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E-Journal №4(68)2025

"PROBLEMS of the REGIONAL ENERGETICS (https://doi.org/10.52254/1857-0070.2025.4-68)"

CONTENTS

1	Integrated Diagnostic System and Multi-level Reliability Modeling for Predictive Maintenance of Transport Induction Motors Authors: 1Duer S., 2Gubarevych O., 3Melkonova I., 1Woźniak M., 4Kyrychenko O., 2Muraviov V. 1Technical University of Koszalin Koszalin, Poland 2Educational and Scientific Kyiv Institute of Railway Transport, Kyiv, Ukraine National Transport University, Kyiv, Ukraine 3 Volodymyr Dahl East Ukrainian National University, Kyiv, Ukraine 4Educational and Scientific Kyiv Institute of Water Transport named after Hetman Petro Konashevych-Sahaidachny, National Transport University, Kyiv, Ukraine
	Abstract: The aim of this study is to develop the architecture of a diagnostic system and a multi-level reliability model aimed at improving the cost-efficiency and operational reliability of induction traction motors. To achieve this goal, a comprehensive development process was carried out: based on failure statistics, the main defects and types of damage to critical motor components were identified for monitoring and timely maintenance; the architecture of an integrated diagnostic system for assessing the technical condition of motor components (stator, rotor, bearings) was designed; and a reliability model was constructed, reflecting eight operational states of the motor from full functionality to catastrophic failure. The reliability assessment is based on the Kolmogorov-Chapman system of equations, which describes probabilistic transitions between operational states and allows accurate prediction of failure-free runtime and optimal maintenance intervals based on current parameters. The most important results include the formalization of the relationship between diagnostic signals and reliability states and the construction of the reliability function for dynamic maintenance scheduling. The significance of the results lies in the integration of diagnostics with probabilistic reliability modeling, which ensures higher failure prediction accuracy, reduced unplanned downtime, and improved operational readiness. A key contribution of the study is the practical implementation of the eight-state model, enabling dynamic maintenance planning and adaptation of service strategies to the real-time condition of equipment. The proposed strategy lays the foundation for intelligent control of traction drives and the implementation of predictive maintenance systems, which is especially relevant for rail transport and other industries using electric drives.
	Keywords: induction motor, failure statistics, diagnostic system, reliability model, predictive maintenance, transport drives, Markov process. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.01
2	Synthesis of Automatic Control System of Traction Asynchronous Motor of Transport Diesel-Generator Power Plant Authors: 1Kulagin D., 2Maslov I. 1National University "Zaporizhzhya Polytechnic" Zaporizhzhya, Ukraine 2 Dunai Institute of National University "Odessa Maritime Academy" Izmail, Ukraine
	Abstract: This paper presents the synthesis of an automatic control system for a traction induction motor used in a transport diesel-generator power plant. The objective of the study is to improve the stability and dynamic performance of current regulation under varying operating conditions. The research covers three main aspects: analysis of the diesel-generator plant as a control object, development of a methodology for designing current regulators, and validation of the synthesized regulators against real transient processes. The proposed methodology provides a systematic approach to constructing structural schemes of the current control loop and the closed-loop system. A new regulator transfer function is synthesized based on transient performance criteria, specifically limiting settling time and overshoot, while maintaining robustness to parameter variations caused by ambient temperature. Analysis shows that the fastest current regulation loop, which determines the system’s overall dynamics, becomes unstable when a conventional regulator based on subordinate control is applied. In practice, widely used serial diesel-generator plants exhibit temperature-induced variations in stator resistance during warm-up, leading to significant overshoot and reduced responsiveness. These effects highlight the limited robustness of existing regulator designs. In contrast, the newly synthesized regulator demonstrates stable transient responses even under resistance variations, confirming its adaptability and efficiency in real conditions. The results provide a foundation for the development of modern control systems for transport diesel-generator power plants, ensuring stable operation, required dynamic properties, and improved reliability. Consequently, the findings have practical significance for creating next-generation traction drive control systems for railway and other transport applications.
	Keywords: power plant, automatic control, autonomous voltage inverter, electrical apparatus, electrical machines, mathematical modelling, electrical systems and networks. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.02
3	Power Quality Enhancement in Grid-Connected Systems using Dynamic Voltage Restorer with Switched Inductor Cascade Boost Converter Authors: 1Lakshminarayana G., 2 Ajumon S.P., 3Viswaprakash B., 4Pandikumar M. 1VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India. 2Noorul Islam University, Kumaracoil, India. 3Kaveri University, Telangana, India. 4Saveetha School of Engineering, SIMATS, Chennai, India.
	Abstract: The main objectives of the study are to improve power quality (PQ) in grid-connected systems and mitigate voltage disturbances by using a dynamic voltage restorer (DVR) powered by a Photovoltaic (PV) system. By integrating PV as the primary power input, the DVR supplies clean energy for voltage restoration, thereby enhancing system efficiency and reliability. This approach provides transition to sustainable energy practices by minimizing the dependency on traditional power grid during disturbances. These objectives were achieved by integrating a Switched Inductor Cascaded Boost Converter (SICBC) for efficient voltage boosting and employing a Pine Cone Optimized Proportional-Integral (PCO-PI) controller for precise output regulation. The SICBC provides provide high and stable voltage gain with improved conversion efficiency, essential for maintaining DVR performance at PV power fluctuations. The cascaded configuration mitigates stress on passive elements, contributing towards better thermal management and longer system life. By adopting the Pine Cone Optimization algorithm, the controller's parameters are fine-tuned to achieve optimal performance in terms of settling time, steady-state error and overshoot. The algorithm mimics the natural seed dispersal behavior of pine trees to explore and exploit the control parameter space effectively. The most important results are a recorded efficiency of 97.9% and a reduction in Total Harmonic Distortion (THD) to 2.56%, as demonstrated through MATLAB/Simulink-based simulations. Furthermore, the system demonstrated robust voltage compensation during both symmetric and asymmetric fault conditions. The obtained result reveals the proposed DVR-PV strategy substantially improves power stability and quality, reinforcing the practical viability of renewable-integrated compensators in modern electric grids.
	Keywords: power quality, dynamic voltage restorer, controller, cascaded boost converter. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.03
4	Features of Topological Optimization of the Synchronous Generator with Permanent Magnets Based on a Genetic Algorithm Authors: Petrov T.I., Safin A.R. Kazan State Power Engineering University Kazan, Russian Federation
	Abstract: The main objective of the study is to assess the feasibility of replacing rare-earth NdFeB magnets with ferrite magnets (BaFe₁₂O₁₉) in a 10 kW synchronous generator designed for use in renewable energy. Ferrites are 10–15 times cheaper than NdFeB and have high thermal stability but have a significantly lower residual induction and forță coercivă. To achieve this goal, the following tasks were solved: creating a technique for multi-criteria optimization of the generator design based on a genet-ic algorithm and the finite element method modeling and analysis of the results. The optimization objective function combines three normalized parameters: rotor mass (kg), magnetic system cost (USD), and electromagnetic losses (W), normalized relative to the base generator with NdFeB. The choice of the genetic algorithm is due to its ability to effectively solve problems with nonlinear field dependencies and complex topology, avoiding local minima. The simulation was performed for three configurations: the base generator with NdFeB and the generator with ferrites before and after optimization. The most important results are that topological optimization allowed reducing the rotor weight by 10% losses and by 18% and increasing the efficiency from 85% to 87.3%, while reducing the cost by 9.6% compared to the original model on ferrite magnets. Compared to the base version of NdFeB, the optimized generator turned out to be 20.5% cheaper, and the efficiency decrease was only 5 percentage points. The significance of the obtained results consists in confirming the prospects for using ferrite magnets in low-power distributed generation systems.
	Keywords: topology optimization, synchronous generator, ferrite magnets, genetic algorithm, finite element method, integral objective function, multicriteria design. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.04
5	Optimization of the Design and Parameters of Electromechanical Energy Converters Using Multiparametric Design Techniques Authors: Shevchenko V.V., Minko A.N., Lazurenko K.A. National Technical University "Kharkiv Polytechnic Institute" Kharkiv, Ukraine
	Abstract: The aim of the work is to increase the accuracy of electromechanical equipment (turbogenerator) designing, selecting the optimal design and maximum permissible electromechanical loads in given dimensions by using the capabilities of multiparametric design, in particular, using the particle swarm method. Due to the refined calculations the presence of thermal and mechanical reserves, the possibility of using the turbogenerators existing cooling system when increasing their capacity have been proven. Multiparameter design using the particle swarm method makes it possible to search for the best solution in a multidimensional parameter space, where the “swarm particles” (possible solu-tions) gradually approach the optimal result while simultaneously maintaining all turbogenerator interrelated parameters within acceptable limits. The goal set is achieved by establishing the heat exchanger optimal operating parameters and turbogenerator cooling system other elements while increasing its power and maintaining all characteristics and indicators within the limits established for turbogenerators of similar power by the manufacturer. The most important result is the estab-lishment possibility of using the factory cooling system when increasing the new turbogenerators power while maintaining the dimensions due to the identified thermal reserves in the base generator at refined multiparametric designing. The optimal geometry of the core and stator winding cooling channels and the internal layout of the heat exchanger elements have been established. The obtained results significance is that the proposed multiparametric designing methodology using the particle swarm method can be used for the optimal design of new electromechanical equipment or its mod-ernization at power plant units.
	Keywords: turbogenerator, optimal construction, increase in power, multiparametric designing, particle swarm method, modernization, cooling system; heat exchanger. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.05
6	Automatic Control of the Heat Supply of Public Buildings using a Combination of Neural Networks and PID Control Authors: Batukhtin A.G., Seredkin A.A., Palkin G.A., Dolgikh R.S. Federal State Educational Institution of Higher Education «Transbaikal State University» (FSEI HE «TSU», Transbaikal State University) Chita, Russian Federation
	Abstract: The aim of this study is to develop a method for improving temperature control in an administrative and public building. Multi-story administrative and public buildings connected to a district heating system were chosen as the subjects of the study. The subject of the study is the heating system of an individual building. To achieve this goal, heating system operation was modeled, including using a physical model on a test site. The analysis was conducted by comparing actual temperatures with their calculated values and those established by a temperature chart. The tasks of modeling the operation of the heating system were solved, including in a physical model at the test site. The analysis of the actual operating parameters was carried out by comparing them with the calculated values and the values set by the temperature schedule. To evaluate energy efficiency and adjust the parameters of automatic control, the authors developed a mathematical model of the object heating system building. It is proposed to supplement the traditional algorithm of automatic PID regulation by taking into account the building temperature parameter determined using a neural network. In this case, the maximum approximation of the controlled parameter value to the target value is achieved. The most important result is to improve the quality of temperature control in the building using a neural network to determine the representative coefficients of various rooms. The significance of the obtained scientific results lies in the fact that due to the use of a neural network, the probability of deviation of the main technological parameter during transients is reduced, which increases the adaptability of regulation.
	Keywords: heating system, temperature graph, heat consumption, automatic control, artificial intelligence, heat consumer. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.06
7	Method of Analysis of Digital Video Integrity with Linear Computational and Low Technical Complexity Authors: 1Kobozieva A.A., 1Lebedieva O.Y., 2Savchenko V.A. 1Odesa National Maritime University, Odesa, Ukraine 2 State University of Information and Communication Technologies, Kyiv, Ukraine
	Abstract: The energy sector is currently undergoing a process of rapid digitalization, which leads to a signifi-cant increase in risks and vulnerabilities to cyberattacks in this area. Video sequences are desirable objects of falsification for intruders pursuing illegal goals, making the task of timely detection of their unauthorized changes critically important. However, methods for analyzing/processing digital video, as a rule, have significant computational complexity, which does not allow using them for integrity examination in real time, or require the use of additional technical means. The purpose of this work is to provide the ability to effectively examine the integrity of a video sequence received by CCTV cameras in real time under conditions of minimal technical complexity by developing a method for detecting the result of a frame substitution attack. The goal was achieved by addressing the following tasks: the justified selection of a small video frame sub-region (a key block); determin-ing the integral characteristic of the relative contribution of the block's frequency components—the normalized separation of its maximum singular value. The most important result of the work is the substantiation of the possibility of using the properties of singular values of a single (key) small-sized block of each video frame to obtain information about the presence/absence of frame substitu-tion attack results. The significance of the obtained result consists in the fact that the proposed method enables effective digital video integrity examination in real-time without the need for additional technical means, thereby increasing the reliability and speed of decision-making during video stream monitoring.
	Keywords: digital video, video integrity examining, CCTV camera, real-time, singular value. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.07
8	Comparative Analysis of Performance and Emission Characteristics of Jatropha Biodiesel and Emulsified Jatropha Biodiesel in a Diesel Engine Authors: 1Vemula N.B., 1Shaik F., 2Gopidesi R.K. 1Vignan's Foundation for Science, Technology & Research, Vadlamudi, India 2Presidency University, Bengaluru, India
	Abstract: The main aim of this study is to investigate the performance and emission characteristics of Jatropha biodiesel blends in a diesel engine and to explore the potential of water-in-biodiesel emulsification as a strategy to enhance efficiency and reduce harmful emissions, particularly nitrogen oxides (NOX). To achieve these objectives, Jatropha biodiesel blends (B10, B20, B30) were first tested in a single-cylinder diesel engine under standard operating conditions to determine the optimum blend. Based on a balance between Brake Thermal Efficiency (BTE) and emissions, B20 was identified as the most suitable blend and was subsequently used as the base fuel to prepare emulsified biodiesel blends with 5%, 10%, and 15% water by volume (B20W5, B20W10, and B20W15). The utmost important results are that the emulsified blends exhibited prominent improvements in performance and emission characteristics compared to B20. Specifically, B20W10 achieved a 4% higher BTE than B20 and a reduced Brake Specific Fuel Consumption (BSFC), while B20W15 recorded reductions in Hydrocarbon (HC) emissions by 31.42%, Carbon Monoxide (CO) by 55.55%, and Smoke Opacity by 36.11% relative to B20. Furthermore, B20W10 demonstrated a 9% decrease in NOX emissions than diesel. The significance of the obtained results is that water-in-biodiesel emulsification, particularly the B20W10 blend, offers an applied and sustainable solution for improving combustion efficiency, lowering fuel consumption, and mitigating harmful emissions, thereby promoting cleaner compression Ignition (CI) engine operation and supporting the transition toward renewable energy use in the transportation sector.
	Keywords: Jatropha biodiesel, emulsified biodiesel, performance, emission, surfactant. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.08
9	Improvement of the Accuracy of Transient Process Analysis in Complex Power Systems Using the Z-Transform Method Authors: Shilin A.N., Shilin A.A., Dikarev P.V., Ngo D.T. Volgograd State Technical University Volgograd, Russian Federation
	Abstract: The main objectives of this study were to develop and comparatively analyze methods for digital modeling of dynamic processes in electrical power transmission lines with distributed parameters, as well as to evaluate the accuracy of simplified lumped parameter models against full models. The re-search aims to overcome limitations of simplified equivalent circuits that may lead to significant errors when analyzing transient conditions, system stability, and emergency situations. To achieve these objectives, the following tasks were accomplished: mathematical models of long lines were developed using operational methods based on Laplace and z-transforms; transfer functions in z-form were obtained for homogeneous lines without distortions and with distortions under different load types (matched and mismatched); for comparison, a simplified lumped parameter power line model was developed; computer simulation of transient responses was performed; and comparative analysis of results was conducted with calculation of absolute and relative errors. The most im-portant results include the identification of significant discrepancies in time delays and amplitudes of transient processes between models; detection of maximum absolute errors reaching 0.45 for matched load and 0.03 for mismatched load; and determination of conditions where the simplified model adequately describes the system. The significance of the obtained results lies in their ability to improve the accuracy of transient process analysis in power systems, provide selection of optimal modeling methods for specific engineering tasks, prevent errors in the design of relay protection and automation devices caused by inadequacy of simplified models, and establish foundations for devel-oping more reliable algorithms for digital protection of power equipment.
	Keywords: smart grid, transient processes, transfer function, wave impedance, equivalent circuit, recurrent algorithms, relay protection, system stability, z-transform, simulation model, modeling error. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.09
10	Optimization of the Grounding Resistance of the Neutral in 20 kV Networks According to the Criteria of Minimizing the Significant Value of the Ground Fault Current and the Overvoltage Amplitude Authors: Kyryk V.V, Buriak A.R National Technical University of Ukraine "Ihor Sykorsky Kyiv Polytechnic Institute", Kyiv, Ukraine
	Abstract: The main objective of this study is to determine the optimal resistance of transformer neutral resistive grounding in 20 kV distribution networks using clustering methods. The research aims to achieve a technical balance between limiting single-phase ground fault currents, minimizing overvoltages, and reducing system sensitivity to stochastic fluctuations in network parameters. To achieve this, the fol-lowing tasks were accomplished: modeling of network operating modes with various grounding resistance values in MATLAB/Simulink; forming a dataset of single-phase ground fault current parameters and corresponding resistances; applying K-Means and DBSCAN clustering algorithms; and analyzing the results in accordance with regulatory standards, including IEC 60071-2. The key findings include the formation of three stable clusters with different fault current modes using the K-Means method, and the identification of a dense zone of characteristic parameters using DBSCAN, which revealed stable and unstable operating conditions. It was established that a resistance range of 50–70 Ohms is optimal in terms of overvoltage limitation and relay protection sensitivity. The cluster centroids reflect typical network operating modes and can be used as references for the design and practical selection of grounding resistance, ensuring both technical and economic feasibility. The significance of the results lies in a comprehensive and well-substantiated approach to the selection of grounding parameters, which ensures effective relay protection, reduces equipment damage risks during faults, and enhances reliability and selectivity in medium-voltage distribution networks. The proposed approach is universal and can be adapted to various network types, making it suitable for further optimization of grounding systems within the Smart Grid concept.
	Keywords: cluster analysis, electric coils, K-Means, DBSCAN, pulsed resistive and point neutral, single-phase cir-cuit diagram. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.10
11	Study of Currents in the Wakes of Vortex Generators on the Blades of Wind Power Turbines Authors: Savelov O.V., Kovalnogov V.N., Chukalin A.V., Kornilova M.I. Ulyanovsk State Technical University, Ulyanovsk, Russian Federation
	Abstract: The article considers the possibility of using vortex generators on the back of wind turbine blades. The main objective of the work is to select the optimal shape of vortex generators for effective boundary layer and separated flow control in the blade back region of wind turbines. To achieve this goal, the following tasks were set: determining the optimal shape of vortex generators installed on the blade backs of wind turbines; development of a model of a surface vortex generator for control-ling the boundary layer and separated flows. The work also examines in detail the formation and de-velopment of separated flows. The most important result is obtaining data on the optimal shape of vortex generators on the blade backs and a prototype of a surface vortex generator for forming flat coherent vortex structures along the blade surface and three-dimensional spiral vortices for influenc-ing the outer boundary of the boundary layer. It is established that surface vortex generators placed on the blade back make it possible to change the flow structure, reduce the energy and scale of tur-bulent vortices, increase the speed of air flow around the blade back, which contributes to an in-crease in lift and energy generation by wind power plants in a wide range of incoming flow veloci-ties. The significance of the obtained results lies in the theoretical and experimental substantiation of the effectiveness of using vortex generators to control the boundary layer along the blade back, their optimal shape, and, ultimately, a method for increasing the coefficient of wind energy use by operating wind power plants.
	Keywords: wind energy system, aerodynamics, particle image velocimetry, vortex generator. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.11
12	Improving the Efficiency of Energy Production in a Distributed Island Power Supply System Authors: Myshkina L.S., Nasibova E.М. Novosibirsk State Technical University Novosibirsk, Russian Federation
	Abstract: Reliability and cost-effectiveness of energy supply are crucial for socio-economic development and investment attractiveness of territories. In areas where there is a high demand for thermal energy, one of the ways to improve energy efficiency is using cogeneration systems with mini-CHP (combined heat and power) plants powered by gas-piston units. The main challenges preventing the full potential of these systems from being realized are the mismatches between electrical and thermal load profiles. The aim of this research is to substantiate the method and choice of technical means for reducing the installed capacity of boiler equipment at a mini-CHP and increasing the utilization rate of installed capacities of heat and electric energy sources in distributed power supply systems. To achieve this goal, we completed the following tasks: an analysis of existing methods for increasing production efficiency and the application of efficiency criteria, as well as the development of a simulation model for a distributed supply system. A methodology was developed for selecting equipment and calculating efficiency indicators, including specific fuel consumption. The paper demonstrates the feasibility of technical solutions for increasing the flexibility of the system through the integration of various equipment, such as heat pumps and heat energy storage systems. A method for selecting a combination of thermal energy sources has been developed. This method allows us to calculate and compare performance indicators for various energy supply systems. To verify our proposed solutions, we applied them to a case study of a regional energy system in a town in the Novosibirsk region. The results confirmed the viability of our approach. The obtained results have practical significance for managing the development of distributed island power systems.
	Keywords: efficiency, energy supply system, specific fuel consumption, installed capacity utilization factor, cogeneration, heat pump, electric boiler, heat storage system, centralized heat supply. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.12
13	Predictive Maintenance Model for Planning Centrifugal Compressor Service Intervals Authors: Goncharov R.A., Taukeev B.B., Kartashov S.V., Kozhukhov Y.V. ITMO University Saint-Petersburg, Russian Federation
	Abstract: This paper presents a predictive methodology for assessing the technical condition of the first stage of an industrial centrifugal compressor to optimize maintenance intervals. The approach integrates computational fluid dynamics (CFD) modelling of gas-dynamic processes within the flow path with machine learning algorithms to predict the decrease in isentropic efficiency caused by surface degradation due to increasing roughness. Numerical simulations were carried out in ANSYS CFX using a verified digital model based on the NZL design methodology, with deviations of key parameters not exceeding 1.5%. This ensured high physical fidelity and enabled the generation of synthetic training datasets. A total of 61 simulations were conducted with varying equivalent sand roughness values to emulate operational degradation corresponding to up to 13 months of service. Five forecasting models of different complexity were applied: exponential-linear regression, polynomial regression with Ridge regularization, Random Forest, Gaussian Process Regression (GPR), and XGBRegressor. Comparative analysis showed that the exponential-linear regression achieved the highest accuracy (R² up to 0.9995) and minimal divergence between training and test datasets (<0.002). Ridge regression on polynomial features demonstrated comparable performance (R² up to 0.9950), providing a balance between interpretability and accuracy. The proposed method combines CFD-based surface roughness simulation, synthetic data generation, and machine learning–based prediction of efficiency degradation. A distinctive feature of the approach is modelling degradation through equivalent sand roughness, reflecting the cumulative effect of surface wear and deposit accumulation. The results provide a foundation for developing intelligent predictive maintenance systems for centrifugal compressors, enhancing reliability, operational stability, and energy efficiency.
	Keywords: centrifugal compressor, machine learning, CFD modelling, surface roughness, Ridge regression, Gaussian Process Regression, XGBRegressor, predictive maintenance, synthetic data. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.13
14	Metaheuristic Optimization of PI Control in Coupled Inductor Sepic Converter for Photovoltaic Applications Authors: 1Kavya Santhoshi B.1, 2Parvathi R.V.L.N.S. 2, Tharpil H.G., 2Vamsi K.M., 2Appaji M. K. 1School of Engineering, Godavari Global University, Rajahmundry, India 2Godavari Institute of Engineering and Technology (A), Rajahmundry, India
	Abstract: Grid-connected PV systems remain essential to supply energy demands as the globe shifts its focus to renewable energy sources (RESs). Although there are many advantages to this integration, there are also a number of issues with power quality and stability at the connection points. The aim of the study is to tackle photovoltaic (PV) energy systems voltage instability poor dynamic response and to increase conversion efficiency in conventional control and converter configurations. The main objectives of the study were achieved by solving the following problems: (i) improving the DC-DC stage's voltage conversion capabilities, (ii) delivering stable DC-link voltage regulation under varied irradiance conditions, and (iii) optimizing the control system's dynamic and steady-state performance. To address these challenges, an intelligent power conversion system has been developed by combining a novel coupled inductor SEPIC (CIS) converter with an Osprey optimized algorithm-based proportional-integral (OOA-PI) controller. The most important result is that the proposed CIS-SEPIC converter and an OOA-PI Controller ensure to step up DC voltage output from the PV array while maintaining voltage stability. This controlled regulated DC output is supplied for a three-phase voltage source inverter ( -VSI) that transforms the DC power into AC power suitable for driving the connected load. The significance of the obtained results lies in improving the quality of electrical energy and reducing its losses. The system has been designed and tested using MATLAB/Simulink, offering better voltage regulation, faster transient response with low harmonic distortion AC output, and improved converter efficiency of 96% compared to the conventional method.
	Keywords: photovoltaic, coupled inductor SEPIC converter, Osprey optimization algorithm, proportional-integral, three-phase voltage source inverter. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.14
15	Dynamic Voltage Restorer using Lemurs-Optimized Cascaded ANFIS-controller for Distributed Power Systems Authors: 1Reddy G.S., 2 Reddy S.K., 3Athimamula S. 1Jyothishmathi Institute of Technology and Science, Karimnagar, Telangana, India. 2 CVR College of Engineering, Mangalpally, Ibrahimpatnam, Hyderabad, India. 3Vidya Jyothi Institute of Technology, Hyderabad, India.
	Abstract: The main objective of this study is to reduce disturbances, such as voltage sags, swells, and fluctuations, increase stability of voltage and Power Quality (PQ) in distributed power systems using an optimized Dynamic Voltage Restorer (DVR) control strategy. These objectives are achieved through the design and optimal tuning of a Cascaded Adaptive Neuro-Fuzzy Inference System (ANFIS) controller using the Lemurs optimization algorithm (LOA). The proposed controller is verified in the MATLAB/Simulink environment systematically for nonlinear and sensitive load conditions, which is a complete verification and testing to establish controller performance for voltage stability, improving dynamic responses, and reliably operating the system under disturbance operating conditions. According to the simulation study, the results show that the DVR controller is able to maintain a consistent load voltage under disturbance, therefore the connected loads are effectively and efficiently utilized within the controlled system. The proposed solution achieves a performance effectiveness of 96%, ensure effective and consistent operation of the system under changing load conditions. The proposed central controller enhances the dynamic performance of the DVR by reducing the settling time to 0.08 s, thus ensuring that performance is better than conventional approaches with fast transient response and higher accuracy. The significance of the results lies in validate that the cascaded ANFIS controller with LOA optimization is a legitimate and computationally efficiency substitute for real-time voltage compensation. This enhances the robustness of sensitive loads, minimizes possible consequences of economic losses and enhances the reliability of distributed networks in modern smart grid infrastructure.
	Keywords: dynamic voltage restorer, lemurs optimized algorithm, cascaded adaptive neuro fuzzy inference system, power quality, voltage sag, swell. DOI: https://doi.org/10.52254/1857-0070.2025.4-68.15