Electrical Engineering & Electromechanics

Power system operational optimization using the kakapo optimization algorithm for dynamic economic dispatch

S. A. Alomari, A. Smerat, O. P. Malik, R. Abu Zitar, M. Dehghani, Z. Montazeri — Sat, 02 May 2026 00:00:00 +0300

Introduction. Metaheuristic algorithms are effective for solving complex power system optimization problems characterized by nonlinearity, multimodality, and high dimensionality. Nature-inspired strategies based on adaptive biological behaviors offer significant potential to enhance search efficiency and convergence reliability. The recently published kakapo optimization algorithm (KOA) is employed in this study to address the dynamic economic dispatch (DED) problem over a 24-hour horizon in multi-unit power systems. Problem. The DED problem extends conventional economic load dispatch into a multi-hour planning horizon, considering hourly load variations, generator ramp-rate limits, valve-point effects, and transmission losses. These characteristics render DED highly nonconvex and nonlinear, posing challenges to conventional and metaheuristic techniques. Maintaining a robust balance between global exploration and local exploitation is critical to prevent premature convergence or suboptimal generation schedules. Goal. To apply kakapo optimization algorithm for the dynamic economic dispatch problem, aiming to generate economically optimal and operationally feasible generation schedules over a 24-hour dispatch horizon while preserving population diversity and search stability. Methodology. KOA models two synergistic behavioral phases of the kakapo. Exploration is inspired by lek mating and acoustic signaling, where higher-fitness solutions emit stronger «calls» that probabilistically attract weaker candidates toward promising regions. Exploitation mimics freezing and camouflage strategies, performing fine-grained local adjustments around promising solutions with adaptive step sizes. KOA is applied to a standard five-unit system over 24 hours and benchmarked against nine well-known metaheuristics. Results. KOA achieves the lowest total generation cost, rapid convergence, and high robustness. Statistical performance metrics – including mean, best, worst, standard deviation, and rank – consistently favor KOA, confirming its effectiveness for multi-dimensional, multi-modal DED problems. Scientific novelty. KOA introduces a biologically inspired, self-adaptive search framework that balances exploration and exploitation without external control parameters. Practical value. The algorithm provides a reliable, versatile, and computationally efficient optimization tool for complex power system dispatch problems, with potential applications in renewable integration, multi-objective optimization, and real-time adaptive operations. References 29, tables 4, figures 2.

Three-phase pulse width modulation boost rectifier enhancement direct power control based on super-twisting algorithm

A. Ahmane, D. Sakri, S. E. Farhi, N. Golea — Sat, 02 May 2026 00:00:00 +0300

Introduction. Three-phase pulse width modulation (PWM) rectifiers are widely used in modern power conversion systems due to their high efficiency, controllability, and ability to provide high-quality energy conversion. They play a crucial role in applications such as motor drives, renewable energy integration, and power supplies, where a stable DC voltage and low harmonic distortion are essential. The conventional direct power control (DPC) method, based on a 12-sector switching table, is commonly employed for its simple implementation, reduced complexity, and fast dynamic response. Problem. Despite its simplicity and fast dynamic response, the classical DPC approach is highly sensitive to parameter variations and relies on a predefined switching table, which limits its robustness and current quality. Goal. To experimentally validate an improved control strategy for a three-phase PWM rectifier that enhances robustness and current quality by integrating the super-twisting algorithm (STA) into the conventional DPC framework. Methodology. The proposed STA-based DPC was implemented and tested on an experimental setup using a dSPACE DS1104 digital control board. Both the conventional DPC and the modified STA-based DPC were experimentally evaluated under the same operating conditions to ensure fair comparison. Results. Experimental results demonstrate that the STA-based DPC achieves a THD reduction from 11.85 % to 6.11 % and improves the stability of the DC-link voltage under parameter variations. These quantitative results confirm current quality, improved robustness and reduced chattering compared to the classical DPC. Scientific novelty. Integrating the STA into the DPC framework eliminates dependence on the predefined switching table and enhances robustness to system uncertainties. Practical value. The experimental validation confirms the feasibility and effectiveness of implementing the STA-based DPC in real-time applications, offering a reliable and high-performance solution for modern power conversion systems. References 17, tables 4, figures 19.

Application of the Newton–Raphson algorithm for enhanced harmonic reduction in seven-level packed U-cell multilevel inverters

O. A. Y. Amran, N. A. Windarko, I. Syarif, T. B. J. Gemilang — Sat, 02 May 2026 00:00:00 +0300

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.

Enhanced power quality in grid-connected wind energy systems using PI-controlled with doubly fed induction generator optimized by hybrid differential evolution and grey wolf algorithm

R. F. Abdelgoui, R. Taleb — Sat, 02 May 2026 00:00:00 +0300

Introduction. Nowadays, the most widely used wind energy conversion system in wind farms is based on a doubly fed induction generator (DFIG); it has a large speed range and can function in multiple modes. Problem. Harmonic distortion in wind energy conversion system can degrade output waveform quality, reduce power conversion efficiency. Goal. This study investigates the dynamic performance of a wind energy conversion system comprising a grid-connected load, a 13-level hybrid multilevel converter and a doubly fed induction generator (DFIG), using a PI controller. The study aims to evaluate the dynamic performance and power quality of wind energy conversion systems, and to develop a novel hybrid metaheuristic method combining differential evolution (DE) and grey wolf optimization (GWO)-based selective harmonic elimination pulse-width modulation (SHEPWM) control strategies. This method reduces total harmonic distortion (THD) and ensures compliance with IEEE 519 standards, while increasing the power transferred to the grid. Methodology. The system, which includes a grid-connected load, a 13-level converter, and a DFIG, is modeled and simulated in MATLAB/Simulink under steady-state wind conditions. Vector control via stator flow orientation was used to modify the energy quality provided by the DFIG, making the system comparable to the DC machine. Our approach was to use a PI controller in order to directly control the active and reactive DFIG power through multi-level converter then a hybrid metaheuristic algorithm combining DE and GWO is implemented to solve the SHEPWM nonlinear transcendental equations. The proposed algorithm is evaluated based on its ability to suppress lower-order harmonics and improve THD performance, these converters increase the power transmitted to the power grid by reducing harmonic content of the output voltages. Results. By using the DE-GWO hybrid method and a PI controller, lower-order harmonics were effectively removed and THD was reduced to meet IEEE 519 standards. Simulations showed an improvement in output wave quality and better energy conversion efficiency compared to conventional optimization methods. Scientific novelty of the proposed work lies in the fact that the study introduces a novel DE-GWO hybrid optimization method for PWM (SHEPWM) in 13-level hybrid multilevel converter applied to wind energy systems. Practical value. The novel method demonstrates that constant high performance in wind energy systems may be achieved by combining intelligent optimization algorithms with complex multilevel converter designs This means it can be effectively integrated into contemporary wind farms where meeting grid standards, adjusting to varying sizes, and ensuring long-term reliability are crucial. References 26, table 1, figures 19.

Comprehensive modeling of grid-connected inverters in weak grid systems

Y. Daili, R. Bentafer, N. Djaraf, A. Harrag — Sat, 02 May 2026 00:00:00 +0300

Introduction. The stability of grid-connected inverters is critical for the integration of renewable energy into modern power systems. However, this stability is significantly challenged under weak grid conditions, characterized by high impedance and low short-circuit ratios. Problem. Under such conditions, complex dynamic interactions arise between the inverter control systems, the grid, and the phase-locked loop, which is essential for synchronization. These interactions can degrade phase tracking and even lead to system instability. Such complexities render traditional models inadequate for accurately evaluating system behavior or guiding robust control design. The goal of this work is to develop and validate a compact, linearized state-space model of a grid-connected inverter under weak grid conditions, enabling stability analysis and supporting the design of robust control strategies. Methodology. Using small-signal modeling, a state-space representation of the inverter system is derived, incorporating control dynamics, grid impedance, and the power converter. The model’s accuracy is validated through detailed nonlinear simulations, ensuring strong consistency between both modeling approaches. Results. The proposed model effectively captures the interaction between inverter dynamics and weak grid characteristics. Simulation results demonstrate a high correlation with nonlinear behavior, confirming the model’s validity. Scientific novelty. Unlike existing models, this unified linearized state-space model explicitly captures cross-coupling effects among control loops and grid dynamics under weak grid scenarios. It enables more accurate stability analysis and provides deeper insights into the system’s dynamic behavior. Practical value. The model serves as a practical tool for engineers designing control systems for renewable energy integration. By enhancing controller robustness, it contributes to more stable and reliable power systems in weak grid environments. References 22, tables 2, figures 6.

Adaptive deep reinforcement learning-based control strategy for high-performance permanent magnet synchronous motor drive systems

S. Dukkipati, S. S. Nagendra, B. H. Kumar, E. Parimalasundar — Sat, 02 May 2026 00:00:00 +0300

Introduction. In recent days, electric vehicles, robotics and in many control system applications, permanent magnet synchronous motors (PMSMs) are widely utilized. Problem. Due to non-linear behavior of system, external interferences and frequent changes in parameters, conventional control techniques like direct torque control, field-oriented control and PI control, frequently experience decline in performance. Goal. This paper presents a new deep learning based reinforcement learning (RL) PMSM control approach that makes use of the twin delayed deep deterministic policy gradient (TD3) and deep deterministic policy gradient (DDPG) algorithms. These algorithms utilize actor-critic architectures to learn optimal control policies in a model-free manner, enabling adaptive and intelligent motor control. Methodology. A MATLAB/Simulink-based simulation framework is developed to train and evaluate the proposed deep reinforcement learning (DRL) based controllers against conventional PI controllers. Performance metrics, including speed tracking accuracy, torque ripple minimization are analyzed. Results. The results demonstrate that DRL-based controllers exhibit superior adaptability, robustness, and dynamic performance under varying load and speed conditions in contrast to traditional control methods. Notably, the comparative analysis reveals that the TD3 algorithm outperforms DDPG by mitigating overestimation bias, resulting in smoother torque output and more stable control actions. Scientific novelty. This paper illustrates the capability of DRL for advanced PMSM control. Practical value. Paving the way for real-time implementation in modern electric drive systems. References 25, tables 3, figures 12.

Hybrid extended Kalman filter long short-term memory framework for robust state and fault estimation in mobile robots under unknown disturbances

K. Khemiri, R. Djebali — Sat, 02 May 2026 00:00:00 +0300

Introduction. Reliable and accurate state estimation plays a central role in mobile robotics, ensuring effective localization, navigation, and control in uncertain and dynamic environments. Traditional estimation methods such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are widely used for nonlinear systems; however, their performance degrades when facing unknown disturbances or modeling inaccuracies. Problem. In real-world mobile robots, unexpected motor faults and unmeasured disturbances significantly reduce the estimation accuracy and may lead to mission failure. Classical EKF and UKF approaches rely on static models and Gaussian noise assumptions, which make them unsuitable for systems affected by unknown or time-varying uncertainties. The goal of this work is to design and validate a hybrid extended Kalman filter long short-term memory (EKF–LSTM) framework capable of achieving joint state and fault estimation for mobile robots operating under unknown disturbances. Methodology. The proposed approach combines a model-based EKF with an offline-trained LSTM neural network. The EKF performs nonlinear state estimation using physical robot dynamics and noisy Global Positioning System (GPS) measurements, while the LSTM predicts additive motor faults based on temporal data. The LSTM outputs are incorporated into the EKF as pseudo-measurements with adaptive covariance tuning, ensuring stability and robustness. Results. Simulation results demonstrate that the hybrid EKF–LSTM reduces trajectory root mean square error (RMSE) by 4.6 % and fault RMSE by 68 % compared to a standalone EKF, and by more than 50 % compared to the UKF. The framework effectively tracks abrupt fault variations and remains resilient to unknown inputs and sensor noise. Scientific novelty. Unlike existing hybrid filters, the proposed method introduces adaptive covariance fusion between EKF and LSTM estimators, enabling reliable operation under directional dynamics and unmodeled disturbances. Practical value. The proposed hybrid EKF–LSTM framework enhances fault-tolerant localization for autonomous robots, providing a scalable solution for real-time applications such as search-and-rescue operations, industrial automation, and autonomous navigation in noisy or GPS-denied environments. References 33, tables 2, figures 5.

Performance improvement of sensorless scalar and vector control for induction motor drives via an enhanced voltage model

P. D. Nguyen, M. Kuchar — Sat, 02 May 2026 00:00:00 +0300

Introduction. Scalar control (SC) and field-oriented control (FOC) are widely used in sensorless induction motor (IM) drives for their balance of performance and cost. Among estimation techniques, the voltage-model (VM) based model reference adaptive system (MRAS) is preferred in industry due to its simple structure and low computational load. Problem. Traditional VM-based MRAS schemes are highly sensitive to parameter uncertainties, especially to variations in stator resistance R_s caused by temperature changes. These variations degrade flux estimation accuracy, leading to significant speed-tracking errors, increased transients, and reduced stability in both SC and FOC. Goal. This study quantitatively evaluates how the estimation of stator resistance R_s and the dependent rotor resistance R_r affects the speed-control performance of sensorless SC and FOC under parameter mismatch. Methodology. An improved VM-based MRAS is proposed with parallel R_s estimation and R_r updated via a linear relation to R_s. Estimator stability and convergence are proven using Lyapunov theory. The estimator is integrated into SC and FOC and tested in MATLAB/Simulink under identical conditions, including a sudden 30 % increase in resistance. Speed tracking is quantified using the integral of time-weighted absolute error (ITAE). Results. Parameter estimation markedly enhances the robustness of both strategies. In sensorless SC, ITAE drops by about 66.2 % (5.512 to 1.863), indicating much lower transient oscillations. In sensorless FOC, ITAE falls by about 54 % (0.7075 to 0.323), with speed overshoot nearly eliminated (0.031). Scientific novelty. The study provides a unified quantitative comparison of sensorless SC and FOC using ITAE under identical operating and estimation conditions, revealing different levels of performance recovery with the proposed dual-resistance adaptation. Practical value. The findings guide the design of more reliable industrial IM drives, showing that while FOC retains superior dynamics, SC with estimation becomes a robust, cost-effective option for applications with significant parameter uncertainty. References 31, table 1, figures 13.

A new stator flow-oriented control method based on type-2 fuzzy logic controllers for permanent magnet synchronous motors

M. Tabbakh, R. Rouabhi, A. Herizi, N. Chami — Sat, 02 May 2026 00:00:00 +0300

Introduction. Stator flow-oriented control is currently the most widely used system in industry or in previous research for improving the quality of mechanical power generated by permanent magnet synchronous motors (PMSM). Problem. However, this control is often based on PI controllers, which have shown problem limitations in terms of performance and robustness. Furthermore, these controllers are not suitable for variable-structure motors, which requires the use of new, more efficient controllers that provide robust control over both internal and external changes, such as type-2 fuzzy logic controllers. The goal of this work is to develop a stator flow-oriented control system by replacing PI controllers with type-2 fuzzy logic controllers that are robust to both external variations, such as changes in torque resistance, and internal variations, such as changes in parameters. Methodology. To implement this control on the PMSM, we maintained the similar structure of stator flow-oriented control, but replaced the PI controllers with type-2 fuzzy controllers. The results of numerical simulations performed using MATLAB/Simulink show that the stator flow-oriented control based on type-2 fuzzy logic controllers achieves an ideal response time and minimal overshoot, with an exponential error close to zero in both the transient and steady states, even with the application of external variations such as resistive torque or changes to the machine’s parameters. The scientific novelty of this work lies in replacing all the controllers in the stator flow-oriented control system with type-2 fuzzy controllers and their programming method, thus addressing the shortcomings of traditional methods. In addition, a rare type of comparative study is presented, thanks to which the effectiveness and robustness of the developed control method relative to other can be demonstrated. Practical value. The excellent results obtained with the new stator flow-oriented control method using type-2 fuzzy logic controllers suggest that it should be taught in academic circles and applied in industry. References 30, tables 3, figures 5.

Effects of friction on the efficiency of open gradient magnetic separation in dry granular materials

O. Belguet, R. Mehasni, A. Belounis, M. Ouili — Sat, 02 May 2026 00:00:00 +0300

Introduction. Magnetic separation is one of the most effective and widely used techniques for the purification and enrichment of materials. It plays a crucial role in mineral processing, recycling, and environmental applications, where the separation efficiency depends on both the magnetic field characteristics and the physical properties of the treated materials. Problem. A major limitation of existing studies is that the frictional drag force is often neglected in magnetic separation, although it can sometimes completely prevent the separation process. Goal. To estimate and experimentally verify the effect of frictional drag force on the performance and operational limits of open gradient magnetic separation (OGMS) under dry conditions. Methodology. An integrated analytical, numerical, and experimental approach was used. The granular medium was modeled as a complex fluid where friction acted as a drag force. The coupled magnetic and dynamic equations were solved using Finite Element (FE) – Runge–Kutta (RK4) methods, and results were validated experimentally with a permanent magnet drum separator. Results. To verify the obtained results experiments were carried out on samples of a mixture of sand and iron particles with different components sizes (iron particles and sand grains) in a permanent magnet drum separator. Limited to fine granulometries, the experiments carried out confirmed the results obtained theoretically. Scientific novelty. The study introduces a coupled FE–RK4 model that explicitly integrates the frictional drag force into the particle dynamic equations, enabling accurate prediction of trajectories and operational thresholds. This provides a realistic description of dry magnetic separation behavior, which has been largely overlooked in previous models of dry magnetic separation. Practical value. The findings provide engineers with a framework for optimizing dry OGMS performance. The developed model defines the threshold separating efficient from inhibited particle capture and clarifies how frictional drag controls the operational range of magnetic separators. These insights support improved design, process adjustment, and greater reliability in dry magnetic separation. References 41, tables 7, figures 12.

Analysis of the external network parameters influence on the operating characteristics of self-excited induction generators

A. Dilmi, A. Bouzida, N. Yassa, B. Fares — Sat, 02 May 2026 00:00:00 +0300

Introduction. Self-excited induction generators (SEIGs) play a vital role in renewable energy systems, particularly in remote regions. However, their performance is highly sensitive to excitation capacitance, rotor speed and load variations, making stability and reliability key challenges. Problem. Simplified analytical models fail to capture the complex internal interactions within SEIGs, limiting the analysis of how external network variations influence their dynamics. Moreover, the gradual degradation of excitation capacitors, a common fault in practice, significantly reduces generator efficiency. The goal of this work is to analyze the influence of excitation capacitance, rotor speed and load variations on SEIG performance, focusing on gradual capacitor degradation and open-phase faults to provide guidelines for reliable and efficient design. Methodology. Finite element modeling (FEM) with ANSYS Maxwell is used to accurately simulate electromagnetic and mechanical dynamics under realistic operating conditions. Results. Simulations show how changes in capacitance, rotor speed and load greatly affect voltage and current stability. Capacitor faults and open-phase conditions cause current distortion, voltage unbalance and reduced efficiency. Scientific novelty of this work lies in the FEM-based analysis of gradual excitation capacitor degradation in SEIGs. It was determined that this degradation directly impacts voltage balance, current waveform distortion and overall efficiency. Practical value. The findings provide clear guidelines for selecting optimal excitation capacitance and load ranges, reducing costs while enhancing the reliability and efficiency of SEIGs, particularly in isolated regions. Also this study offers new physical insight and a reliable framework for generator condition monitoring and design optimization. References 24, tables 1, figures 12.

Determination of the transition resistance of detachable electrical contacts with Camital active grease

V. V. Kozyrskyi, V. Ya. Bunko, P. M. Darmoris — Sat, 02 May 2026 00:00:00 +0300

Problem. The reliability of detachable electrical contact connections is significantly reduced due to an increase in transition electrical resistance caused by thermomechanical deformations, oxidation of contact surfaces, and a decrease in the effective contact area during operation. According to the results of operational and experimental studies, failures associated with contact degradation account for up to a third of the total number of electrical installation failures. Traditional methods, in particular the use of passive conductive lubricants, mostly only slow down oxidation processes and do not ensure active restoration of the contact condition. In this regard, it is important to develop models and technical solutions capable of describing and ensuring the stabilisation of the transition resistance of electrical contacts through controlled thermomechanical processes in the contact zone. Goal. To establish the regularities and interrelationships of processes in electrical contacts through experimental research and mathematical modelling of the evolution of the transition resistance of contact connections with composite grease modified with Cu–Al–Mn (Camital) with shape memory, taking into account the interaction of electrical, thermal, thermomechanical and tribological processes in normal and emergency operating modes. Methodology. Experimental studies were performed on models of bolted contact connections of aluminum busbars using composite grease containing 5 % and 10 % Cu–Al–Mn powder by volume, as well as on control samples without grease. Long-term measurements of contact resistance were carried out at a constant temperature and under periodic thermal loads. The theoretical study is based on a multilevel mathematical model, the numerical solution of which was carried out using implicit stable methods with parameter identification based on experimental data. Results. A decrease and stabilisation of contact resistance was established when using composite lubricant, most pronounced at a Cu–Al–Mn powder content of 10 % by volume. A reduced model of contact resistance evolution was proposed. Scientific novelty. For the first time, a generalised mathematical model of a detachable electrical contact with active composite lubricant has been developed, which takes into account the phase transformations of Cu–Al–Mn alloy particles and the mechanism of thermomechanical destruction of oxide films. The possibility of a step-like decrease in contact resistance under impulse currents is shown. Practical value. The results obtained can be used to improve the reliability of detachable electrical contact connections, predict changes in contact resistance during operation, and justify the choice of the composition of active electrical contact lubricants. References 37, tables 4, figures 7.

Possibility of cooling the rotor of an electric traction motor by bidirectional air flows

Sat, 02 May 2026 00:00:00 +0300

Introduction. The performance reliability of electric vehicles (EVs) is an important factor in evaluating their suitability for widespread adoption. The reliability and lifespan of an EV depend on several critical factors including the motor, battery pack, controllers, and thermal management systems. The problem addressed in this paper is to cool down the rotor of permanent magnet synchronous motor efficiently using new combined cooling methods. Goal. Determination of the effectiveness of the combined rotor cooling method, which includes a bidirectional airflow circulating through a designed fan and oil circulation in the hollow shaft. Methodology. The solution was carried out using CFD (computational fluid dynamics) analysis. Results. A numerical model of a new combined cooling method for the rotor, which taking into account heat generation in the rotor and the thermal influence of the stator and bearing units, based on heat flow equations that consider its laminar or turbulent nature, was developed and studied. Scientific novelty. Based on the analysis of the rotor’s numerical model, a fan design was proposed that allows for effective heat dissipation by creating bidirectional airflow circulation. Practical value. The developed model can be used for further research on the dynamic thermal parameters of the rotor and evaluation of heat dissipation efficiency, which will optimize the heat and mass transfer processes within the motor, enhance its operational efficiency, and ensure the stability of its performance in various operating modes. References 21, tables 5, figures 17.