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
A SINGLE SWITCH NON-ISOLATED QUADRATIC HIGH GAIN CONFIGURATION FOR RENEWABLE ENERGY APPLICATIONS
This article presents a quadratic high-gain (QHG) transformerless DC-DC converter that integrates an active switched inductor (ASL) and a voltage doubler (VD) to achieve high voltage gain across a wide duty cycle range using a single switch. The design ensures steady input current, uses a simple continuous conduction mode (CCM), and lowers voltage stress on components—enabling the use of efficient low-resistance, low-voltage MOSFETs. By eliminating transformers and coupled inductors, it reduces size, weight, and leakage issues. Steady-state mathematical and efficiency analyses support the operating principles. A comparative study highlights its advantages, and a 100 W prototype is validated using a Simulink model.
Électronique et transmission de l’information | Electronics & Information Technology
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EVALUATION FOR THERMAL ANALYSIS OF DC MOTORS IN ELECTRIC VEHICLES
Series-wound DC motors remain attractive in many applications due to their simplicity, robustness, and cost-effectiveness. However, their performance and service life depend heavily on effective thermal management. This study presents a detailed investigation into the modeling, simulation, experimental validation, and thermal analysis of a series-wound DC motor under various cooling strategies. A thermal circuit model was developed in LabVIEW to predict temperature rise in different motor components, while a custom experimental setup was constructed to directly measure torque, current, and temperature during real-world operation. Multiple thermocouples were embedded in the motor to capture temperature distributions with high accuracy, and LabVIEW was employed for precise data acquisition and processing. Experimental results were used to refine and assess the thermal model, enabling a comparison between solid and optimized motor configurations. The findings highlight the impact of selecting appropriate cooling techniques on reducing hot-spot temperatures, thereby improving overall motor efficiency, reliability, and lifespan.
Thermotechnique et thermoénergétique | Thermotechnics and Thermal Energy
ENHANCING SMART BUILDING RELIABILITY AND DATA UCONTINUITY USING EDGE COMPUTING
Starting from the increase in the number of IoT devices inside buildings, devices that are integrated are the basis of the smart building concept, thus resulting in the exponential growth of the volume of data generated. Such an implementation is feasible but presents certain limitations in terms of the time required for data processing and due to the management of data queues, thus resulting in data losses that can lead to erroneous decisions inside buildings. The article proposes an integration between smart buildings and Edge computing, an integration that aims to demonstrate the benefits of this approach. The system is implemented through the ThingsBoard Edge platform and facilitates access to information generated by several buildings on the campus of the National University of Science and Technology Politehnica Bucharest. To present the benefits of this implementation, a two-month reference period was considered, during which we simulated, in parallel, a smart building infrastructure with and without an integrated edge node. Results confirm superior data continuity for the platform with an integrated edge node; the dependence on an internet connection no longer limits the system's capacity in the absence of a stable connection.
Automatique et ordinateurs | Automation and Computer Sciences
DESIGN SENSITIVITY ANALYSIS AND PERFORMANCE IMPROVEMENT OF A SIX-PHASE SQUIRREL-CAGE INDUCTION MACHINE
Current research increasingly focuses on improving the design of six-phase induction motors, particularly within the realm of scientific inquiry. The primary objectives of this study include maximizing motor efficiency while minimizing losses, decreasing motor mass, maximizing power output within a compact size, addressing environmental concerns such as vibrations, acoustic noise, electromagnetic compatibility, and incorporating eco-friendly materials. This paper investigates the design sensitivity analysis and performance improvement of six-phase asynchronous motors under investigation. To achieve this goal, design parameter variations are performed to analyze their influence on machine characteristics, geometric and electrical parameters, aiming to minimize losses and motor size while maximizing efficiency. This approach endeavors to create robust and dependable machines while minimizing associated costs.
Électrotechnique et électroénergétique | Electrical and Power Engineering
MAGNETIC ANALYSIS OF ROTATING MAGNETIC FIELD DEVICES USED FOR STUDIES ON BLOOD CELLS
The study of the molecular-level effects in blood cells of the variable magnetic field requires the design of appropriate magnetic devices. In this article, four immobile configurations are analyzed: Helmholtz coils, Gramme coils, a 4-pole electromagnet, and a 6-pole electromagnet. These devices can create a rotating magnetic flux density, intense (up to hundreds of mT), of high frequency (up to 1 MHz) and with an appropriate degree of inhomogeneity (maximum 5 %) in the bioreactor area of 1 cm in diameter. The rotating field is created by supplying the component coils with currents having shifted phases. The original comparative numerical analysis with the help of COMSOL software highlighted the effect of the device geometry, the type of core and conductor, correlated with the working frequency, on the magnetic flux density level in the blood cells. Original and useful results were extracted from the analysis of the homogeneity of the magnetic field in the bioreactor domain.
Génie biomédical | Biomedical Engineering
THERMAL AND ENERGY EFFICIENCY SOLUTIONS FOR NATURAL GAS COMPRESSION USING INDUSTRIAL AUTOMATION
The paper presents as results a proportional–integral–derivative (PID) function developed for a programmable logic controller (PLC) used to protect a screw electro-compressor from its thermal energy and a complex PLC algorithm developed for ensuring energy efficiency. The operating mode of an electro-compressor can be imposed as manual mode or automatic mode and can be selected from a developed HMI screen. The algorithm behind both manual mode and automatic mode will be analyzed in the article. The efficiency of energy consumption will result from the variation analysis of the current consumed by the main electric motor that drives the compression unit. The oil temperature evolution will also be analyzed from the parameter records, which is kept under control from a thermal point of view by a custom parameterized PID function. It will be detailed in the article how this custom parameterization of the PID function was performed and what the implications are from the point of view of the thermal efficiency for the electro-compressor.
PRACTICAL ASPECTS OF THE ARTIFICIAL URINARY SPHINCTER IN MEN
The artificial urinary sphincter (AUS) remains the gold standard in moderate to severe urinary incontinence after prostatic surgery. Starting from the significant personal experience of the authors in the field, we aim to review the current indications, limits and challenges associated with the implantation of an AUS. We present different surgical approaches and pre- and postoperative considerations.
SENSORLESS OPTIMAL CONTROL OF A FIVE-PHASE INDUCTION MOTOR WITH HARMONIC MINIMIZATION
This work presents a sensorless optimal control strategy (model predictive torque and speed control) applied to a five-phase induction machine. Model predictive control (MPC) is used for both torque and flux control, eliminating the need for traditional field-oriented control (FOC) and direct torque control (DTC) techniques. Additionally, model predictive speed control (MPSC) replaces the conventional PI regulator, ensuring fast response and improved dynamic performance. An extended Kalman filter (EKF) is integrated, allowing for accurate estimation of rotor flux, stator currents, and speed. The components of Clarke currents that contribute to harmonic generation are incorporated into the model-predictive torque control (MPTC) optimization criterion. The simulation results from MATLAB Simulink demonstrate the effectiveness of this strategy.
Model predictive torque and speed control
INTEGRATING INDUSTRY 4.0 IN ENGINEERING EDUCATION
The paper analyses both the importance of introducing Industry 4.0-related courses into the curricula of Industrial Engineering and Management (IEM) education and the appropriate ways to do so. The case study focuses on questioning two categories of relevant stakeholders: students and professors. It also analyses their position on the introduction of new courses tailored to Industry 4.0 content and/or the integration of Industry 4.0 elements into existing courses.
Industrial engineering and management (IEM) education
METAHEURISTIC-DRIVEN DUAL INDUCTOR BOOST CONVERTER FOR FLOATING PV SYSTEMS IN MATLAB/SIMULINK
The best way to present a floating photovoltaic (FPV) system would be to recognize the increasing demand for renewable energy sources and the challenges faced by traditional land-based solar systems, including limited space and the astronomical costs of installation. One of the possible solutions to these problems is FPV systems, which use water surfaces as a place to install solar panels, such as lakes, reservoirs, and ponds. The research paper will help optimize the energy collection process for FPV systems by developing an Improved Perturb and Observe (IP&O) algorithm with a dual-inductor boost converter (DIBC). This is aimed at precise monitoring of the peak power point, particularly under changing environmental conditions. The simulation results of the suggested MPPT approach in MATLAB/Simulink are consistent with those reported in the literature. The findings show that reaction time and overall functionality of the FPV system improved significantly, highlighting the possible benefits of the IP&O algorithm for optimizing the energy output of floating solar arrays compared to the traditional MPPT approach.
A NOVEL MODULAR REDUCED COMPONENT MULTISOURCE MULTILEVEL INVERTER FOR SUSTAINABLE APPLICATIONS
This paper introduces a novel modular multi-source multilevel inverter (MSMLI) topology tailored for renewable energy applications. The proposed architecture features a compact basic unit comprising nine switches, three DC voltage sources, and an H-bridge polarity reversal circuit. With equal source magnitudes, this module produces a 7-level output; configuring the sources in a 1:3 ratio extends the output to 15 levels. By connecting multiple units in series, higher voltage levels can be achieved efficiently in both symmetric and asymmetric modes. Crucially, only four switches need to be active per level, minimizing switching losses and improving overall efficiency. Total harmonic distortion (THD) is significantly reduced—from 12.20% in symmetric operation to 5.38% in asymmetric mode—enhancing waveform quality. Generalized mathematical expressions support both level generation control strategies. Comparative evaluation with existing inverter topologies demonstrates advantages in switch count, THD, and total standing voltage (TSV). The theoretical analysis was validated by experimental results obtained from a laboratory-built prototype. The multi-source capability and low hardware complexity make this MSMLI ideal for integration with sustainable applications.
SIMULATING CYBERATTACKS IN A VIRTUAL ENVIRONMENT: A CASE STUDY IN THREAT DETECTION
In this study, we present how we simulated cyberattacks in a controlled virtual environment to assess the security and detection abilities of a Windows 7 system. Using common penetration testing tools, we recreated realistic scenarios including port scanning, brute-force login attempts, password cracking from NTLM hashes, and phishing with cloned websites. Our findings revealed that outdated systems, when left unpatched and poorly monitored, are especially vulnerable, thereby underlining the need for regular updates, strong password practices, and real-time monitoring to reduce risk, while providing insights into how such environments can be tested and strengthened against different cyberthreats.
CURRENT RESEARCH ON THE VARIABLE STIFFNESS MAGNETIC SPRINGS
This paper provides a synthesis of research on magnetic springs with variable stiffness that can be the basis for obtaining configurations of electromechanical systems whose operation requires fixed or real-time adjustable pre-established elastic forces, such as vibration damping or humanoid and medical recovery robots. The study and systematization of the research known up to this point highlights the basic concepts and specific characteristics for the two main categories of magnetic springs with variable stiffness, namely, passive magnetic springs with a predetermined stiffness at a desired value (ASMSs) and active magnetic springs with real-time adjustable stiffness (CSEMSs). The study highlights that CSEMSs that generate variable stiffness in a very wide range, from ˗˗9800 N/m to +9800 N/m, can be obtained, which makes them very useful in the design and construction of systems for controlling fast processes, such as vibration isolation systems with quasi-zero-stiffness (QZS).
INTELLIGENT CONTROLLER-BASED DYNAMIC VOLTAGE RESTORER TO REDUCE THE VOLTAGE FLUCTUATIONS
In today's power system research, improving power quality is a crucial issue. Due to the advent of numerous industrial equipment and sensitive loads, it has become increasingly vital. Distribution-side voltage sags and swells are the leading causes of power quality issues. Five-level multilevel inverters are too expensive for average-voltage applications and high-power applications due to higher voltage stress on switches, large dv/dt, and the need for extensive filtering. The proposed seven-level multilevel inverter-based dynamic voltage restorer (DVR) is a superior solution to these issues because it can be directly connected to the medium-voltage distribution system without an injection transformer. There are numerous ways to reduce voltage sags and swells, but the planned DVR is one of the most widely used techniques. As a series compensating device, the DVR is primarily used in applications involving low- and medium-voltage systems and employs a fuzzy logic controller (FLC)- based Proportional and Integral (PI) controller to compensate for voltage sags during a three-phase fault. Using simulation results from a fresh DVR setup available in MATLAB/Simulink, the effectiveness and performance of the proposed model are confirmed.
STUDY AND DESIGN OF A DIGITAL PULSE WIDTH MODULATION SIGNAL GENERATOR FOR DC-DC CONVERTERS
This paper presents the design and implementation of a novel digital pulse-width modulation (PWM) signal generator for controlling DC-DC power converters. The proposed digital approach enables precise control of both the switching frequency and duty cycle of the PWM signals via a computationally efficient algorithm. This technique is versatile and can be integrated into various DC-DC converter configurations, thereby facilitating the development and experimental testing of new power-circuit designs. Experimental results demonstrate that the method offers significant advantages over traditional analog and digital techniques, including enhanced accuracy and improved signal quality. The performance of the proposed generator is validated through testing with a single-ended primary-inductance DC-DC converter (SEPIC). Additionally, the control board is suitable for both research and educational applications.
Single-ended primary-inductor converter (SEPIC)
TIME-FREQUENCY LOCKED LOOPS INTENDED FOR THE TRACKING OF THE PULSE SIGNAL PERIODS
This article describes the theory of the time-based frequency-locked loop (TFLL), intended for tracking the input signal periods, which change extremely rapidly. They are based on the processing of the input signal periods. The described algorithm, when appropriately implemented, can also be applied to track and predict any physical variable in real time, provided that the pulse signal period is replaced with periodic data from the physical variable. The paper presents a mathematical procedure for determining optimal system parameters for tracking rapidly changing periods. Since this mathematical procedure is very lengthy for higher-order systems, the paper focuses on a new abbreviated analysis method based on a tabular approach. This approach has not been described in the literature so far. Mathematical analyses in the time domain were performed using the Z transformation. Simulation of the system operation was carried out. For frequency-domain analysis, the theory of FIR digital filters and the corresponding MATLAB software were used. The system's tracking capabilities are demonstrated in the time and frequency domains.
NEURAL SWITCHING TABLES FOR A FOUR-LEVEL MULTICELLULAR INVERTER TO ENHANCE DIRECT TORQUE CONTROL OF A PMSM
This paper proposes neural switching tables (NCST, NRST) to improve direct torque control (DTC) of a permanent magnet synchronous motor (PMSM) driven by a four-level multicellular inverter (4LMI). Classical DTC suffers from high torque and flux ripples, which can cause mechanical stress and reduce reliability. The neural approach replaces conventional and reduced lookup tables with compact neural network models, allowing seamless integration in Simulink without large precomputed datasets. Simulation results confirm identical control behavior to that in classical tables, while reducing torque ripple by approximately 50% and maintaining flux within hysteresis limits. This solution enhances modularity, simplicity, and scalability, making it a promising step toward AI-based DTC strategies.
MAXIMUM RIPPLE ELIMINATING MULTI-LEVEL BIDIRECTIONAL DC-DC CONVERTER VIA OPTIMIZED DEEP LEARNING NETWORK
In this research, a novel deep learning based Multi-level Bidirectional DC-DC converter using a modified Emperor Penguin Optimized multi-graph neural network (MEPO-MGN2) has been proposed. Grid power is converted to direct current by means of an AC-DC converter, and then a bidirectional multi-level DC-DC converter (MLDC) is used for the power transfer in both directions between the grid and PMDs. The proposed method utilizes an attention multi-graph convolution network (AMGCN) for the duty cycle (α) prediction of MLDC to regulate the flow of power between the grid and PMD, vice versa. This system employs multiple Proportional-Integral (PI) controllers to manage voltage and current for stable, optimized power transfer. Modified emperor penguin optimization (MEPO) is used to tune the parameters of MLDC, thereby achieving a well-regulated DC output voltage in the charging stations. The MEPO-MGN2 performance is evaluated, and implementation is carried out using the MATLAB platform. The efficacy of the proposed method is 98.5%, which is better than the other existing converter techniques.
POWER LOSS ANALYSIS AND CONTROL OF A BIDIRECTIONAL HIGH-GAIN CONVERTER FOR EV CHARGING USING PV ARRAY
This study looks at how a bidirectional high-gain converter (BDHGC) can support charging electric vehicles (EVs) using a PV array. The solar irradiation varies, and the PV system’s output is increased with an MPPT technique before it is sent to the BDHGC. The converter increases the voltage and allows power to move back and forth for successful charging. Both switching and conduction losses are studied in detail by building MATLAB/Simulink simulations. The system uses a relay feedback control system to keep the output voltage steady whenever the load changes. From the simulation, it is evident that the system gives high efficiency and stable control, which makes voting solar-powered EV charging a possibility.
ADVANCED DUAL-AXIS SOLAR TRACKING USING A NOVEL ARTIFICIAL NEURAL NETWORK-PID CONTROL STRATEGY
This paper addresses the challenge of enhancing dual-axis solar tracking systems' adaptability and precision under dynamic conditions. A novel hybrid control approach is proposed, combining an artificial neural network (ANN) with a proportional-integral-derivative (PID) controller. The ANN, trained using the Levenberg-Marquardt algorithm, adaptively tunes the PID gains (Kp, Ki, Kd) in real-time. Although Model Predictive Control (MPC) is currently recognized as the most advanced and effective strategy for solar tracking, our comparative study shows that the ANN-PID controller achieves faster dynamic response, improved adaptability to disturbances, and reduced computational complexity. MATLAB-Simulink simulation results validate the superior tracking accuracy and energy capture performance of the ANN-PID system, as confirmed by MAE. These findings highlight the ANN-PID control as a promising real-time alternative to MPC, offering robust and efficient solar tracking with lower computational demands.
Proportional-integral-derivative (PID) controller
A HYBRID INTELLIGENT CONTROL FRAMEWORK WITH REAL-TIME VALIDATION FOR INDUCTION MOTOR DRIVES
This paper proposes a hybrid speed–current control framework for high-performance induction motor drives under field-oriented control. The outer speed loop combines Backstepping, Radial Basis Function neural approximation, and high-order sliding mode compensation, where Backstepping provides a Lyapunov-based nonlinear structure, the RBF network estimates lumped uncertainties online, and the HOSM term ensures finite-time disturbance rejection and fast convergence. An enhanced Harris Hawks Optimization with chaotic Lévy flights is employed to optimally tune the controller parameters. In the inner loop, a Higher-Order Non-Singular Terminal Sliding Mode controller regulates stator currents, guaranteeing finite-time tracking, reduced chattering, and robustness against parameter variations and inverter nonlinearities. Lyapunov analysis confirms uniform ultimate boundedness of the speed loop and finite-time convergence of the current loop. The effectiveness of the proposed strategy is verified through MATLAB/Simulink simulations and real-time implementation on the OPAL-RT OP5707XG platform, demonstrating superior dynamic performance and disturbance rejection compared with PI- and conventional sliding-mode-based schemes.
Higher-order non-singular terminal sliding-mode control
ENHANCING WIND FARM PERFORMANCE THROUGH A PARTICLE SWARM-BASED OPTIMIZATION OF TURBINE DIMENSIONS AND LAYOUT
Wind energy plays a crucial role in the global transition toward sustainable power generation. To meet the growing demand for renewable energy, optimizing wind farm design is essential for both maximizing energy output and minimizing costs. This paper builds upon previous studies by refining and expanding several ideal wind turbine configurations, using them as the foundation for a more comprehensive analysis and enhancement. While prior research has primarily focused on reducing the cost per kilowatt (cost/kW) of power generated, this study takes a broader approach, aiming to optimize overall wind farm efficiency through the strategic adjustment of turbine rotor diameters and hub heights. By implementing a particle swarm optimization (PSO) algorithm, this work identifies the optimal arrangement of these turbine dimensions to achieve higher efficiency while simultaneously reducing overall costs. The proposed methodology offers a flexible, scalable solution that can significantly enhance wind farm performance, making it more adaptable to varying environmental conditions and economic constraints.
Particle swarm optimization (PSO) algorithm
ELECTRICALLY DRIVEN ROTARY VOLUMETRIC PUMP EFFICIENCY
This paper presents the development and experimental validation of a rotary volumetric pump with profiled rotors designed for domestic water supply systems. The proposed solution integrates an electric drive system coupled with frequency control to improve hydraulic and energy performance. A constructive concept, mathematical modeling, and an experimental prototype were developed at the National University of Science and Technology POLITEHNICA of Bucharest. Comparative studies with conventional centrifugal pumps highlight significant improvements in energy efficiency, lower power demand, and the ability to convey viscous fluids or suspensions without performance degradation. Experimental installations equipped with sensors and monitoring instruments confirmed theoretical predictions, demonstrating that integrating electrically driven rotary volumetric pumps can reduce operational energy consumption and increase reliability in civil building services. These results underline the potential contribution of the proposed pump to sustainable energy management in water distribution systems.
SIMULATION AND EXPERIMENTAL INVESTIGATION OF A COUPLED-INDUCTOR BASED LED DRIVER CIRCUIT
A light-emitting diode (LED) or an LED string can receive a regulated power input from highly efficient, low-cost LED driver topologies using a simple control strategy. The presented work elucidates the analysis of a DC-DC buck topology-based single-stage LED driver circuit with dual output voltage levels. The projected driver structure has a reduced semiconductor-based component count and can control the LED light output. The suggested driver circuit employs a magnetically coupled inductor for transformerless energy transfer. The power switches employed in the proposed structure use a zero-voltage switching (ZVS) strategy to prevent voltage transients that may occur during switch turn-off due to leakage flux components of the inductors. The control and regulation of the light output of the LED lamps are achieved by applying double Pulse Width Modulation (PWM) signals to the switches. The proposed topology features relatively low power losses and improved voltage regulation. The simulation analysis and the projected driver-circuit results obtained in PSIM 9.0 are validated against prototype model results.
Double pulse width modulation (PWM) technique
Light-emitting diode (LED) driver circuit
PHOTOVOLTAIC FLUCTUATION SMOOTHING: MULTI-CRITERION OPTIMIZATION OF LOW-PASS FILTERS
The integration of photovoltaic (PV) systems into power grids faces inherent challenges posed by power fluctuations driven by variable weather conditions, potentially destabilizing grid operations. This study, based on real data from the CDER network in Algeria, proposes a systematic comparative analysis of a discrete first-order low-pass filter (LPF) for attenuating these fluctuations by evaluating three representative time constants (TC = 10, 20, 30 min). Using a novel multi-criteria evaluation framework, we assess both smoothing performance and battery stress effects, and introduce an innovative SVM-based heatmap classification method for ramp rate (RR %) pattern analysis. Key findings reveal fundamental trade-offs: while TC = 30 min achieves an 80% reduction in high fluctuations (RR% > 10%), it concurrently increases battery energy throughput by 35%, potentially accelerating long-term degradation. The TC = 20 min configuration emerges as the optimal balance, delivering 60% power variance reduction while limiting the mean squared error (MSE) increase to just 8%. Our results provide: (1) quantitative evidence for LPF parameter optimization, (2) visual analytics for fluctuation pattern recognition, and (3) practical guidelines for maintaining grid stability while extending battery lifespan in PV-integrated systems.
EXPERIMENTAL INVESTIGATION OF COTTON DUST INFLUENCE ON POWER OUTPUT OF PHOTOVOLTAIC MODULE
This research presents the influence of cotton dust on photovoltaic (PV) systems installed in textile industries. An indigenously designed experimental setup is installed, and two different experiments have been conducted based on cotton dust concentrations from (28000 – 52431) mg/cm2 in twelve days. The results showed that the output of the PV module decreased drastically as the cotton dust accumulation increased. The accumulated cotton dust samples are collected from the PV surface for physical examination. It is observed that cotton dust has a unique stickiness, which causes the fibre to adhere to the PV module surface. When exposed to sunlight for an extended period, its color becomes dull, and yellowness increases, which decreases the transmittance and forms large agglomerates due to an increase in humidity, which blocks irradiance. The results of this research can be utilized to devise a specific cleaning mechanism for the textile sector that will increase the PV output.
ECOLOGIC NAVAL POWER PLANT INSTALLED ON BOARD MARITIME TRANSPORT VESSEL
The use of renewable energy sources on board ships is one solution to reduce pollution from maritime transport. Considering it one of the many solutions for the transition to "zero" emission ships, we studied the possibility of installing a new type of power plant on ships already in operation that uses solar/photovoltaic and wind energy conversion systems. The current electricity production system is transformed into a hybrid system, and by improving the available electrical power management algorithms, clean energy consumption will be prioritized. Monitoring daily electricity consumption and recording values for renewable energy source parameters during ship periods and voyages enabled calculations to determine the potential for electricity production from renewable sources and demonstrated the viability of the chosen solution. The results obtained highlight that installing the ecological marine power plant (ENPP) can achieve significant reductions in fuel consumption for producing electricity on board the ship.
CONTROL AND OPTIMIZATION OF VOLTAGE PROFILES AND SAG MITIGATION IN LOW-VOLTAGE POWER NETWORKS
Voltage sags, swells, and fluctuations in low-voltage networks can disrupt sensitive equipment, reduce industrial productivity, and accelerate component aging. This paper reviews common assessment practices, including ITIC/CBEMA curves and waveform analysis, and proposes an enhanced method that also considers pre- and post-event intervals to better quantify disturbance severity and recovery behavior. A disturbance direction detection procedure is presented to support source localization and targeted mitigation. As an alternative to conventional UPS-based solutions, active voltage conditioners (AVC)/dynamic voltage restorers (DVR) are discussed for fast compensation without energy storage and with high tolerance to voltage variations, while not covering complete interruptions. The main contribution is a combined DVR/AVC and active filtering solution that improves voltage stability, power factor, and harmonic content, enabling a cleaner, more reliable supply.