REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE
The journal publishes original papers in English, French, German, and Russian, representing research on power economy, electrical power, electrical engineering, electronics, information transmission, computers, control systems in electrical power, thermopower, thermomechanics, bio-medical engineering, and related problems. It reflects especially the fundamental and experimental research activity in power and communications of our country, papers presented at international conferences held in Romania, as well as the contributions of some specialists from abroad. A special part is assigned to reviewing the most relevant books, appearing in Romania and from abroad. The papers published are of a high level of the modern sciences and technique and represent original contributions to the development of contemporary power sciences. All manuscripts are strictly refereed and only papers of high quality, original, and with the application of the results, are accepted for publication. Through its topics, Revue is of concern to specialists working in research and education, doctoral candidates, and senior-year students. Revue Roumaine des Sciences Techniques, Série Électrotechnique et Énergétique is a journal of the Romanian Academy, the Engineering Section
The Publishing House of the Romanian Academy
REAL-TIME VEDIC MATHEMATICS BASED MEMORYLESS ARITHMETIC CIRCUITS VERIFICATION TECHNIQUE
This paper proposes a new method for verifying arithmetic circuit operations based on the Vedic mathematics Sutra (formulae) “Gunita Samuccaya”. According to this sutra, our proposed method verifies arithmetic operations, e.g., c = a + b, by checking whether the sum of 'a' and 'b' digits equals the sum of digits of 'c' for correct computation. In contrast to built-in self-test (BIST) schemes, our approach is simpler, eliminating traditional test pattern generators and output analyzers while achieving 100% fault coverage for simple arithmetic operations. Our system, designed in Verilog hardware description language (HDL), is real-time, memoryless, and scalable. This proposed testing method revolutionizes arithmetic circuit verification, guaranteeing the integrity of intricate digital systems where mathematical precision is vital.
Électronique et transmission de l’information | Electronics & Information Technology
DEVI POONGUZHALI SINGARAVELU DEVI POONGUZHALI
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ELECTROPERMEABILIZATION FOR ORGANIC MATERIAL – NUMERICAL MODELING
Electroporation, also known as electropermeabilization (EP), occurs when a cell's transmembrane potential exceeds a critical threshold under the influence of an electric field, corresponding to a limit value of the electric field intensity. EP depends on the distribution of the electric field, which in turn depends on and, here, determines the material's electrical properties. Some critical electric field strengths act as a “switch” for the EP, which is, to some extent, reversible. This paper aims, through numerical experiments, to unveil the effects of the electric field on the poration of an organic substance (lavender) and the thermal stability of the EP cell. The substance is assumed to be a continuous medium with electric-field-dependent material properties.
Génie biomédical | Biomedical Engineering
EFFECT OF THE LAMBDA PARAMETER ON THREE-PHASE INDUCTION MOTOR DESIGN BY ANALYTICAL AND MAGNETIC METHODS
Induction motors can be designed for powers ranging from small to considerable. Several key parameters must be considered during the design process. In addition to critical motor design parameters, there are also design parameters that are not taken into consideration and are usually taken as a fixed or average value. One of these parameters is the λ (lambda) parameter, which represents the ratio of the package length to the pole pitch. This parameter is typically specified in design books and appears to be a subject that researchers do not often study. In this study, a 7.5 kW, 3-phase squirrel-cage induction motor has been designed using the lambda value to fill the gap in the literature. The primary motivation of this study is to demonstrate how the lambda value influences the dimensions of the motor and its impact on the performance and magnetic performance of the motor. For this purpose, analytical and 2D modeling have been performed using Rmxprt and Ansys Maxwell software for motor analysis. Performance and magnetic analyses were performed. According to the results obtained, it is concluded that the lambda coefficient, which is not very important in the design process, is a very effective parameter in motor design.
Électrotechnique et électroénergétique | Electrical and Power Engineering
ARTIFICIAL INTELLIGENCE FEATURES ON OBSERVATIONS OF NONLINEAR CHEMICAL REACTOR DYNAMICAL PROCESS
This paper proposes a novel approach for enhancing the optimization of nonlinear high-gain observers by utilizing a genetic algorithm (GA) to improve state estimation precision in chemical reactors. Unlike traditional tuning methods, the GA optimally seeks optimal observer gain parameters that yield a minimum estimation error and improve convergence rates. The new method is used to benchmark a nonlinear continuous stirred-tank reactor (CSTR) model. The simulation outcomes validate that the GA-optimized observer exhibits a substantially enhanced rate of convergence and accuracy in estimating the temperature and concentration states compared to traditional methods. Additionally, the technique enables smaller dependence on physical sensors, thus promoting stronger and less expensive monitoring and control systems. The approach introduced is model-independent and applicable in real-time to an extensive class of engineering systems, including electrical and power systems. This work highlights the practical benefits of integrating metaheuristic optimization and nonlinear observer design in industrial processes.
Thermotechnique et thermoénergétique | Thermotechnics and Thermal Energy
INFORMATION SYSTEM DEVELOPMENT OF ELECTRIC CAR CHARGING STATIONS BY UNIFIED MODELLING LANGUAGE DIAGRAMS
This paper presents a high-level approach to developing an information system for electric car charging stations, utilizing a Process Layer Supply pattern. This pattern organizes activity processes, business rules, visions, and goals that support system modelling. The paper models the system's structural and behavioral aspects using UML diagrams—specifically, class, use case, and activity diagrams — via the Papyrus UML2 tool. These diagrams facilitate visualizing functional requirements, user-to-system interactions, and system components for efficient planning, development, and implementation. The model addresses the most critical gaps in an electric car charging infrastructure and optimizes the information system's operations for practical implementation. The proposed system is designed to support future developments, like integration with dynamic demand markets for flexible pricing and optimized operations. Additionally, we use pseudocode to link abstract UML models to actual implementations, ensuring the accurate transfer of system logic to the corresponding code. Since every component of the charging network is logically interconnected, a sustainable foundation for future electric car mobility is established.
Automatique et ordinateurs | Automation and Computer Sciences
AUTOMATION SYSTEM OF AN EDUCATIONAL TEST BENCH FOR NAVAL PISTON DIESEL ENGINES
The paper focuses on the custom automation system of a test bench for diesel engines used on navy ships, namely on tugboats. The test bench, with its automation system, is developed for practical training at a naval academy. The test bench aims to meet the highest standards in the education of Navy students and personnel. It facilitates undertaking practical laboratory works regarding the main constructive elements, operation, monitoring, and maintenance of four-stroke internal combustion engines, of the gearbox, as well as of the propeller load simulated by a hydraulic brake. The custom-made automation control system includes a modular cabinet with drives and automation sections, featuring a local command console for engine control and a remote command console for the entire test bench, with a large display for parameter monitoring.
Supervisory control and data acquisition
A MIXED DOPPLER SHIFT AND POLARIZATION MANAGEMENT APPROACH FOR SATELLITE COMMUNICATIONS
The rapid displacement of satellites in low Earth orbit (LEO) poses several challenges for communication with the ground segment. One of the main problems encountered is significant Doppler frequency shifts, which can disrupt signal transmission and require precise adjustments to maintain stable communications. This paper presents a software solution to effectively compensate for the Doppler shift, along with a hardware implementation to manage the two available polarizations at the station: right-hand circular polarization (RHCP) and left-hand circular polarization (LHCP). This polarization management is necessary because the demodulator used in our case possesses only a single input. This solution has been implemented in an existing S-band ground station (GS) located in Oran, Algeria. The experimental results obtained during actual passes of the ALSAT-2A and ALSAT-2B satellites, whose orbits are 180 degrees apart, were satisfactory. The implemented solution showed good results, with accuracy comparable to the estimated Doppler frequency, without any loss of telemetry at the ground segment level.
ENHANCED SPIRAL DYNAMIC ALGORITHM WITH APPLICATION TO INDUCTION MOTOR PARAMETERS IDENTIFICATION
The spiral dynamic algorithm (SDA) is a metaheuristic characterized by the setting of parameters (spiral radius and rotational angle). The drawback of all meta-heuristic methods is the premature convergence, which occurs when a trade-off between exploitation and exploration is not maintained. SDA provides a good exploitation phase because all points are attracted to the best solution. But the exploration phase is poor when the spiral parameters are set to constant values during the whole search process. To improve SDA performance and circumvent premature convergence, this paper proposes an enhanced SDA in which the parameter settings vary simultaneously according to nonlinear functions. The effectiveness of the enhanced SDA algorithm (ESDA) was proven by identifying the electrical and mechanical induction motor (IM) parameters. This is achieved using the reference model method, in which the estimated parameters correspond to the minimum of the objective function. A comparison is established between the ESDA, SDAs, genetic algorithm (GA), and particle swarm optimization (PSO). The developed program and the estimation approach are tested using simulated and measured data from an IM (1.5 kW).
MINIATURIZED AND CIRCULAR POLARIZED METAMATERIAL-INSPIRED ANTENNA FOR WIRELESS COMMUNICATION
In this paper, a miniaturized triple-band antenna is designed for wireless communication applications. The two inverted C-shaped strips are used to enhance the electric length, which improves the impedance bandwidth. The unit cell analysis of the inverted C-shaped strips indicates that the three bands are directly responsible for the negative permeability. The triangular-shaped parasitic stub is used in the ground to perturb the surface waves, which affects the CP behavior of the antenna at higher operating bands. The antenna bandwidths are obtained as follows: 2.37 GHz (2.337–2.405 GHz), 3.34 GHz (3.06–3.84 GHz), and 5.21 GHz (5.08–5.38 GHz), where the axial ratio is attained from 5 GHz to 5.35 GHz. The miniaturized size and triple-band antenna are well-suited for portable applications that require a compact design.
Circular polarized antenna; triple-band antenna; Metamaterial Inspired antenna; 5G applications; WLAN applications
TECHNO-ECONOMIC BASED OPTIMIZATION OF PHOTOVOLTAIC/BATTERY/DIESEL GENERATOR MICROGRID
The global adoption of renewable energy sources (RESs) is rapidly increasing to reduce greenhouse gas emissions. Algeria's abundant solar energy makes it an ideal location for installing photovoltaic (PV) systems. This research examines the techno-economic feasibility of an off-grid microgrid system powered by solar energy, combined with a battery energy storage system (BESS) and a diesel generator (DG), to supply electricity to the rural community of Ghars Boughoufala in Ouargla province, southern Algeria. The proposed system incorporates a PV/BESS/DG configuration with bidirectional DC and AC buses and converters. The study employs a load-following (LF) energy management strategy (EMS) to maintain consistent energy distribution and power supply. Optimization of the proposed configuration was performed using the Wild Horse Optimizer (WHO) metaheuristic. WHO's performance was compared with four cutting-edge algorithms. Results showed that WHO outperforms the other algorithms in terms of convergence speed and in minimizing life cycle cost (LCC) and cost of energy (COE), with the designed microgrid achieving an LCC of 7,229,644 USD and a COE of 0.3845 $/kWh.
A GENERALIZED MULTISOURCE SYMMETRICAL MULTILEVEL INVERTER WITH REDUCED SWITCHES
This paper proposes a generalized multisource symmetrical multilevel inverter with reduced switches. The proposed topology uses fewer switches, thereby minimizing switching losses and improving system efficiency. The salient features of this topology are the elimination of diodes and capacitors, a reduced number of switches, the ability to expand the circuit to achieve as many levels as needed, reduced total standing voltage (TSV), reduced cost, and lower Total Harmonic Distortion (THD). The phase-disposition level-shifted pulse-width modulation technique is used, and logic gates are employed to generate triggering pulses. The proposed topology is simulated in MATLAB/Simulink for 11 levels, with 5 DC sources and nine switches. The performance analysis for the resistive and inductive loads was performed. I have also provided a detailed comparison with other recent research works to demonstrate the effectiveness of the proposed system. The proposed topology is also realized using the hardware for an 11-level output.
ENHANCING THE TRANSIENT PERFORMANCES AND STABILITY OF THREE-TANK LIQUID LEVEL USING A MODIFIED PID CONTROLLER
Managing liquid levels in industrial tanks is crucial, especially for precise component mixing. Traditional PID controllers, though widely used, often exhibit slow settling times and excessive overshoot, which can affect system performance. This study proposes a fractionalized order PID (FrOPID) controller optimized using the Modified Artificial Hummingbird Algorithm (MAHA) to enhance stability and response in a three-tank system. The controller’s effectiveness is evaluated under varying valve coefficient (Kv) and tank cross-sectional area conditions. A comparative analysis with advanced metaheuristic-optimized PID controllers confirms the superiority of the MAHA/FrOPID in terms of accuracy, response speed, and robustness, making it a highly efficient solution for liquid level control.
ADVANCED CONTROL FOR PHOTOVOLTAIC-UNIFIED POWER QUALITY CONDITIONER SYSTEMS: A SIMULATION APPROACH
This paper presents the design and evaluation of a three-phase photovoltaic-unified power quality conditioner (PV-UPQC), integrating series and shunt compensators via a shared DC link. The system combines distributed generation with active power filtering, where the shunt compensator harvests PV power and compensates for harmonic currents and reactive power from nonlinear loads. Harmonic identification uses p-q theory, with experiments conducted under real solar irradiation in Algeria’s Adrar region. The shunt active power filter (ShAPF) compensates for harmonics and reactive power while optimizing PV power extraction at the maximum power point (MPP). Adaptive neuro-fuzzy inference systems (ANFIS) and sliding mode control (SMC) are combined to reduce chattering and enhance PV energy extraction. Simulations show SMC/ANFIS outperforms conventional SMC.
Unified power quality conditioner (UPQC)
Adaptive neuro-fuzzy inference (ANFIS) systems
DEEP LEARNING AND WBG DEVICES COMBINING TO IMPROVE PV SYSTEM EFFICIENCY: ANFIS-BASED MPPT CONTROLLER
With the escalating demand for renewable energy sources, photovoltaic (PV) systems have emerged as a pivotal solution for sustainable power generation. The efficacy of these systems is paramount for their widespread implementation. This research article delves into the efficiency assessment of silicon carbide (SiC) components within a boost converter integrated into a PV system. Notably, the boost converter switch is under the intelligent control of an adaptive neuro-fuzzy inference system (ANFIS) based maximum power point tracking (MPPT) controller. This innovative approach leverages AI to optimize energy extraction from PV panels, thereby enhancing overall system efficiency. The cooperation of SiC components and AI-driven control presents a novel perspective on robust and efficient PV systems. To substantiate the research, data collected from the Sidi Bel-Abès PV central is utilized to train the ANFIS. The utilization of real-world data enhances the accuracy of the predictive model, thereby increasing its applicability to practical scenarios. Integrating AI technologies with PV systems marks a significant advancement toward intelligent and adaptive energy systems.
RECONFIGURABLE INTELLIGENT SURFACE TUNED WITH NOMA FOR RESOURCE ALLOCATION
A reconfigurable intelligent surface (RIS) offers the potential benefits of 5G when combined with non-orthogonal multiple access (NOMA). As a result, the issues with distance, spectrum, and energy use worsen. Due to the limited energy supply, it is necessary to control the channel and achieve revolutionary energy efficiency that maximises both total rate and power optimisation. We jointly optimize the transmit power and optimal phase shift to mitigate the weak environment, thereby increasing the signal-to-noise ratio (SNR) and multiplexing data streams in the spatial domain. RIS arrays are used to form beams in the required directions. By decoupling the adjustable phase shift array elements, power allocation is performed using a low-complexity Dinkelbach method. The results are shown to provide practical solutions for users in different scenarios. The comparative results are shown to prove the novelty of the work and its significance.
Reconfigurable intelligent surface (RIS)
PHYSICS-INFORMED REPRESENTATION LEARNING FOR HYBRID ELECTRIC VEHICLE ENERGY MANAGEMENT
Integrating physics-based and learning systems enhances fuel cell hybrid electric vehicles (FCHEVs) for better performance control and efficient power source operation. Balancing this diverse mix is challenging, given the uncertainties and fluctuations in complex physics-based modeling. In this framework, our work has a dual purpose. Firstly, precise physics-based modeling enables the effective generation of data. This helps gather diverse data resembling real-world scenarios, aiding in drawing reliable conclusions. Several known driving cycles were utilized to generate sufficient data for the experiments and findings presented in this work. Secondly, the collected data undergoes an advanced representation learning process with adaptive functions, enhancing the interaction between learning models and the FCHEV system's physical phenomena. The effectiveness of the suggested approach is validated through a comprehensive evaluation of developed algorithms using various visual and numerical metrics. In a comparative analysis, the results illustrate the efficacy of the methodology in addressing energy management (EM) challenges in fuel cell hybrid electric vehicles (FCHEVs).
SIGNIFICANT NOTES AND NEWLY DEFINED ACCURATE TERMS REGARDING CONTROLLED LINEAR SYSTEMS
In certain instances, the conventional performance definitions can lead to misinterpretations in the control of linear systems. Hence, it becomes imperative to rectify these definitions. This paper presents new, precise definitions of performance metrics, along with significant insights into the transient and steady-state phases. Specifically addressing step responses, we refine conventional definitions of overshoot, rise time, and settling time for systems with final response values of zero. Furthermore, we give due consideration to the open-loop phase margin in stable systems. For the ramp response of controlled systems, where final values tend to infinity, we introduce new, accurate definitions of overshoot and settling time that apply in such cases. Numerous illustrative simulation examples are provided for each appended note.
POWER QUALITY EVOLUTION FOR WIND ENERGY CONVERSION SYSTEMS USING EMBEDDED Z-SOURCE INVERTER AND PERMANENT MAGNET SYNCHRONOUS GENERATOR
This study focuses on two key goals: maximising wind power and providing the system with high-quality electricity. A permanent-magnet synchronous generator and an embedded Z-source inverter are used in this setup to increase the voltage. The Permanent Magnet Synchronous Generator is employed for its unique features, including excellent performance, low weight and volume, and the fact that it doesn't require an external power source to excite its permanent magnets. The DC-link embedded Z-Source inverter is used to connect this generator to the electrical grid. Typically, the Z-Source connection requires many turns in the transformer winding; however, in this case, lower-rated windings are used for inductance instead of the transformer. Thus, the voltage gain is also balanced by the parallel capacitances. Moreover, symmetrical voltage and current distribution across the network, as well as reduced voltage stresses, are benefits of embedded technology. The recommended method, the embedded Z-Source inverter, is specifically controlled by a fuzzy logic controller that also tracks the maximum power to the wind system and reduces total harmonic distortion by 0.86%, as recorded in MATLAB. However, results were also confirmed from an experimental prototype perspective.
Permanent magnet synchronous generator (PMSG)
CONTROL AND IMPLEMENTATION OF A MINI CYLINDRICAL-PARABOLIC SOLAR CONCENTRATOR
This research presents the design and implementation of a solar concentration system utilizing a cylindrical parabolic solar concentrator. The system is designed to capture and focus sunlight onto a tube containing a heat transfer fluid. The resulting heat is harnessed to produce steam, which subsequently drives a steam turbine for electricity generation. A solar tracking mechanism ensures optimal system performance throughout the day. The core of the concentration system comprises a stepper motor integrated into the mechanical structure, with communication facilitated by an Arduino board and MATLAB. The control of the solar concentrator is implemented through two distinct strategies. The first is automatic control based on light-dependent resistors (LDRs), which are used to determine the sun's position. This data is transmitted to the control system, which enables automatic adjustment of the parabolic trough solar concentrator's orientation and positioning. The second one is a manual control based on a MATLAB graphical user interface (GUI), developed to enable manual control of the solar concentrator's stepper motor. This paper investigates the intricate relationship between control precision, error, and the number of motor steps.
WIRELESS AUTHENTICATION SYSTEM FOR INTERNET OF THINGS USING FREERADIUS AND BLOCKCHAIN
Wi-Fi networks are essential for wireless connectivity in homes, businesses, and public areas. However, many still rely on the outdated Wi-Fi Protected Access 2 (WPA2) protocol, which is well-known to have security weaknesses. These allow attackers to intercept and steal data or gain unauthorized access. While WPA3 offers better security through stronger encryption and authentication, it has not been widely adopted since many older devices do not support it. To address this challenge, we propose a decentralized authentication system that integrates a FreeRADIUS server with a locally hosted validation mechanism. We implemented a private blockchain using Hyperledger Fabric to enable distributed registration and verification of digital identities. As this system does not depend on a central authority, attackers cannot entirely compromise it by targeting single components. Our findings show that, although Hyperledger Fabric adds about 300 milliseconds to the authentication process, communication remains smooth thereafter, indicating that our approach is both practical and secure for device verification on such networks.
ENHANCED STABILITY INVESTIGATION OF HIGH-GAIN BOOST CONVERTER FOR PHOTOVOLTAIC SYSTEM
An effective DC-DC converter is recommended for use in renewable energy applications, as suggested in the study. For the design of a high-gain boost converter (HGC), switched inductor cells (SIC) and voltage multiplier cells (VMC) are utilized. VMC provides high voltage gain in the converter side, while switched inductor cells provide a constant source current. Efficiency enables the recommended converter to maintain a high voltage gain at a low duty ratio. The converter stability is achieved under state space modelling (SSM). The electromagnetic compatibility (EMC) condition of the power converter is verified using a spectrum analyzer. The power semiconductor’s electrical discharge and potential energy under steady-state conditions, the Bode plot, and the Nyquist plot are examined. Furthermore, the interface of the PV module with a high-gain converter is simulated for the specified values.
MULTI-PHASE PERMANENT MAGNET SYNCHRONOUS MOTOR USING DIRECT TORQUE ADAPTIVE FUZZY CONTROLLED
The performance of the conventional direct torque control (DTC-C) scheme, which is primarily based on switching tables or conventional proportional integral (PI) controllers, yields high ripples in torque and magnetic flux, thereby compromising the overall robustness of the system. This research proposes an adaptive fuzzy logic control (AFLC) for controlling a five-phase permanent magnet synchronous motor (5P-PMSM), incorporating the space vector modulation (SVM) algorithm. This approach aims to overcome the limitations of DTC-C schemes. The proposed AFLC-DTC-SVM method is designed to enhance the robustness, response time, and efficiency of the 5P-PMSM drive. Simulation results using MATLAB/Simulink demonstrate that the proposed method significantly reduces torque ripple by approximately 72% compared to the DTC-C technique and 51.16% compared to the DTC-SVM method. Flux ripple is also reduced by 71.42% and 33.33% compared to the DTC-C technique and the DTC-SVM method, respectively. Furthermore, the proposed technique offers robust performance against variations in machine parameters and load disturbances, thereby confirming its superiority over conventional methods.
Five-phase permanent magnet synchronous motor
EFFECT OF DEFECT GEOMETRY IN A COMPOSITE ON RELIABILITY
This work focuses on the study of the effect of the physical properties of a random-type composite material and the geometric shape of defects on the reliability analysis of an inspection device using non-destructive testing. Two types of defect geometries are considered: rectangular and triangular. A stochastic finite element method (SFEM) was used to solve the 2D electromagnetic equation in a cylindrical structure. The differential sensor recovers the impedance change signal in the fault zone. The signal is analyzed and compared for the two types of geometries. Post-processing is started to assess the reliability of our structure by determining the reliability index and the probability of failure. The results obtained for random rectangular and triangular shapes are presented, along with a comparison between the stochastic finite element method and the Monte Carlo method. A good agreement is observed. The results show that the proposed SFEM model offers post-processing in addition to analysis, compared to the Monte Carlo method, which requires numerous draws for analysis and relies on the inverse problem to determine the actual values of the physical property considered.
FIELD-ORIENTED CONTROL OF DUAL-STAR INDUCTION MACHINE WITH ENERGY QUALITY BASED ON FUZZY LOGIC
Power segmentation offers a solution to ensure service continuity and improve the quality of electrical energy. Multi-star machines powered by voltage inverters are subjected to non-sequential currents, which disturb the fundamental currents and thus deteriorate the quality of the energy supplied by these machines. In this work, a new field-oriented control (NFOC) based on a new mathematical model of the double-star induction machine (DSIM) is proposed. This new model separates the DSIM into two distinct parts (fundamental and secondary), enabling the elimination of these non-sequential currents using fuzzy logic. This also brings the control of the DSIM closer to that of classical three-phase induction machines, resulting in improved regulation and reduced computation time. The new model, along with its new control, has been validated through simulations in MATLAB/Simulink, yielding very interesting results compared to the classical DSIM field-oriented control (CFOC).
COMPARISON BETWEEN SEVERAL METHODS OF IDENTIFICATION OF PHOTOVOLTAIC PARAMETERS
Renewable energy, especially photovoltaic, is a promising solution to address the depletion of fossil fuels. Using single- and dual-diode models, solar cell modeling enables prediction of photovoltaic module behavior under various environmental conditions, making accurate parameter extraction essential. In this paper, we review different methods for identifying photovoltaic parameters, such as nonlinear least squares, and several meta-heuristic algorithms such as the genetic algorithm (GA), particle swarm optimization (PSO) and their versions combined with explicit equations (PSOX, GAX), and ant colony optimization in the continuous domain (ACOR). Experimental data are compared with these methods to identify the characteristics of a model photovoltaic panel, SY-M80W.The techniques focus on the single diode model to determine five unknown parameters, namely photovoltaic currents (Iph), saturation currents (Is), series resistance (Rs), parallel resistance (Rsh), and ideality factor (A). This comparative analysis aims to identify the most accurate method for photovoltaic parameter extraction, supporting enhanced solar energy system performance.
A DOUBLE SWITCH INTEGRATED HIGH-GAIN QUADRATIC BOOST CONVERTER FOR ELECTRIC VEHICLE APPLICATIONS
The rapid development of electric vehicles in the automotive industry opens the door for the development of DC-DC converters. This paper proposes a high-gain DC-DC converter with a lower part count for light electric vehicle (LEV) applications. When the converters are cascaded for maximum gain, a topology change is recommended that involves the integration of a voltage multiplier and a switching capacitor with a quadratic boost structure. A remarkable 496 is offered by this converter. Additionally, the theoretical portion of this work covers the 496 performance of the presented converter. Furthermore, MATLAB/Simulink is utilized to simulate the proposed configuration, which confirms the theoretical findings, and a 100 W laboratory prototype of the same is fabricated and tested to verify the performance of the presented converter.
DYNAMIC DE-EXCITATION PERFORMANCE OF BRUSHLESS SYNCHRONOUS MACHINES USING ADVANCED CONTROL STRATEGY
Synchronous generators (SG) are key electromechanical converters widely used in power plants, where precise excitation control is crucial for maintaining voltage regulation and stability. The main limitation of the conventional brushless excitation (CBE) system is its inability to supply negative voltages to the field winding, which limits fast de-excitation during sudden load rejection and causes terminal-voltage overshoots. To address this issue, this paper proposes an advanced fuzzy brushless excitation (FABE) system integrating fuzzy logic control (FLC) with H∞ control to enhance the transient and steady-state performance of synchronous generators. The H∞ controller ensures robustness against disturbances, parameter uncertainties, and nonlinearities, while the FLC improves adaptability and dynamic response. The proposed hybrid approach enables faster de-excitation, reduced voltage peaks, and improved damping of oscillations. Simulation results demonstrate that the FABE system clearly outperforms the conventional excitation method in terms of voltage stability, dynamic response, and overall control performance under various operating conditions.
HARMONIC ANALYSIS OF DISTRIBUTED ENERGY SOURCES USING SLIDING FFT AND IEC 61000-4-7
This paper presents the results of harmonic analysis of the current and voltage signals measured in the points of common coupling (PCC) to the distribution networks of several distributed energy sources. One small hydro (HPP) and four small photovoltaic (PV) power plants are considered. Voltage and current harmonics are calculated in two ways: 1) as per standard IEC 61000-4-7, and in accordance with IEEE 519 and EN 50160, and 2) by sliding fast Fourier transform (SFFT), which is applied to calculate time-varying current and voltage harmonics in the specific recorded signals. Application of IEEE 519 and EN 50160 yields different results and conclusions due to different calculation procedures and limiting values. PV power plants can generate almost sinusoidal currents when operating with high power, while the HPP can generate currents with strongly distorted waveshapes when supplying large nonlinear loads. As a result, all four PV power plants meet the requirements for current and voltage harmonics, whereas the analyzed HPP does not meet some of the defined limits. The SFFT analysis confirms the feasibility of dynamic real-time harmonic monitoring, which can play a crucial role in modern distribution networks.
FAULT DETECTION AND DIAGNOSIS IN PHOTOVOLTAIC POWER SYSTEMS USING FISHER RANDOM MATRIX APPROACH
This paper proposes a novel methodology for fault detection and diagnosis (FDD) in photovoltaic (PV) systems that combines Fisher's linear discriminant (FLD) with the Mahalanobis distance. The approach utilizes FLD to reduce the dimensionality of operational data while maximising the separation between healthy and faulty states. The Mahalanobis distance is then used to detect anomalies by accounting for correlations among variables such as voltage, current, and temperature. The method's validity was established using real-world data from a 20 MWp PV plant in Algeria. The results obtained demonstrate the efficacy of the proposed method in classifying various faults, including open-circuit, shading, and short-circuit faults. The approach demonstrates substantial improvements in detection accuracy, efficiency, and false-alarm reduction compared to conventional methodologies. The proposed FDD solution is robust and scalable, rendering it ideal for real-time monitoring of large-scale PV systems.