Electrical Engineering & Electromechanics

Application perturb and observe maximum power point tracking with interconnection and damping assignment passive-based control for photovoltaic system using boost converter

A. Toualbia — 2025-11-02

Introduction. Power generation from renewable sources, such as photovoltaic (PV) power, has become increasingly important in replacing fossil fuels. A PV system’s maximum power point (MPP) moves along its power-voltage curve in response to environmental changes. Despite the use of maximum power point tracking (MPPT) algorithms, the displacement of the MPP results in a decrease in PV system performance. Problem. Perturb & Observe (P&O) MPPT algorithm is a simple and effective algorithm, it can suffer from some drawbacks, such as oscillations around the MPP, slow tracking of rapid changes in irradiance, and reduced efficiency under temperature variation condition. The new MPPT control strategy for a solar PV system, based on passivity control, is presented. The goal of this study is to enhance the efficiency and stability of MPPT in PV systems by integrating the P&O algorithm with Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC). Methodology. The new MPPT P&O PBC strategy aims to extract maximum power from the PV system in order to improve its efficiency under some conditions such as the variations of the temperature, the irradiation and the load. IDA-PBC is employed to design a Lyapunov asymptotically stable controller using the Hamiltonian structural properties of the open-loop model of the system. Also, with minimization of the energy dissipation in boost converter of the PV system to illustrate the modification of energy and generate a specify duty cycle applied to the converter. The results with MATLAB clearly demonstrate the advantages of the proposed MPPT P&O PBC, showcasing its high performance in effectively reducing oscillations in various steady states of the PV system, ensuring minimal overshoot and a faster response time. Scientific novelty. Key contributions include methodological improvements such as dynamic adjustment of the cycle for boost converter and a new approach to partner selection, which significantly optimizes the algorithm’s performance. Practical value. A comparative analysis of the proposed MPPT controller against conventional algorithms shows that it offers a fast dynamic response in finding the maximum power with significantly less oscillation around the MPP. References 46, tables 2, figures 13.

Inverter fuzzy speed control of multi-machine system series-connected fed by a single five-phase an asymmetrical 19-level inverter with less number of switches

T. Bessaad — 2025-11-02

Introduction. 5-phase permanent magnet synchronous machines (PMSMs) are widely used in modern electric drive systems due to their superior torque density, improved fault tolerance, and reduced torque ripple. These characteristics make them ideal for demanding applications such as electric vehicles, aerospace systems, and industrial automation. Problem. Despite their advantages, conventional multi-machine systems using multilevel inverters and PI controllers suffer from sensitivity to parameter variations, high torque ripple, and increased cost and complexity due to the large number of power switches. The goal of this work is to design and validate a compact robust drive system that enables independent vector control of two series-connected 5-phase PMSMs using a reduced switch count asymmetrical 19-level inverter and fuzzy logic controllers. Methodology. The proposed system is modeled in the phase domain and transformed using Clarke and Park transformations to enable decoupled control. Mamdani-type fuzzy logic controllers are implemented for both speed and current regulation. The system is simulated in MATLAB/Simulink to evaluate performance under dynamic conditions and parameter variations. Results. The fuzzy logic controller significantly outperforms the conventional PI controller, achieving a settling time of 0.06 s versus 0.15 s, a steady-state speed error of 0.4 % compared to 1.9 %, and a torque ripple reduction of 47 %. Under robustness testing with doubled inertia, the fuzzy controller maintains stable and accurate control, whereas the PI controller fails. Additionally, the inverter achieves near-sinusoidal output with a total harmonic distortion of less than 4.5 %, and the switch count is reduced by 66 % compared to traditional 36-switch designs. Scientific novelty. This work presents the first implementation of independent vector control for two series-connected PMSMs using a single 12-switch asymmetrical 19-level inverter and model-free fuzzy logic control, offering a simpler and more efficient alternative to existing approaches. Practical value. The proposed system provides a highly efficient and cost-effective solution for electric drive applications where space, reliability, and control robustness are essential, such as in electric transportation, avionics, and compact industrial systems. References 26, tables 4, figures 9.

Optimal power flow analysis under photovoltaic and wind power uncertainties using the blood-sucking leech optimizer

B. Bouhadouza — 2025-11-02

Introduction. Optimal power flow (OPF) is a fundamental task in modern power systems, aiming to ensure cost-effective generation dispatch and efficient energy distribution. The increasing integration of renewable energy sources such as photovoltaic (PV) and wind turbines (WT), alongside conventional thermal units, introduces significant variability and uncertainty into system operations. Problem. The OPF problem is nonlinear, constrained by complex technical limits, and further complicated by the stochastic nature of PV and WT power generation. Efficiently addressing these uncertainties while maintaining system optimality remains a major challenge. The goal of this study is to solve the OPF problem in power networks that integrate PV and WT systems, while accounting for the uncertainty in their power outputs. Methodology. The stochastic behavior of PV and WT units is modeled using probability distribution functions. A novel bio-inspired metaheuristic, the Blood-Sucking Leech Optimizer (BSLO), is proposed and benchmarked against two well-established algorithms: Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). Simulations are conducted on both the IEEE 30-bus test system and a real Algerian transmission network. Results. The BSLO algorithm consistently outperforms PSO and GWO in minimizing generation cost, power losses, and voltage deviation across all tested scenarios. Scientific novelty. This work considers both single and multi-objective OPF formulations, whereas most previous studies focus solely on single-objective approaches. It integrates renewable generation uncertainty through probabilistic modeling and introduces a novel metaheuristic (BSLO). Validation on a real Algerian power grid confirms the method’s robustness and practical relevance. Practical value. The results confirm the BSLO algorithm as a promising and effective tool for solving complex, renewable-integrated OPF problems in real-world power systems, contributing to more reliable, economical, and flexible grid operation. References 48, tables 13, figures 17.

Fault-tolerant control of a double star induction machine operating in active redundancy

S. Guizani — 2025-11-02

Introduction. The operating safety of a variable-speed drive is of paramount importance in industrial sectors, such as electric propulsion for ships, rail transport, electric cars, and aircraft, where reliability, maintainability, and safety are top priorities. Problem. One solution to improve the availability of a variable-speed drive is the use of a double star induction machine (DSIM). This machine can provide active or passive redundancy. Redundancy is active if both converters operate simultaneously, and the failure of one of them does not affect system operation. Passive redundancy is passive if only one converter is operating and the 2nd is on standby; the latter will only operate if the first fails. Goal. Improving the availability of a DSIM by the operation in active redundant of the machine supply system. Methodology. Use scalar control to control the machine power system in active redundancy. Simulation results with this scalar control demonstrated the need to equip this control with a decoupling of the variables responsible for machine magnetization and torque production. Field-oriented control (FOC) is then used to ensure the reconnection of a converter after a failure for active redundancy operation, without the risk of significant torque ripples. Scientific novelty. To increase the availability of the variable speed drive, an original control strategy for reintegrating the repaired faulty inverter is implemented to allow the repaired inverter to resume operation of the drive motor. This strategy control is based on the specific use of FOC to resynchronize the output frequency of the repaired inverter with the motor speed. Results. The results demonstrated the value of vector control in each star power supply system to avoid transient over currents at the input of the 2nd converter, by synchronizing the frequency of the 2 converters to the rotor speed. Practical value. An experimental model around a DSIM is set up to validate the active redundancy operation of the system. Active redundancy provides the variable speed drive with an increase in the reliability of the variable speed drive and significantly improves the availability rate of the driven load, since the disconnection of one of the 2 converters following a failure does not affect the operation of the machine. References 17, tables 2, figures 13.

Robust fault-tolerant sliding mode control and advanced fault diagnosis for doubly-fed induction generators

N. Hamdi — 2025-11-02

Introduction. Doubly-fed induction generators (DFIGs) have become the preferred technology in modern wind energy systems due to their high efficiency and flexible variable-speed operation capabilities. Problem. Despite their advantages, DFIGs face significant challenges related to grid-connected power converters, which are susceptible to operational instability caused by voltage imbalances and electrical faults. Goal. This study aims to develop and validate a novel Active Fault-Tolerant Sliding Mode Control (AFT-SMC) strategy that integrates real-time fault diagnosis to enhance the reliability and stability of DFIG systems during grid disturbances. Unlike existing approaches, this work specifically addresses the reduction of false fault detections during transient events and improves fault characterization through spectral analysis. Methodology. The proposed control framework combines a robust sliding mode controller with a model-based fault detection and isolation system that employs adaptive thresholds and diagnostic residuals for accurate fault identification. The approach has been thoroughly tested through high-fidelity simulations under severe voltage unbalance scenarios. Results. Simulation outcomes demonstrate the superior performance of the proposed strategy in maintaining system stability under a 30 % voltage unbalance scenario. Specifically, the controller achieves a voltage recovery time of 0.28 s, compared to 0.42 s with conventional vector control, and reduces electromagnetic torque oscillations by approximately 45 %. Furthermore, the integrated spectral diagnosis method reaches a fault classification accuracy of 94.6 %, confirming its effectiveness in enabling early and reliable fault detection. These results validate the advantages of the proposed AFT-SMC framework in both dynamic response and fault resilience. Scientific novelty. The key innovation lies in the integration of a self-correcting «detect-and-adapt» mechanism that mitigates false triggers during transient grid conditions, alongside a novel spectral decomposition method for precise detection and characterization of voltage imbalances through negative-sequence component analysis. Practical value. This strategy significantly reduces operational costs at pilot wind farms and sets a new benchmark for intelligent fault management in renewable energy systems, with broad applicability to other power electronic interfaces in smart grids. References 35, figures 12.

Synthesis of combined shielding system for overhead power lines magnetic field normalization in residential building space

B. I. Kuznetsov — 2025-11-02

Problem. Most studies of power frequency magnetic field reduced to safe level in residential buildings located near overhead power lines carried out based on two-dimensional magnetic field modeling, which does not allow studying of original magnetic field shielding effectiveness in residential building edges. The goal of the work is synthesis of combined active and multi-circuit passive shielding system to improve shielding efficiency of initial magnetic field to sanitary standards level in residential building edges generated by overhead power lines. Methodology. System synthesis methodology based on vector game solution, in which vector payoff calculated based on of Maxwell’s equations solution in a quasi-stationary approximation using the COMSOL Multiphysics software. Vector game solution calculated based on hybrid optimization algorithm, which globally explores synthesis search space using Particle Swarm Optimization and gradient-based Sequential Quadratic Programming to rapidly calculated optimum synthesis point from Pareto optimal solutions taking into account binary preference relations. Results. During combined active and multi-circuit passive shielding system synthesisspatial arrangement coordinates of 16 contours of passive shield and two compensating windings, as well as windings currents and phases of active shield calculated. New scientific results are theoretical and experimental studies of synthesized combined active and multi-circuit passive shielding system efficiency for magnetic field created by overhead power lines. Scientific novelty. For the first time synthesis methodology for combined active and multi-circuit passive shielding system taking into account original field shielding effectiveness decrease in residential building edges for more effective reduction of industrial frequency magnetic field created by overhead power lines developed. Practical value. Practical recommendations for the reasonable choice of the spatial arrangement of a multi-circuit passive shield and two shielding windings of active shielding system for magnetic field created by overhead power lines are given. The possibility of reducing the initial magnetic field induction to the sanitary standards level is shown. References 42, figures 16.

Fuzzy logic-based vector control of permanent magnet synchronous motor drives under inter-turn short-circuit fault conditions

Y. Laamari — 2025-11-02

Introduction. Permanent magnet synchronous motors (PMSMs) are widely used in industrial and automotive applications due to their high efficiency and power density. Problem. However, their performance can be significantly affected by faults such as inter-turn short-circuits faults (ITSCFs) in the stator windings. These faults introduce oscillations in rotor speed and electromagnetic torque, increase total harmonic distortion (THD), and degrade the overall reliability of the system drive. Conventional field-oriented control (FOC) methods, particularly, those employing PI controllers, often struggle to maintain stability under such fault conditions. Goal. This study aims to develop and evaluate a fuzzy logic-based control strategy to enhance the fault tolerance of PMSM drives under ITSCFs conditions. Methodology. To achieve this, a mathematical model of the PMSM is developed to represent both healthy and faulty operating states. This model is integrated into a vector control framework where two types of speed controllers are compared: a conventional PI controller and a fuzzy PI controller. The proposed fuzzy logic controller is implemented within the FOC scheme and evaluated through simulation. Results. Simulation results demonstrate that the fuzzy vector control approach significantly reduces rotor speed and electromagnetic torque ripples under both healthy and faulty conditions, while maintaining stable torque output and minimizing THD. It consistently outperforms the conventional PI controller. Scientific novelty. Unlike traditional FOC methods, this study introduces a fuzzy logic-enhanced control strategy specifically designed to improve PMSM performance under fault conditions. The integration of fuzzy logic with vector control offers superior dynamic response and enhanced resilience. Practical value. The proposed approach improves the robustness and reliability of PMSM drives, particularly in fault-sensitive applications such as industrial automation and electric vehicles. This contributes to extended system lifespan and improved operational stability. References 26, tables 2, figures 13.

New adaptive modified perturb and observe algorithm for maximum power point tracking in photovoltaic systems with interleaved boost converter

M. Makhlouf — 2025-11-02

Introduction. In recent years, maximum power point tracking (MPPT) has become a critical component in photovoltaic (PV) systems to ensure maximum energy harvesting under varying irradiance and temperature conditions. Among the most common algorithms, perturb and observe (P&O) and incremental conductance (IC) are widely adopted due to their simplicity and effectiveness. Problem. Conventional P&O suffers from steady-state oscillations and slow dynamic response, while IC requires higher computational complexity and loses accuracy under rapidly changing conditions. These drawbacks limit overall tracking efficiency and system reliability. The goal of this work is the development and evaluation of a novel adaptive modified perturb and observe (AM-P&O) algorithm for a PV system with an interleaved boost converter. The proposed method dynamically adjusts the perturbation step size to achieve faster convergence and lessen steady-state oscillations to enhance tracking efficiency. Its performance is assessed through simulation with varying irradiance. It is then compared to traditional methods (P&O and IC) using quantitative metrics such as convergence time, oscillation magnitude, tracking efficiency, and computational cost. Methodology. The AM-P&O algorithm introduces an adaptive step size adjustment strategy, in which the perturbation magnitude is dynamically tuned according to the slope of the PV power-voltage curve. A detailed PV system and converter model was developed in MATLAB/Simulink, and simulations were performed under varying irradiance conditions. Performance metrics include tracking efficiency, convergence time, steady-state oscillation amplitude, and computational complexity. Results. The proposed AM-P&O achieves a better tracking, reduces convergence time by approximately 35 %, and decreases steady-state oscillations by nearly 90 % compared to conventional P&O. Under fast irradiance variations, the AM-P&O also demonstrates superior dynamic performance with lower computational burden compared to IC. Scientific novelty of this work lies in the adaptive perturbation mechanism, which balances fast convergence and reduced oscillations without increasing algorithmic complexity. Practical value. The AM-P&O provides a practical MPPT solution for PV systems, ensuring higher energy yield and improved stability in real-world applications, thereby supporting more efficient renewable energy integration into power networks. References 32, tables 8, figures 8.

A robust hybrid control strategy for enhancing torque stability and performance in PMSM drives

V. T. K. Nhi — 2025-11-02

Introduction. Recently, permanent magnet synchronous motors (PMSMs) have become essential in various high-performance applications, including electric vehicles and renewable energy systems. However, traditional control methods, such as PI controllers, often struggle to handle dynamic operating conditions and external disturbances, resulting in torque ripple and stability issues. Problem. The main issue with existing control strategies is their inability to maintain accurate torque control and system stability under fluctuating loads and varying motor parameters, which negatively impacts performance in real-world applications. Goal. This paper proposes a robust hybrid control strategy that integrates sliding mode control (SMC) with proportional resonant control (PRC), enhanced by Luenberger and Kalman observers. The goal is to improve torque stability, reduce errors, and optimize performance in PMSM drive systems. Methodology. The proposed method combines SMC and PRC to form an SMC-PRC controller, with Luenberger and Kalman observers integrated for effective load torque estimation. Results. The simulation experiments were carried out to compare the effectiveness of the proposed control strategy with that of traditional PI controllers. The results revealed that the SMC-PRC approach offers a notable improvement in overall control performance, including reduced tracking error, enhanced dynamic response, and better stability. Furthermore, the proposed method achieved faster settling times and maintained robust operation under varying system conditions. Scientific novelty. This work introduces a hybrid control approach that combines SMC and PRC with advanced state estimation techniques, providing a robust and efficient solution to PMSM control. Practical value. The proposed method is highly beneficial for applications under dynamic operating conditions, such as electric vehicles and renewable energy systems, improving system efficiency and stability. References 40, tables 7, figures 10.

Nonlinear vector control of multiphase induction motor using linear quadratic regulator and active disturbances rejection control under disturbances and parameter variations

S. E. Rezgui — 2025-11-02

Introduction. This paper introduces a hybrid control strategy for multiphase induction motors, specifically focusing on the dual star induction motor (DSIM) by integrating active disturbances rejection control (ADRC) and linear quadratic regulator (LQR). Problem. Conventional PI-based indirect field oriented control (IFOC) of DSIM drives exhibit 3 critical shortcomings: 1) sensitivity to parameter variations, such as rotor resistance fluctuations; 2) sluggish transient response during rapid speed and torque changes; 3) slow disturbances rejection, such as sudden load torque variations. The goal of this work is to achieve enhanced reliability, precision and robustness of DSIM drives in high-performance demand applications such as automotive. Methodology. The proposed hybrid control architecture is structured as follows: 1) IFOC decoupling. The DSIM’s stator currents are decomposed into 2 components using Park transformations, aligning the rotor flux vector to the d-axis. 2) The LQR is designed to optimize the outer speed/torque loop regulation by minimizing control efforts and state deviations. 3) ADRCs controllers are designed in the inner current loops. Each controller utilizes an extended state observer to estimate and compensate parameter variations and external disturbances in real time. Results. Simulations using MATLAB/Simulink validation on a 5 kW DSIM under multiple scenarios confirm the robustness of the proposed hybrid strategy. Scientific novelty. The contribution lies in the integration of ADRC and LQR in IFOC: The hierarchical fusion of ADRC (inner loops) and LQR (outer loop) uniquely leverages ADRC’s and the LQR’s real-time power to handle any disturbances and unmodeled dynamics. Practical value. The proposed technique demonstrates enhanced performances in speed’s response, sudden load torque demands and parameter variations. It exhibited high robustness even under degraded conditions such as phase faults, making this strategy ideal for high-performance applications like electric vehicles, where stability and adaptability are critical. References 31, tables 2, figures 24.

Enhanced siting and sizing of distributed generation in radial distribution networks under load demand uncertainty using a hybrid metaheuristic framework

S. S. Sabry — 2025-11-02

Introduction. Constant changes in electrical system loads lead to increased power losses and voltage drops, requiring effective strategies to improve grid performance amid changing power demands. Problem. Many studies assume constant loads when determining optimal locations for distributed generation (DG) units, when in reality, loads change throughout the day. These changes affect network performance and require efficient solutions that adapt to changes in loads demand to maintain system efficiency and stability. Goal. This research aims to optimize the locations and sizes of DG units to reduce power losses and optimize voltage profile, taking into account changes in loads hourly over a 24-hour period. Methodology. The study analyzes 24 hourly scenarios using 2 optimization techniques: the conventional particle swarm optimization (PSO) algorithm and the hybrid-dynamic PSO algorithm. A multi-objective function is adopted to reduce power losses and improve voltage profile at the same time. Results. The modified IEEE 33 bus system was used to verify the effectiveness of the proposed method. The hybrid-dynamic PSO algorithm has shown superior performance in reducing active and reactive losses compared to the traditional algorithm. It also contributed to a significant improvement in the voltage profile, demonstrating its high efficiency in dealing with changes in loads demand during time. Scientific novelty of this work lies in the integration of hourly load changes into the process of allocating DG units and using a hybrid-dynamic PSO algorithm that combines the benefits of PSO traditional and adaptation mechanisms, leading to realistic and more efficient improvement. Practical value. This methodology enhances the performance of the smart grid by reducing power losses and voltage deviation under daily load, ultimately reducing operational costs and improving grid reliability. References 28, tables 4, figures 10.

Improved speed sensorless control for induction motor drives using rotor flux angle estimation

C. D. Tran — 2025-11-02

Introduction. In the typical field-oriented control (FOC) method, the variation of machine resistance is not considered when calculating the rotor flux angle. This omission affects the accuracy of the control method during motor operation, leading to potential performance degradation. Problem. Neglecting stator resistance variations in the voltage model-based FOC technique can cause rotor flux angle estimation deviation. This inaccuracy impacts motor speed control, especially under varying operating conditions where resistance changes due to temperature fluctuations. Goal. This paper aims to improve the accuracy of rotor flux angle estimation in the voltage model-based FOC technique by incorporating a real-time stator resistance estimation process. Methodology. The proposed research integrates a model reference adaptive system to estimate the stator resistance and replaces the rated resistance value in the rotor flux angle calculation algorithm of the FOC technique. The effectiveness of the method is evaluated by using MATLAB/Simulink simulations, where the estimated resistance value is compared with the actual resistance value, and the motor speed control performance is analyzed. Simulation results demonstrate that the proposed method significantly enhances the accuracy of rotor flux angle estimation by adapting to changes in stator resistance. This improvement ensures better motor speed control performance, reducing deviations between the actual and reference speeds under different operating conditions. Scientific novelty of this research lies in integrating real-time stator resistance estimation into the rotor flux angle calculation process of the voltage model-based FOC technique, addressing a key limitation in typical FOC approaches. Practical value. By improving the accuracy of rotor flux angle estimation, the proposed method enhances the stability and efficiency of motor speed control. This ensures better performance in industrial applications where precise motor control is essential under varying operating conditions. References 27, figures 11.

Effect of short-circuit in stator windings on the operation of doubly-fed induction generators operating in a wind power system

Y. Diboune — 2025-11-02

Introduction. Wind energy has been a clean and renewable source of electricity in recent decades, making a significant addition to overall generation, and wind power is one of the most popular sources of renewable energy. Problem. Accurate modeling of wind turbine generators is critical to improve the efficiency of power systems. Doubly-fed induction generator (DFIG) stands out for its economic advantages associated with the use of frequency converters and induction machines. Increasing operating and maintenance costs of wind turbines highlight the need for early fault identification to optimize costs and ensure reliable operation. The goal of this work is to develop a simplified yet effective model for analyzing stator winding short-circuits in DFIGs operating in wind turbines. The model uses line-to-line voltages as inputs and explicitly considers the neutral-point voltage variation under fault conditions. Methodology. The problem was solved using spectral analysis, the model was implemented for 4 kW DFIG wind turbine in MATLAB to validate its effectiveness. Results. The simulation results confirm the effectiveness of the proposed approach for timely fault detection and analysis. It demonstrates computational simplicity by accurately capturing the main fault characteristics, which is preferable to traditional methods such as symmetrical components and FEM. The scientific novelty of the work lies in a methodology for modeling DFIG during stator short-circuits, integrating the effect of elevated neutral voltage during faults using line-to-line voltages in the base model. It also takes into account phenomena such as magnetic saturation, gap effects, and skin effects. The simplicity of the model makes it suitable for condition monitoring and validation of fault-tolerant control algorithms, which distinguishes it from more complex methods such as symmetrical components or the FEM. Practical value. The proposed model offers a pragmatic and reliable approach for monitoring and analyzing defects in DFIG wind turbines. Its versatility and efficiency improve the optimization of maintenance costs and reliability of renewable energy systems. References 27, tables 2, figures 8.