Nonlinear Loads Research Articles

Synergistic Control of Active Filter and Grid Forming Inverter for Power Quality Improvement

This paper addresses the challenges and opportunities associated with integrating grid-forming inverters (GFMs) into modern power systems, particularly in the presence of nonlinear loads. Nonlinear loads introduce significant harmonic distortions in the source voltage and current, leading to reduced power factor, increased losses, and an overall reduction in system performance. To mitigate these adverse effects, active filters are employed. The objective of this study is to investigate a synergistic approach to modeling and control in integrated power systems with GFMs, focusing on enhancing power quality and grid stability by reducing harmonic distortions through the use of voltage-source active filters. This research contributes to sustainability by supporting the reliable and efficient integration of renewable energy sources, thereby reducing dependency on fossil fuels and minimizing greenhouse gas emissions. Additionally, improving power quality and system efficiency helps reduce energy waste, which is crucial for achieving sustainable energy goals. Simulations are conducted on a 1000 kW GFM connected to a grid with a nonlinear variable load, demonstrating the system’s effectiveness in adapting to dynamic conditions, reducing harmonics, and promoting a stable, resilient, and sustainable power grid.

Improving the efficiency of a non-ideal grid coupled to a photovoltaic system with a shunt active power filter using a self-tuning filter and a predictive current controller

Introduction. Recently, photovoltaic (PV) systems are increasingly favored for converting solar energy into electricity. PV power systems have successfully evolved from small, standalone installations to large-scale, grid-connected systems. When the nonlinear loads are connected to a grid-tied PV system, the power quality can deteriorate due to the active power supplied by the PV array, there’s a noticeable decline in the quality of power delivered to consumers. Its combination with the shunt active power filter (SAPF) enhances system efficiency. Consequently, this integrated system is adept at not only powering local loads but also at compensating for reactive power and filtering out harmonic currents from the main grid. The novelty of the work describes how an operation of a small scale PV system connected to the low voltage distribution system, and nonlinear load can be achieved, the investigation aims to analyze the system’s behavior and elucidate the advantages of employing various control algorithms. These proposed algorithms are designed to ensure a unity power factor for the utility grid while prioritizing high convergence speed and robustness against load power fluctuations across different levels of solar irradiation affecting the PV modules. The purpose of this work is to enhance the dynamic performance of the SAPF by cooperatively using a self-tuning filter (STF) based instantaneous active and reactive power method (PQ) with a novel predictive current control, enhance the system resilience, ensure optimal management of the total active power between the PV system, the electrical network and the non-linear load by integrating the functionalities of the SAPF under different levels of solar irradiation and maintain the DC-link capacitor voltage constant. Methods. A novel predictive current controller is designed to generate the switching signals piloted the three phase source voltage inverter, also a novel algorithm of instantaneous active and reactive power is developed, based on STF, to extract accurately the harmonic reference under non ideal grid voltage, also the perturb and observe algorithm is used to extract, under step change of solar irradiation, the maximum power point tracking of the PV module and the PI controller is used to maintain constant the DC-link capacitor voltage of the SAPF. Results. The efficacy of the proposed system is primarily centered on the grid side, and the performance evaluation of the control system is conducted using the STF based PQ algorithm and predictive current control. In addition, comprehensive testing encompasses all modes of operation, including scenarios involving distorted voltage sources, step changes in solar radiation, and variations in nonlinear loads. Results highlight superior performance in both transient and stable states, affirming the robustness and effectiveness of the proposed controllers. Practical value. The total harmonic distortion value of the grid current for all tests respects the IEEE Standard 519-1992. References 21, tables 7, figures 25.

Research on power metering method for nonlinear loads in power system based on improved S-transform

Abstract Traditional power metering algorithms are no longer suitable for new power systems to address the issue of distorted voltage and current waveforms caused by a growing number of nonlinear loads in modern power systems. The paper proposes a power-metering algorithm based on an Improved Stockwell Transform (IST). Based on the Stockwell transform, several parameters that can control the Gaussian window are introduced to improve the flexibility of the Gaussian window. Additionally, the inequality constraint based on the energy concentration measure is used to optimally select the best window parameters, enhancing the time–frequency domain analysis capability of the IST. The study uses IST to decompose and reconstruct the voltage and current fundamental characteristic signals and distortion characteristic signals in the power system. This provides good time resolution at low frequencies and good frequency-domain resolution at high frequencies. Power metering based on unsteady voltage and current is achieved by calculating the resulting fundamental and harmonic powers, respectively. The simulation results demonstrate that the IST-based power metering method has a higher level of accuracy than the existing metering methods.

Advanced energy management scheme for fuel cell-based microgrid using self–regulated controller and switched capacitor inverter

Clean energy production is now the main challenge for sustainable future which can be addressed by introducing renewable energy sources. Fuel cells are critical in providing sustainable energy solutions by enabling efficient energy conversion in microgrids. To enhance the performance of fuel cell-based microgrids, advanced controllers and inverters are necessary to manage power quality and stability. One of the key benefits of this fuel cell is the separation of energy conversion and management, which allows independent optimization for each function of microgrid's performance, cost, or other installation considerations. The ability to individually control of each component of a microgrid can significantly impact various applications positively. Beyond their technological and economic advantages, fuel cells are highly sensitivity to microgrid's characteristics such as current quality and harmonics which creates difficulties for their design and management. Therefore, the entire microgrid must be managed by an effective energy management strategy and integration of advanced inverter topologies. This study aims to improve fuel cell efficiency and power quality within the microgrid through an advanced energy management (AEM) strategy. The proposed AEM structure is developed focusing on two key components: a self-regulated controller (SRC) and a switched capacitor multilevel inverter (SCMLI). These elements work together to mitigate the disturbances and enhance the power quality of the system. The methodology includes simulation and hardware-in-the-loop (HIL) testing under non-linear load conditions. Initial grid-side current total harmonic distortion (THD) of 28.38% was reduced to 2.19% through the proposed system. An impact analysis is also presented to demonstrates that reducing current harmonics and voltage imbalance have improved the efficiency of fuel cell to 50.18% and fuel utilization to 98.05%. The findings show that the proposed scheme significantly reduces current harmonics and improves the overall performance benchmark of the microgrid and fuel cell.

A Novel Approach for Power Quality Improvement Using D-STATCOM in Wind Integrated Distribution System

Objectives: The major goal of the proposed article is to enhance the power quality of a wind-integrated radial distribution network utilizing D-STATCOM. It is done by the appropriate allocation of wind turbine-based DGs and D-STATCOM. Methods: The multi-objective optimization problem is implemented using a novel and effective Prairie Dog Optimization (PDO) to attain the best-compromised solutions. This optimization tool is well suited for solving complex, non-linear voltage stability problems. The proposed approach is validated for the modified IEEE-13 bus highly unbalanced system using MATLAB. Findings: The findings indicate enhancements in the voltage profile, system losses, and total harmonic distortion (THD). The THD for the load current is 18%, while the THD for the source current is 2.54% for nonlinear loads using the proposed methodology. The voltage profile of 3.25% is enhanced as compared with the existing method, which is 2.15% better than the other obtainable method. Novelty: Prairie Dog Optimization (PDO) was chosen over traditional algorithms for its nature-inspired approach, simplicity, and efficacy in exploring complicated search fields. Its robust exploration and exploitation skills make it excellent for multi-modal optimization challenges. Keywords: Radial distribution system (RDS), D-STATCOM, Power quality, Prairie Dog Optimization, THD

Experimental investigation of adaptive multi-generalized integrator-based controller for electronically interfaced hybrid microgrid system

This research work explores the conceptualization and evaluation of a hybrid microgrid that taps into the potential of solar photovoltaic systems, wind energy conversion systems, and battery energy storage systems. In practice, nonlinear loads pose power quality issues that significantly impact the performance of hybrid microgrids. To tackle these challenges, an adaptive multi-generalized integrator (MGI) filter is proposed. This filter extracts the fundamental signal from the distorted utility grid voltages. It features a pre-filter with a DC-off set rejection loop, effectively minimizing the DC-offsets from the distorted grid voltages. This facilitates the distribution of active power generated by the hybrid microgrid's sources while simultaneously addressing various power quality problems. In addition, a dynamic power management control approach enhances grid resilience by operating the hybrid microgrid in grid-connected and islanding modes. It provides uninterrupted and high-quality power supply to consumers during grid outages. The performance of this filter is comprehensively assessed through numerical simulations in MATLAB®/Simulink® environment. A real-time laboratory prototype is developed with WAVECT® WUC300 FPGA controller, demonstrating the practical application of the proposed filter. It ensures the minimum DC-offsets of 0.02V, fast convergence, and minimum oscillations. The grid synchronization and power quality index of the grid currents simultaneously achieve a THD of 2.82 %, complying with the IEEE-1547 and IEEE-519 standards. Importantly, the proposed adaptive-MGI filter outperforms the conventional SOGI and LMF filters in terms of nonlinear load tracking capabilities, with a response speed of less than 200μs, thereby highlighting its practical relevance and importance.

Temperature Analysis of Single busbar With Variation of Total Harmonic Distortion in Current

Typically, busbars are used to transmit and distribute currents in a bus duct system. The alarming use of nonlinear loads in the industrial sector or at residentials, such as arc welding, computers, ballast lighting, variable speed drives, and so on, has resulted in the generation of harmonics in current distortion, which are uncontrolled and thus increase heat generation within the system. The research conducted in this paper focuses on the prediction of the heat distribution as well as the analysis on operating temperature of a single busbar with compliance to the British National and International Standard (BS 159: 2014) using the Finite Element Method (FEM) in COMSOL Multiphysics software. The copper busbar dimension used for this research was 20mm x 6mm x 300mm, and the fundamental Root Mean Square (RMS) current was 419.1 A. The size of this busbars can withstand the maximum current of 430 A at a maximum operating temperature of 90°C, which complies with the standard requirement. The fundamental current is injected with variation of total harmonic distortion in current up to 55% with an interval of 5%. According to the findings, the operating temperature increases in direct proportion to the increase in total harmonic distortion with the current injections. With the presence of 55% of total harmonics in the current, the current was increased up to 57.73 A from the fundamental current, while the operating temperature was increased up to 140C from the fundamental temperature. The total harmonics in current produced by the nonlinear loads could affect the operating temperature of the busbars, and this continuous operation of current flow will affect the busbars' lifespan due to the occurrence of overheating.

An analytical solution to ground stresses induced by tunneling considering ground surface boundary conditions and gravity

Accurately predicting the stress distribution around the tunnel is crucial for designing safe and economical support systems. The stress distribution is closely related to the ground stress release induced by tunneling, as well as the initial gravity stress and boundary conditions. In this study, a two-dimensional analytical model considering the ground surface boundary conditions and gravity is presented to investigate the stress field around the tunnel. Then, a numerical model was developed to validate the proposed analytical model. Finally, parametric analyses were conducted, and the limitations of the load calculation method of the code for design of shield tunnel in China were discussed. The results indicate that: (a) Tunnel excavation induces stress redistribution in the soil, resulting in a soil arching effect around the tunnel. This arching effect causes nonlinear load changes around the tunnel. (b) The soil mass around the tunnel can be divided into undisturbed and disturbed zones. Above the tunnel, the disturbance range is C-2D(C and D represent the burial depth and the tunnel diameter), while below and on both sides of the tunnel, the disturbance ranges are 4D and 1.5D, respectively. (c) Once the stress release rate reaches 0.6, a combined arching effect zone, consisting of both major and minor principal stresses, is formed in the disturbance zone above and below the tunnel. (d) The load distribution pattern calculated by the code for design of shield tunnel in China is gourd-shaped, and this calculation method is insufficient for accurately evaluating the load around the tunnel. The research results can provide a reference for the design of the shield tunnel.

Data-adaptive hybrid control for power quality improvement using H-bridge circuit

The extraction of fundamental current and controlling the H-bridge circuit, called shunt active power filter (SAPF), for power quality support have always been major research concerns. The effectiveness of a SAPF depends on its fundamental component estimation. In this context, empirical mode decomposition (EMD) is applied to SAPF operations due to its effectiveness in complex signal analysis. Being a data-driven, adaptive tool, EMD decomposes the distorted nonlinear signal into signal- and noise-dominated signals, called intrinsic mode functions (IMFs). However, its exploitation has been hindered by its mode mixing issue. As a remedy, a second-order generalized integrator (SOGI) is integrated with the EMD approach to extract the required fundamental active component of distorted load current. Thus, this work investigates the effect of an EMD-based SOGI hybrid control approach in extracting the fundamental active component of distorted load current. The MATLAB/Simulink results demonstrate the effectiveness of the proposed hybrid control strategy for nonlinear load current generated by the diode bridge rectifier. Furthermore, the simulated results are validated through a real-time simulation result using the OPAL-RT OP4510 test bench. Results are analyzed under sinusoidal and distorted voltage scenarios at the point of common coupling. The simulation results showed that the proposed hybrid control approach provides better active filtering efficiency, support for reactive power, and improved total harmonic distortion, which meets the IEEE 1547-2018 standard.

Hybrid Deep Neural Network Approaches for Power Quality Analysis in Electric Arc Furnaces

In this research, we investigate the power quality of the grid where an Electric Arc Furnace (EAF) with a very high load operates. An Electric Arc Furnace (EAF) is a highly nonlinear load that uses very high and variable currents, causing major power quality issues such as voltage sags, flickers, and harmonic distortions. These disturbances produce electrical grid instability, affect the operation of other equipment, and require strong mitigation measures to reduce their impact. To investigate these issues, data are collected from the Point of Common Coupling where the Electric Arc Furnace is fed. The following three main factors are identified for evaluating power quality: apparent power, active and reactive power, and distorted power. Along with these powers, Total Harmonic Distortion, an important indicator of power quality, is calculated. These data are collected during the full process of producing a complete steel batch. To create a Deep Neural Network that can model and forecast power quality parameters, a network is developed using LSTM layers, Convolutional Layers, and GRU Layers, all of which demonstrate good prediction performance. The results of the prediction models are examined, as well as the primary metrics characterizing the prediction, using the following: MAE, RMSE, R-squared, and sMAPE. Predicting active and reactive power and Total Harmonic Distortion (THD) proves useful for anticipating power quality problems in an Electric Arc Furnace (EAF). By reducing the EAF’s impact on the power system, accurate predictions will anticipate and minimize disturbances, optimize energy consumption, and improve grid stability. This research’s principal scientific contribution is the development of a hybrid deep neural network that integrates Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) layers. This deep neural network was designed to predict power quality metrics, including active power, reactive power, distortion power, and Total Harmonic Distortion (THD). The proposed methodology indicates an important step in improving the accuracy of power quality forecasting for Electric Arc Furnaces (EAFs). The hybrid model’s ability for analyzing both time-series data and complex nonlinear patterns improves its predictive accuracy compared to traditional methods.

Topology design of variable speed drive systems for enhancing power quality in industrial grids

In the last two decades, a rapid increase in the utilization of non-linear loads within electrical grids has been observed. Consequently, elevated levels of harmonics are found in both voltage and current waves, and adverse effects on power quality are caused. In this context, the variable speed drive (VSD) systems are considered a significant non-linear contributor. To mitigate the harmonic content in VSD systems, various techniques are explored, such as electronic smoothing inductor incorporation in the DC-link, active filters utilization at the grid side, and passive filters integration. A technique centered on the reconfiguration of the DC-link in the VSD systems is proposed in this paper to improve the overall performance of the VSD systems. The configuration comprises two transistors and two diodes, along with smoothing inductors and a capacitor to enhance power quality in the VSD systems. The utilization of three-stage sine pulse width modulation (SPWM) control technology ensures accurate control of the switches, generating optimal control signals that enhance the power quality of the voltage and current waves at the grid side. The effectiveness of the proposed approach is tested via time-domain simulation in MATLAB/Simulink under both constant and variable loading conditions and is verified using a laboratory prototype. The obtained results demonstrate a notable improvement in power quality, showcasing reduced total harmonic distortion (THD) in AC voltage and current waveforms, as well as minimized ripple factor in the DC-link when compared to existing methods.

A Quantitative Analysis of Harmonic Effects on the Accuracy of Single-Phase kWh Meters in PT. PLN (Persero) ULP Kuta

The accurate measurement of electrical energy transactions using kWh meters is crucial to prevent losses for both consumers and utilities. However, the growing prevalence of nonlinear loads can introduce harmonics into the power system, potentially affecting the accuracy of kWh meter readings. This study aimed to investigate the impact of harmonics on the measurement accuracy of analog and electromechanical kWh meters. The results demonstrate that as the percentage of Total Harmonic Distortion (%THD) increases, due to the increased use of nonlinear loads, the measurement accuracy of both types of kWh meters decreases, potentially leading to financial losses for both consumers and the utility company. Based on the study, Simulation results demonstrate this impact, with analog and electromechanical kWh meters showing significantly different billing outcomes under resistive and capacitive loads. For example, a purely resistive 300-watt load resulted in a bill of Rp. 327,870 for the analog meter and Rp. 319,343 for the electromechanical meter. In contrast, a 300-watt capacitive load resulted in bills of Rp. 84,497 and Rp. 83,707, respectively.

Synergetic UPQC Application for Power Quality Enhancement in Microgrid Distribution System: SCSO Approach

Nowadays, Hybrid renewable energy systems (HRES) are increasingly being integrated into grid-connected load systems to lower losses and boost dependability. When the HRES system is connected to the grid system to satisfy needed load demand, power quality issues arise because of imbalanced load circumstances, non-linear load, and critical load. So this manuscript proposed a synergetic Unified Power Quality Conditioner (UPQC) application for power quality enhancement in microgrid distribution systems. The Sand Cat Swarm Optimization (SCSO) technique is based on the proposed sand cat swarm optimization method. The proposed strategy's primary goal is to regulate power flow, minimize harmonic distortion in both voltage and current waveforms, and maximize UPQC. By then, the proposed method's performance has been implemented into practice on the MATLAB platform and contrasted with several currently used techniques. The proposed technique displays the low Total Harmonic Distortion (THD) and operation time in all existing approaches like Moth Flame Optimization (MFO), Genetic Algorithm (GA), Salp Swarm Algorithm (SSA), Ant Lion Optimizer (ALO), Improved Bat Search Algorithm (IBSA), Lion Algorithm (LA), Artificial Bee Colony (ABC), Atom Search Optimization (ASO) and Crow Search Algorithm (CSA). The proposed method attains THD as before UPQC is 31%, after UPQC is 3%, load current is 1.42%, and load voltage is 2%. It also achieves a low operation time of 506ms and a low settling time of 0.15s compared to the existing methods. The significant improvement in power quality metrics demonstrates the effectiveness of the proposed SCSO technique.

MODELING OF SYSTEMS WITH THE PHOTOVOLTAIC POWER SOURCE AND WATER PUMPS

The article is devoted to the calculation of systems consisting of a solar photovoltaic power source and water pumps. It is noted that such systems can be used both in households or industry, and in agriculture, in particular for irrigation. Several variants of water pumps are shown. An analysis of the operational modes where the photovoltaic power source is connected to the pump has been carried out. The selection of equipment was carried out and the expediency of using a system with an electric energy booster was indicated. A booster for providing current during start-up modes can be a capacitor, a battery of capacitors or an ionistor. Emphasis is placed on the fact that for doing of such systems it is necessary to apply modeling with the use of electrical models. It is shown that for developing of electric models of solenoid-based pumps and pumps based on rotating direct current motors, it is necessary to use the methods of electromechanical analogies. Electrical models of a photovoltaic power source and, based on analogies, a solenoid-based pump and a direct current motor-based pump with permanent magnet excitation and parallel excitation were developed. When developing electrical models, controlled sources of voltage and current were used with mutual influence of the electrical and mechanical parts of the pumps. The need to use direct current motors with parallel excitation is indicated, as they are more stable to emergency modes. It is also stated that in general, the mechanical load of the rotating part of motors is non-linear and depends on the number of revolutions of the shaft. A nonlinear resistance that models a nonlinear mechanical load is shown, and it is noted that the higher-order nonlinearity is insignificant. Conclusions are drawn and further development in the direction of the use of digital technologies is outlined.

Flow memory effects on the nonlinear hydrodynamic load of an ROV in translational maneuvering

This paper describes experimental and numerical investigations of the flow memory effect on the nonlinear hydrodynamic load response of a work-class remotely operated vehicle (ROV) under surge, sway, and heave impulse motions. The hysteresis loops of the dynamic drag coefficients during impulse motion tests are analyzed by comparing them with those obtained in steady drag tests. The areas of the loops and differences between the maximum and minimum dynamic and steady coefficients are used to quantify the flow memory effect. A novel unsteady hydrodynamic model for ROVs in translational maneuvering is established. This model considers the flow memory effect in terms of the unsteady hydrodynamic load response obtained from impulse motion response tests. The results given by the unsteady model are found to be in good agreement with those from CFD simulations. The unsteady hydrodynamic characteristics (including the asymmetric forces, force magnitude, and phase delay), motion amplitude, and frequency effect on the hydrodynamic forces of the ROV are analyzed by comparing the unsteady model results with those obtained from the steady model, revealing the rules governing the flow memory effect.

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.

Economic management of microgrid using flexible non-linear load models based on price-based demand response strategies

Demand response programmes are used in microgrid research without considering the different price elasticity of distinct load types. To evaluate the impacts of demand response efforts, it is necessary to utilise a mix of nonlinear and linear models for creating load-responsive models in a manner that is realistic. With an aim to address this gap in research, an exhaustive technoeconomic investigation is being conducted to determine the effect that price-dependent demand response programmes have on the optimal scheduling of microgrids when linear and nonlinear load models are present. The flexible elasticity model is used to accurately describe how customers respond to changes in electricity price. Four load models, including exponential, hyperbolic, linear, and logarithmic, were constructed for each demand response programme. Rime is a newly created physics-based algorithm that has been deployed to handle the anticipated energy management problem that the microgrid may be experiencing. To evaluate the efficacy of the proposed strategy, four case studies based on grid price and participation scenarios have been carried out. The findings from our research are notably impactful, revealing an 8 % reduction in energy consumption when applying the critical peak price (CPP) load demand model. This efficiency gain translates into a notable enhancement in the load factor, increasing from 0.83 to 0.86, and a significant drop in overall generation costs from $25,463 to $21,823 under optimal conditions. These results vividly illustrate the practical value of our proposed research work, showcasing their ability to generate substantial energy savings and cost efficiencies in microgrid operations. The improvements in operational efficiency and cost-effectiveness underscore the potential of these models to refine microgrid management, delivering both economic and performance gains that are crucial for advancing sustainable energy solutions.

Robust Control Scheme for Optimal Power Sharing and Selective Harmonic Compensation in Islanded Microgrids

In power systems, nonlinear loads cause harmonic distortion, adversely affecting sensitive equipment such as induction motors, power electronics, and variable-speed drives. This paper presents a novel control strategy that integrates with existing hierarchical control systems to mitigate voltage imbalances and harmonic disturbances in AC-islanded microgrids. The proposed method utilizes selective harmonic order filtering through multiple second-order generalized integrators (MSOGI) to extract negative, positive, and harmonic order components. The distributed generation (DG) unit control mechanism is designed to immediately correct voltage imbalances and harmonic disruptions, distributing the compensatory load evenly to rectify real and reactive power imbalances and harmonic disturbances. The microgrid’s control architecture primarily includes droop controllers for real and reactive power of positive sequences, voltage and current regulation inner control loops, an additional loop for correcting imbalances and harmonics, and secondary controllers to maintain voltage magnitude and frequency at nominal levels, ensuring high-quality voltage at the point of common coupling (PCC). The effectiveness of this approach is demonstrated through simulation results on the MATLAB/Simulink platform, proving its ability to effectively mitigate voltage imbalances and harmonic issues with the total harmonic of voltage reduced to approximately THDv = 0.5% and voltage unbalance factor (VUF) within approximately 0.1%.

Application of Artificial Intelligent Techniques for Power Quality Improvement in Microgrid System

This paper focuses on modeling, control and power quality improvement of a microgrid connected system. This last was designed as a multi-converter system with Wind Turbine driven Permanent Magnet Synchronous Generator, and lithium ion Battery Storage Energy System. These sources are connected by a continuous bus to a nonlinear load through a DC /AC converter and three-phases multi-functional voltage source inverter. Where, wind systems are considered as primary power resource, and the grid is used for the effect of consumption of the overage power available from sources, when the battery has been fully charged. Multi Functional Voltage Source Inverter is used to ameliorate the performance of the proposed system, guaranteeing both reactive power and harmonic compensation. Moreover an intelligent control by fuzzy logic control algorithm are managed In order to extract the maximum power from wind turbine, to guarantee an effective storage management, this about the DC side. For the AC side a direct power control strategy with fuzzy logic algorithm have been used. The simulation of the system solution is carried out in Matlab/Simulink. The obtained simulation results show that the technique of fuzzy logic furnish the best solution in term of robustness, optimization performance, low THD and fast dynamic response.

Output Voltage Harmonics Mitigation in Static Frequency Converter for Shore to Ship Power Connection Supplying Nonlinear Loads using Multi-frequency Quasi Resonant Controller

Output Voltage Harmonics Mitigation in Static Frequency Converter for Shore to Ship Power Connection Supplying Nonlinear Loads using Multi-frequency Quasi Resonant Controller