energy consumption, CO2 emissions. Energy storage system, fuel system, Wind Solar Hybrid System, Conventional System, PV energy storage system. Involvement of Distributed Generation (DG) system PV energy storage system ranked 1st, and the Conventional system also got 5th position.

Performance Investigation of Hybrid Shipboard Microgrid using ESOGI-FLL Technique

The issue of reducing greenhouse gas (GHG) emissions from ships has garnered significant interest from stakeholders within the maritime industry. This work considers a hybrid shipboard microgrid powered by a battery energy storage (BES), solar photovoltaic array (SPVA), and diesel generator (DG) set. The enhanced second-order generalized integrator-based frequency-locked loop (ESOGI-FLL) technique synchronizes the DG set and the shore grid at different operating modes to supply uninterruptable power to loads. The propulsion motor, nonlinear service loads, DG set, and sources equipped with power-electronic inverter result in power quality challenges within a hybrid shipboard microgrid. Thus, the ESOGI-FLL algorithm is utilized for the mitigation of power quality issues of hybrid shipboard microgrid. The hybrid microgrid is modeled in MATLAB/Simulink at different operating conditions and validated on a real-time test simulator.