The increase in non-linear loads in the electrical distribution system has resulted in harmonics, which affect the power system’s stability and performance. The project focuses on mitigating the current harmonics of the system by implementing a Shunt Active Power Filter (SAPF), optimized using an Artificial Neural Network (ANN). The proposed system ensures the generation of compensating current through the Shunt Active Power Filter (SAPF), which helps in mitigating the harmonics present in the system. The project showcases the gradual improvement in power quality using different techniques for optimization in the conventional Shunt Active Power Filter (SAPF). This paper presents a comparative analysis of harmonic reduction techniques for a non-linear load system. The uncompensated system shows a Total Harmonic Distortion (THD) of 28.34%. Applying a conventional Shunt Active Power Filter (SAPF), PI-tuned SAPF, and PSO-optimized PI-SAPF reduces THD to 14.01%, 3.43%, and 1.64%, respectively. An Artificial Neural Network (ANN) further enhances the PSO-PI controller through adaptive real-time optimization. MATLAB/Simulink simulations demonstrate the proposed ANN-based SAPF achieves a THD of 1.41%, offering superior harmonic suppression compared to traditional methods. This demonstrates the significant improvement in the power quality by effectively mitigating the harmonics present in the system.

Introduction. Recently, multilevel inverters (MLIs) have been widely investigated for industrial and renewable energy systems as they are valuable in applications where they can produce clean, high-fidelity electrical signals that minimize harmonic content and distortion. Problem. Among the modulation strategies, selective harmonic elimination pulse width modulation (SHE-PWM) is highly effective, but solving its nonlinear transcendental equations requires accurate numerical methods. Goal. To improve the performance of the 7-level packed U-cell (PUC) inverter by applying the Newton–Raphson method to compute optimal switching angles for SHE-PWM, thereby minimizing total harmonic distortion (THD), improving waveform quality, and achieving a more compact and cost-effective design with fewer components. Methodology. The Newton–Raphson iterative algorithm was implemented in MATLAB/Simulink to solve the nonlinear equations of SHE-PWM, and a hardware prototype of the 7-level PUC-MLI was fabricated and tested to validate real-world performance. Results. The application of the Newton–Raphson algorithm significantly improved the system’s performance. After implementation, the THD was reduced to 13.19 % in the simulation and 18.14 % in the hardware prototype, whereas both initially exhibited considerably higher THD levels. Scientific novelty. The proposed method demonstrates the capability of the Newton–Raphson algorithm as a reliable numerical solution for selective harmonic elimination in the 7-level PUC MLI, ensuring rapid convergence and precise determination of switching angles. Practical value. The study shows that significant harmonic reduction can be achieved without additional hardware or complex circuitry, making the approach applicable to other inverter topologies and suitable for advanced power electronic and renewable energy systems. References 22, tables 4, figures 9.

Abstract This article presents a new strategy to enhance the maximum power point tracking (MPPT) method for optimal power extraction from photovoltaic (PV) panels, as well as an inverter control strategy for regulating the active and reactive power injected into the grid in a double-stage singlephase photovoltaic installation. The proposed method is based on a robust Third-Order Super-Twisting Sliding Mode Control (TOSTC).In the first stage, TOSTC is used to control the boost converter in order to ensure fast and accurate tracking of the maximum power point, even under varying environmental conditions, while reducing chattering and minimizing power losses. In the second stage, TOSTC is applied to control the inverter current, enabling precise regulation of both active and reactive power injection, and significantly reducing harmonic distortion, accordingly, improving the overall power quality delivered to the grid. The article compares the performance of the TOSTC with conventional control methods, namely the PI controller for the boost converter and the PR controller for the inverter, all implemented in the MATLAB/Simulink environment. Simulation results demonstrate the superiority of the TOSTC approach in terms of tracking speed, accuracy, and harmonic reduction. The stability of the proposed controller is validated using Lyapunov criteria, and its effectiveness is confirmed through simulations under both dynamic and steady-state conditions, highlighting the robustness and reliability of this innovative control strategy for grid-connected photovoltaic systems

Abstract The increased adoption of nonlinear loads, particularly in the renewable energy and automotive sectors, generates harmonics that directly affect electricity transmission systems, influencing the operation of the power grid and potentially leading to a significant deterioration in the quality of electrical energy, as well as socioeconomic repercussions. This means that it is essential to improve the quality of electrical energy while ensuring that nonlinear loads are integrated in a manner that is compatible with the grid. To overcome these problems, the use of active power filters is one of the most effective solutions for improving electrical power quality. In this article, we propose an integral backstepping control technique for a three-phase active power filter to improve electrical power quality by providing better harmonic compensation. The integral action integrated into backstepping improves the robustness of the system against parametric uncertainties and external and/or internal disturbances, thus ensuring the optimization of the active power filter, and consequently improving the quality of electrical energy in the network by compensating for harmonics. This control technique is compared to classic backstepping in order to verify the effectiveness of the integral action backstepping controller proposed for the APF. The results of simulations and experimental tests carried out in various cases demonstrate its performance. Our system perfectly compensates for harmonics in accordance with standards. The proposed integral backstepping controller is more robust than the classic backstepping controller in terms of harmonic distortion reduction, stability, and speed thanks to a reduced response time and minimized ripple. The results obtained demonstrate its increased performance and efficiency in improving power quality, as well as its socioeconomic impact for industries.

In this paper, an operating-mode-oriented collaborative vibration suppression methodology is proposed to suppress the vibration of permanent magnet brushless (PMBL) motors under whole open throttle (WOT) condition driven. The WOT is naturally divided into two operating modes: maximum torque per ampere at low speed and flux weakening at high speed. Then, by constructing the correlation between the key radial electromagnetic force harmonics and the d-axis demagnetization current, it was clarified that the dominant vibration sources of the two operating modes are the electromagnetic force carrier harmonics force and (0,6<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f_e</i>), (0,12<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f_e</i>) electromagnetic force harmonics, respectively. For an extensive investigation, a 48-slot, 8-pole PMBL motor is chosen as a research example. Then, the vibration suppression methods of key harmonics reduction and carrier harmonics energy shifting are proposed. Next, the performances of the optimal PMBL motors are simulated to validate the proposed methodology. Finally, a prototype is fabricated and experimented. Both simulated and test results are presented to verify the validity of the theoretical analysis and design methodology.

Harmonics, which negatively affect power quality, are among the primary problems caused by non-linear loads. These harmonics lead to distortions in voltage and current waveforms, excessive current and voltage surges, insulation failures, and malfunctions in power electronics-based equipment in industrial power systems. Therefore, the development of optimization-based harmonic filter design methods suitable for industrial applications is of great importance for improving power quality and ensuring system reliability. In this study, five different passive harmonic filter topologies (Single-Tuned Harmonic Filter, First-Order High-Pass Filter, Second-Order High-Pass Filter, Third-Order High-Pass Filter, and C-Type Filter) were optimized under a multi-criteria framework using four advanced meta-heuristic algorithms (Genetic Algorithm – GA, Particle Swarm Optimization – PSO, Differential Evolution – DE, and Grey Wolf Optimization – GWO) within a multi-criteria framework. The optimization process simultaneously minimizes three fundamental performance criteria: average total harmonic distortion (THDI_mean), the IEEE-519 standard violation penalty, and reactive power consumption (QC). Numerical analysis results show that Single-Tuned filters optimized with PSO and DE algorithms achieved the lowest harmonic distortion value (THDI_mean ≈ 0.577), while C-Type filters stood out with their low reactive power requirement (~1.9×10⁴ VAr) and superiority in suppressing third harmonics. In contrast, high-pass filters (1st–3rd order) performed worse across all algorithms. As a result, it was found that single-criterion approaches focused solely on harmonic reduction are insufficient. Instead, multi-criteria optimization, which simultaneously considers harmonic reduction, compliance with standards, and reactive power balance, offers more balanced and industrially applicable solutions. This study presents a new, comprehensive methodological framework that addresses a gap in the literature on the optimization of passive harmonic filters.

This paper presents a new (LCR) trap -LCL-RC passive filter for five level inverters utilised in grid connected PV applications. The novel filter is synthesized using the traditional LCL and LC trap-LCR configurations. A capacitor is connected across the R-C branch of the conventional LCR filter and an additional resistance is connected across the LC trap filter capacitor to improve high frequency harmonic attenuation and to decrease damping power loss. The paper brings out a comprehensive component design methodology for the developed filter which takes into account the impact of switching frequency and selection of reactive filter elements. A novel procedure for the selection of minimum inductance for the filter using particle swarm optimization technique is suggested. Further, the same technique is utilized to ensure minimum resonant peaking considering increased high frequency harmonic attenuation. A 110 V, 1 kW SPARTAN 6-XC6SLX25 processor based grid connected five level inverter connected to the developed filter is implemented. Simulation and experimental results are included to evaluate the performance of the proposed filter against various passive filter topologies that includes total harmonic distortion (THD), damping loss and switching harmonic current ripple reduction.

Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that quantifies tissue magnetic susceptibility, offering non-invasive insights into brain microstructure, including iron content and myelination. While extensively applied in adult neuroimaging, its use in pediatric populations is rapidly expanding. This systematic review aims to provide a comprehensive overview of QSM applications in pediatric brain imaging, highlighting methodological advancements, diagnostic potential, and current limitations. A systematic literature search was performed using PubMed and Google Scholar up to April 2025. Inclusion criteria were original research articles written in English, involving only pediatric populations (0-17years) and employing QSM in brain imaging. Twenty studies met eligibility criteria and were analyzed in terms of acquisition protocols, post-processing methods, study objectives, and main findings. A systematic search on PubMed and Google Scholar found 54 QSM brain studies in children; after exclusions, 20 original research papers qualified for review and were quality-checked using Quality Assessment of Diagnostic Accuracy Studies version-2 (QUADAS-2). Most studies were recent (85% in the last 5years), in Asia (55%, with China 35%), and used 3-tesla (T) MRI (80%). Typical imaging parameters: 8 echoes (TE=40ms), slice thickness=2-2.5mm, matrix often 256×256; Laplacian was the main phase-unwrapping method and variable-kernel sophisticated harmonic artifact reduction for phase data (VSHARP) the dominant background-field removal. Study aims clustered into improved detection, microstructural analysis, normative comparisons, clinical correlations, developmental patterns, and pathology tracking. QSM emerges as a valuable tool in pediatric neuroimaging, offering quantitative biomarkers for brain development, disease monitoring, and potential clinical translation. Despite promising results, challenges remain, including motion artifacts, lack of normative pediatric data, and methodological heterogeneity. Future research should focus on longitudinal designs, standardization of protocols, and integration with complementary imaging modalities. With further refinement, QSM has the potential to become an integral component of pediatric neuroradiological assessment.

Enhanced harmonic reduction and energy optimization in grid-connected photovoltaic-battery systems for improved power quality

Harmonic distortion reduction and magnetic core impact in 12-pulse diode rectifiers: a simulation and experimental study

This paper proposes an enhanced Finite Control Set Model Predictive Control (FCS-MPC) approach to optimize the performance and efficiency of grid-connected photovoltaic (PV) systems. The novelty of this study lies in applying a two-step forward prediction scheme within the FCS-MPC framework, coupled with optimized cost functions, to improve control accuracy, harmonic reduction, and transient response. A 1MW industrial-scale PV system model, based on the Oued El Kebrit power plant in Algeria, is simulated to evaluate the controller under realistic grid disturbances. Simulation results demonstrate that the proposed strategy improves efficiency from 97.63% to 97.73%, reduces voltage Total Harmonic Distortion (THDv) to 2.08%, and shortens the voltage stabilization time from 0.25s to 0.165s. Furthermore, the method ensures consistent performance during grid faults such as voltage sags and maintains grid code compliance. The proposed FCS-MPC method outperforms conventional strategies, offering a scalable and robust solution for enhancing the energy conversion and stability of large-scale PV systems.

This work begins with the initial design of an LCL filter for a 20 kW SiC inverter, and its response is experimentally analysed from the perspective of grid quality. Based on these results, a sensitivity analysis is carried out by varying the parameters of the RC branch. The objective is to identify the RC branch that achieves maximum efficiency in harmonic content reduction, as well as minimising losses. The conclusions drawn relate to the sizing of the LCL filter and the various possibilities for its optimisation. The conclusions presented have been obtained with regard to the sizing of the LCL filter and the different possibilities for its optimisation. Key words. LCL filter, SiC inverter, filter optimization, harmonic contents.

Permanent Magnet Synchronous Generators (PMSGs) combined with Cascaded H-Bridge Inverters (CHBIs) are widely adopted in wind energy systems due to their high efficiency and superior power quality. However, even five-level CHBIs retain noticeable low-order harmonic components and output ripple under nonlinear PMSG wind conditions, indicating that further refinement of switching-angle control is required to maximize performance. This paper introduces a dual optimization–prediction framework to address these challenges. The proposed method integrates the Greater Cane Rat Algorithm (GCRA) for adaptive switching-angle optimization with a Visual Relational Spatio-Temporal Neural Network (VRSTNN) for predictive control under dynamic operating conditions. By jointly minimizing harmonic distortion and forecasting system responses under varying wind and load scenarios, the framework ensures high-quality voltage output and stable operation. Across 10 independent simulation runs, the system achieved a mean THD of 2.10% ± 0.04, voltage ripple of 1.6% ± 0.12, and response time improvement from 0.035 s to 0.012 s, confirming consistent performance with low variability. MATLAB results further demonstrate reduced power losses, improved efficiency, and faster transient stabilization compared with ANN, RERNN-LSE, RPOA-DTRN, GA–PSO, and CNN-based methods. These findings highlight the potential of the dual optimization–prediction strategy as a robust and scalable solution for next-generation intelligent PMSG–CHBI wind energy conversion systems.

In this paper, a harmonic current controller based on the multiple synchronous reference frame (MSRF) is proposed to achieve stable harmonic current control in an interior permanent magnet synchronous motor (IPMSMs) at dynamic response. The structure of the controller consists of complex vector PI controllers that control the current of each frequency component connected in parallel. To ensure a stable dynamic response, controller is designed to achieve pole-zero cancellation between the plant and the resonant controller. In this process, the controller structure and gains are determined by considering the saliency and flux saturation of the plant. To consider saliency, the controller gains are applied before performing the rotational transformation into each harmonic reference frame. Additionally, considering flux saturation, the controller gains are designed with dynamic inductance and apparent inductance. The proposed controller can be applied with the same structure even to motors without saliency like SPMSMs. Experiments were conducted on a 17 kW IPMSM including 6th harmonic components, and the improvement in controller performance was verified through dynamic current response analysis.

With an increasing deployment of renewable energy generation system, the interaction between inverter-based renewable energy generation system and grid harmonics is inevitable. The output power quality of widely adopted LCL-type inverter, which is the key to achieve power transformation of inverter-based renewable energy generation system, will be deteriorated because of the grid harmonic distortion. Aiming at this problem, an impedance analysis method is adopted to analyze and compare the inherent stability and grid-voltage harmonic rejection capability of inverter with two typical control structure, when digital time delay and grid equivalent impedance are considered. Compared with the inverter with active damping structure, it is revealed that inverter with single-loop structure not only has at least treble in stability range, but also has the advantage in grid harmonics suppression. Therefore, a control strategy, which combines <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Padé</i>-based optimized grid-voltage full-feedforward and single-loop structure, is proposed for enhancing the stability and grid voltage harmonic rejection capability with a relatively simple control structure. The experimental results are consistent with the theoretical analysis, and desired PWM harmonic reduction and grid-voltage harmonics rejection performance are achieved, even in the face of the variation of digital time delay and grid equivalent impedance.

Abstract This article proposes the power quality (PQ) assessment using a deep belief-learning network (DBLN) approach-based inductor and capacitor (LC) supported distributed static compensator (DSTATCOM). This suggested DBLN controller is constituted by considering six sub networks for direct and quadrature components of three phases. Several factors like previous weight, step size, harmonic component and learning rate are associated in the DBLN learning mechanism to possess better dynamic performance. This proposed DBLN is suggested for both DSTATCOM and LC coupled DSTATCOM to showcase the proper DC link voltage regulation, which furthermore leads to providing better PQ improvement. To build a high-accuracy evaluation model LC coupling is analysed and designed by means of mathematical analysis and incorporated in the system. The proposed study is investigated by simulation and practical implementation using MATLAB/Simulink and hardware setups to improve power factor (p.f.) correction, source current harmonic reduction, voltage balancing and voltage control under various loading scenarios as per IEEE-519-2017 and EN-50160.

The increasing integration of photovoltaic (PV) systems into modern power grids poses significant operational challenges, including variability in solar generation, fluctuations in demand, degradation of power quality, and reduced reliability under uncertain conditions. Addressing these challenges requires advanced control strategies that can manage uncertainty while coordinating storage, inverter-level actions, and power quality functions. This paper proposes a unified stochastic Model Predictive Control (SMPC) framework for the optimal management of photovoltaic (PV) systems under uncertainty. The approach integrates chance-constrained optimization with Value-at-Risk (VaR) modeling to ensure system reliability under variable solar irradiance and demand profiles. Unlike conventional deterministic MPCs, the proposed method explicitly addresses stochastic disturbances while optimizing energy storage, generation, and power quality. The framework introduces a hierarchical control architecture, where a centralized SMPC coordinates global energy flows, and decentralized inverter agents perform local Maximum Power Point Tracking (MPPT) and harmonic compensation based on the instantaneous power theory. Simulation results demonstrate significant improvements in energy efficiency from 78% to 85%, constraint satisfaction from 85% to 96%, total harmonic distortion reduction by 25%, and resilience (energy supply loss reduced from 15% to 5% under fault conditions), compared to classical deterministic approaches. This comprehensive methodology offers a robust solution for integrating PV systems into modern grids, addressing sustainability and reliability goals under uncertainty.

The rapid growth of photovoltaic generation in Mexico poses electrical challenges related to power factor and power quality. This study evaluates the impact of PV systems on harmonic distortion and power factor reduction in a company with critical equipment, considering the (DOF, 2017)-(CRE, 2020) and the (IEEE, 2009). Through electrical simulation and experimental measurement, losses of information and possible economic penalties were identified according to CFE data, the results show high agreement between simulations and measurements, evidencing that incorporating SFV without prior analysis can decrease the power factor and compromise stability. Hybrid and reactive compensation solutions are proposed, highlighting the importance of previous technical studies for an efficient and safe energy transition.

Due to increased use of nonlinear loads such as variable frequency drives, uninterruptible power supplies and rectifier based devices, there is an increase in harmonic pollution which is detrimental to power quality as well as the reliability of the system. In this paper a real time method based on an HAPF is presented that reduces both small and large harmonic distortions in nonlinear distribution systems. A hybrid topology combines a tuned passive filter to aim at selective harmonic reduction and a shunt-connected active filter with a VSC to achieve wide and fast harmonic cancellation. The active filter extracts harmonics using Synchronous Reference Frame (SRF) theory and provides an accurate and fast outcome using a Proportional-Integral (PI) hysteresis current controller during the injection of current. Following the simulations in MATLAB/Simulink, it is depicted that the proposed system significantly enhances the power quality of the system by decreasing the Total Harmonic Distortion (THD) of 23.6 % to 3.1%, which is in compliance with the requirements of IEEE-519. Besides that, simulation in a prototype implemented on a TMS320F28379D DSP demonstrates that the control strategy is functional under dynamic variations of the load. The developed HAPF discovered in the work provides an outstanding harmonic mitigation, improved stability and flexibility, which determine its applicability in the industry and utilities.

Multilevel inverters (MLIs) have emerged as a foundational component in modern power electronics, particularly in medium- and high-voltage applications where conventional two-level inverters are no longer sufficient to meet performance, efficiency, and reliability standards. One of the primary motivations behind the widespread adoption of MLIs is their ability to synthesize high-quality output voltages with lower total harmonic distortion (THD), thereby improving power quality and system compatibility. This harmonic reduction is crucial in industrial and utility-scale applications, where precise voltage waveforms are essential for the reliable operation of motors, transformers, and sensitive loads. This paper introduces a novel multilevel inverter topology based on the cascaded connection of fundamental inverter modules. The proposed configuration is designed to operate efficiently in both symmetrical and asymmetrical modes, making it highly suitable for integration with renewable energy sources such as fuel cells and photovoltaic systems. In the symmetrical arrangement, each module utilizes identical DC source magnitudes, whereas in the asymmetrical configuration, unequal DC voltage levels—derived through binary or trinary progression—are employed to generate a greater number of output voltage levels using fewer components. The comparative analysis demonstrates that the proposed topology significantly reduces the number of power switches and passive components required, leading to lower power losses and enhanced overall inverter efficiency. Additionally, the total standing voltage stress on the semiconductor switches remains within acceptable limits, thereby improving reliability and operational safety compared to conventional multilevel inverter designs. The flexibility and simplicity of the proposed structure make it an ideal candidate for low- to medium-power renewable energy applications. To validate the functionality and effectiveness of the design, both simulation and experimental results are presented for 11-level, 15-level, and 19-level inverter configurations. The results confirm that the proposed inverter achieves high-quality output voltage waveforms with minimized harmonic distortion and improved performance across various load conditions.