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28,451 Article Results

Low voltage fault ride-through operation of a photo-voltaic system connected utility grid by using dynamic voltage support scheme

10.11591/ijpeds.v16.i3.pp1608-1619
Satyanarayana Burada , Kottala Padma
This research suggests a control technique that makes use of a microgrid's energy storage and to enable low voltage ride through (LVRT) process with a flexible dynamic voltage support (DVS) system. First, the requirements for the microgrid's maximum DVS are stated, together with an explanation of how these requirements depend on the characteristics of the analogous network that the microgrid sees. In order to create a flexible DVS regardless of the changing system circumstances, reference signals for currents that are derived from maximum voltage tracking technique are suggested in this research. These signals take into account the challenges involved with real time parameter assessment in the context of transient voltage disruptions. Second, a control scheme is suggested to allow a microgrid's energy storage-based LVRT operation. Thirdly, a novel approach to energy storage sizing for LVRT operation is offered, taking into account the corresponding network characteristics, grid code requirements, and the rated current value of the power electronic converter. Real-time MATLAB simulations for low-voltage symmetrical faults are used to validate the suggested control technique.
Volume: 16
Issue: 3
Page: 1608-1619
Publish at: 2025-09-01

Optimization of ANN-based DC voltage control using hybrid rain optimization algorithm for a transformerless high-gain boost converter

10.11591/ijpeds.v16.i3.pp1711-1720
Mohcine Byar , Abdelouahed Abounada
This paper introduces an adaptive voltage regulation technique for a transformerless high-gain boost converter (HGBC) integrated within standalone photovoltaic systems. A neural network controller is trained and fine-tuned using the rain optimization algorithm (ROA) to achieve improved dynamic behavior under variable solar conditions. The proposed ROA-ANN framework continuously updates the duty cycle to ensure output voltage stability in real time. Validation was carried out using MATLAB–OrCAD co-simulation under multiple scenarios. Comparative results highlight superior performance of the ROA-ANN controller in terms of convergence speed, overshoot minimization, and steady-state response, outperforming conventional PID and ANN-based methods.
Volume: 16
Issue: 3
Page: 1711-1720
Publish at: 2025-09-01

An efficient machine learning framework for optimizing hyperspectral data analysis in detecting adulterated honey

10.11591/ijeecs.v39.i3.pp1776-1786
Ashwini N. Yeole , Guru Prasad M. S. , Santosh Kumar
Honey adulteration detection involves employing spectral data, often utilizing machine learning (ML) techniques, to identify the presence of impurities or additives in honey. This study aims to explore ML models through the collection of a hyperspectral honey dataset with limited samples and 128 features. Three distinct feature selection (FS) methods i.e., Boruta, repeated incremental pruning to produce error reduction (RIPPER), and gain ratio attribute evaluator (GRAE) are applied to extract important features for decision-making. Then, the feature-selected dataset is classified through four effective ML algorithms, such as support vector machine (SVM), random forest (RF), logistic regression (LR), and decision tree (DT). Accuracy, F1-score, Kappa Statistics, and Matthews correlation coefficient (MCC) are the performance metrics used to assess the results of ML algorithms. RIPPER FS technique gave the best results by improving its accuracy values from 79.05% (primary data) to 91.89% (augmented data) for the RF classifier model and 74.93% (primary data) to 91.89% (augmented data) for the DT classifier model. These detailed examinations of the experiments demonstrate that proper finetuning of the ML methods can play a vital role in optimizing hyperspectral data analysis for detecting adulteration levels in honey samples.
Volume: 39
Issue: 3
Page: 1776-1786
Publish at: 2025-09-01

Early detection of food safety risks using BERT and large language models

10.11591/ijeecs.v39.i3.pp1683-1692
Mohammed El Amin Gasbaoui , Soumia Benkrama , Mostefa Bendjima
Sentiment analysis can be a powerful tool in safeguarding public health. This allows authorities to investigate and take action before a foodborne illness outbreak spreads. This paper introduces a novel system that proactively empowers restaurants to identify potential food safety hazards and hygiene regulation violations. The system leverages the power of natural language processing (NLP) to analyze Arabic restaurant reviews left by customers. By fine-tuning a pre-trained BERT mini-Arabic model on three targeted datasets: Sentiment Twitter Corpus, an Algerian dialect dataset, and an Arabic restaurant dataset, the system achieves an impressive accuracy of 91%. Additionally, the system caters to spoken feedback by accepting audio reviews. We utilized Whisper AI for accurate text transcription, followed by classification using a fine-tuned Gemini model from Google on Algerian local comments and others generated using large language models (LLMs) through few-shot learning techniques, reaching an accuracy of 93%. Notably, both models operate independently and concurrently. Leveraging RESTful APIs, the system integrates the solved sub-solutions from each microservice into a fusion layer for a comprehensive restaurant evaluation. This multifaceted approach delivers remarkable results for both modern standard Arabic (MSA) and the Algerian dialect, demonstrating its effectiveness in addressing restaurant food safety concerns.
Volume: 39
Issue: 3
Page: 1683-1692
Publish at: 2025-09-01

Enhance the performance of 3-phase induction motors with the utilization of a 9-phase winding design

10.11591/ijpeds.v16.i3.pp1528-1536
Zulkarnaini Zulkarnaini , Sepannur Bandri , Erhaneli Erhaneli , Zuriman Anthony , Yusreni Warmi , Arfita Yuana Dewi Rachman
Because of its sturdy design, affordability, and convenience of use, the three phase induction motor is a common kind of electric motor, especially in the industrial sector. This motor design is still being improved to make it work better. For example, permanent magnets are being added to the rotor, control systems are getting better, the number of phases is being increased, and motor winding designs are developing. Nevertheless, the creation of the motor winding design is the least expensive aspect of all these endeavors. By creating a nine-phase winding configuration with a three-layer design in the motor, this study aims to enhance the performance of a three-phase induction motor. This study examined output power, speed, mechanical torque, and motor efficiency in a 3-phase system operation. The study's results indicated that the new design motor worked better, with higher output power (4.27%), rotor speed (0.61%), and mechanical torque (3.47%), despite a minor reduction in efficiency relative to conventional 3-phase induction motors (-0.24%).
Volume: 16
Issue: 3
Page: 1528-1536
Publish at: 2025-09-01

Cancellation of periodic disturbances for dual start induction drives based on a novel robust adaptive control strategy

10.11591/ijpeds.v16.i3.pp1673-1686
Ngoc Thuy Pham , Phu Diep Nguyen
The disturbance cancellation has always been an important area that has received much attention, especially for the nonlinear drive systems as the dual start induction motor (DSIM). In this paper, a new robust adaptive hybrid strategy based on an improved variable-gain quasi-continuous third order sliding mode (VGQSTOSM) algorithm integrated with RC and a load torque disturbance estimator helps to reduce chattering, cancel the periodic and extended load disturbances, and enhance tracking performance effectively. By using third-order sliding mode with variable gain dependent on the magnitude of the sliding variable, this proposal aims to be adaptive. It provides higher gain when far from the sliding surface (is large), leading to faster convergence and lower gain when close to the sliding surface (is small), potentially reducing chattering further and decreasing control effort near the equilibrium. The robustness of the proposed controller is improved because the adaptive gain mechanism effectively compensates for uncertainties or disturbances. Furthermore, a plug-in RC is integrated into the improved high-order sliding mode structure (DRVGQSTOSM), and an estimated load torque disturbance value is also used to help identify and proactively eliminate disturbances. The system stability is assured using Lyapunov theory the virtual control vectors' outputs are chosen based on Lyapunov theory. Simulation results obtained using the MATLAB software confirm the tracking and harmonic disturbance rejection performance as well as the robustness of the proposed control strategy.
Volume: 16
Issue: 3
Page: 1673-1686
Publish at: 2025-09-01

Permanent magnet generator performance comparison under different topologies and capacities

10.11591/ijpeds.v16.i3.pp1516-1527
Ketut Wirtayasa , Muhammad Kasim , Puji Widiyanto , Anwar Muqorobin , Sulistyo Wijanarko , Pudji Irasari
This paper compares the magnetic, electrical, and mechanical characteristics of two permanent magnet generator topologies: single-gap axial flux and single-gap inner rotor radial flux. The study aims to identify how the key parameters fluctuate at each power capacity and investigate the trends in their values as power changes. The power capacities observed are 300 W, 600 W, 900 W, 1200 W, and 1500 W. Simulations used with the help of Ansys Maxwell software to obtain: i) magnetic characteristics without load, including air gap flux density, flux linkage, and induced voltage, ii) electrical performance, consisting of armature current, terminal voltage, voltage regulation, total harmonic distortion, core loss and output power, and iii) mechanical performance, including shaft torque and cogging torque. The last step compares the power density of both topologies. The simulation results show that the axial flux permanent magnet generator (AFPMG) has better air gap flux density, voltage regulation, total harmonic distortion (THD), efficiency, electromagnetic torque, and power density characteristics. Meanwhile, the radial flux permanent magnet generator (RFPMG) is superior in induced voltage and output power. These results conclude that, in general, AFPMG is exceptional from a technical point of view and is more economical when applied to hydro or wind energy systems.
Volume: 16
Issue: 3
Page: 1516-1527
Publish at: 2025-09-01

Nutritional status and anxiety levels of adolescent during COVID-19 pandemic

10.11591/ijphs.v14i3.22550
Ratna Indriawati , Bambang Edi Susyanto , Farah Dita Amany , Tunjung Wibowo
The COVID-19 pandemic has had various health impacts, experienced by all age groups. However, many health problems are experienced by adolescents. The nutritional and psychological issues of teenagers during the COVID-19 pandemic require additional investigation. This study seeks to investigate the nutritional status and anxiety levels of teenagers during the COVID-19 pandemic. The cross-sectional research. Boys and girls aged 14-18 years became the research subject, who was chosen by using incidental sampling. The independent variable is nutritional status. The variable is anxiety. The data was collected by distributing a questionnaire, the assessment of nutritional status using body mass index, and self-rating anxiety scale (SAS/SRAS) for psychological status. It reported that there is no influence between nutritional status and anxiety in adolescents (p>0.05). There is no influence between nutritional status and anxiety in adolescents.
Volume: 14
Issue: 3
Page: 1436-1440
Publish at: 2025-09-01

A model predictive control strategy for enhance performance of totem-pole PFC rectifier

10.11591/ijpeds.v16.i3.pp1687-1700
Le Chau Duy , Nguyen Dinh Tuyen
This paper proposed a simple but effective finite control set-based model predictive control (FCS-MPC) method to control a totem-pole bridgeless boost PFC rectifier (TBBR). The control algorithm selects from the possible switching states an appropriate one that fulfills a predefined cost function. This method also successfully eliminates the zero-crossing current distortion so that the grid current can synchronize well with the grid voltage. The theoretical analysis was presented and verified by simulation. Finally, a 3.3 kW/400 Vdc prototype was fabricated and investigated through various working conditions to realize the effectiveness of the proposed control strategy. Both simulation and experimental results show that the proposed control method can ensure accurate control of DC link output voltage and sinusoidal input current with unity power factor.
Volume: 16
Issue: 3
Page: 1687-1700
Publish at: 2025-09-01

Investigation of optimal tilt, orientation, and tracking of a solar PV system in Iraq

10.11591/ijpeds.v16.i3.pp1914-1925
Ahmed Zurfi , Ali Abdul Razzaq Altahir , Ali Ibrahim
This paper examines the effect of tilt angle and tracking modes on energy performance of a PV system under Iraqi weather conditions. A 5-kWdc rooftop residential PV system is modeled and simulated using system advisor model (SAM) to investigate its optimal configuration of tilt angle and tracking axes for maximum energy extraction. The system is simulated with meteorological datasets for all 18 Iraqi provinces. The effect of soiling losses due to dust accumulation on incident irradiance and energy generation is considered as most Iraqi territories suffer from frequent dust storms yearly. The system annual AC energy and optimal tilt angles are evaluated and compared in five different scenarios including fixed-axis with tilt at latitude, fixed-axis with tilt at annual optimal angle, fixed-axis with tilt at monthly annual angle, one-axis tracking and dual-axis tracking. The results showed that considerable amount of energy is left unharnessed in fixed-axis scenarios when tilt angles are adjusted at latitude and optimal annual values. Using optimal monthly tilt with fixed-axis improved energy extraction by 5-6% for all locations. Energy performance is further improved with one axis tracking. Dual-axis tracking achieved highest energy yield compared to other scenarios. Overall, mid-south provinces provided highest energy opportunities among others.
Volume: 16
Issue: 3
Page: 1914-1925
Publish at: 2025-09-01

DC bus control strategy and implications for voltage source converter system

10.11591/ijpeds.v16.i3.pp1505-1515
Haider Fadel , Ahmed Abdulredha Ali , Mustafa Jameel Hameed
Significantly, the use of power electronic devices in residential and industrial settings has grown significantly in the last several years. Recent advancements in power semiconductors and microelectronics may be the main reason of their growing use in power systems for filtering, conditioning, and compensating. Additionally, the proliferation of semiconductor switches appropriate for high-power applications, and the enhancement of microelectronics enable mixed signal processing and control mechanisms. Furthermore, the concentration on renewable energy sources within the electric utility industry has emphasized the incorporation of power electronic converters into power systems. The operation and control of the regulated DC-voltage power port are examined in this work, a key part in different applications, such as STATCOM, dual mode HVDC converter systems, and aerodynamic wind energy converters with adaptive-speed optimization, emphasizing its significance in upholding a stable voltage level throughout the DC bus. The research also highlights the importance of power electronic converters within contemporary power systems, emphasizing their crucial role in facilitating effective and reliable power distribution. The obtained simulation results confirmed the efficacy of feed forward compensation in stabilizing the voltage responses of the DC bus.
Volume: 16
Issue: 3
Page: 1505-1515
Publish at: 2025-09-01

Advancing power quality via distributed power flow control solutions

10.11591/ijpeds.v16.i3.pp1801-1811
Abdelkader Yousfi , Fayçal Mehedi , Khelifa Khelifi Otmane , Youcef Bot
The growing demand for enhanced power quality and reliable transmission has driven advancements in power flow control technologies. The distributed power flow controller (DPFC) represents an advancement over the unified power flow controller (UPFC). In contrast to the UPFC, the DPFC removes the DC link connecting the shunt and series converters, and redistributes the series converters along the transmission line as single-phase static series compensators. This modification enhances grid performance while maintaining full power flow control capabilities. The DPFC offers several advantages over the UPFC, including higher reliability, improved controllability, and greater cost-effectiveness. The system comprises a shunt converter in conjunction with multiple series converters, each with its own control circuit, all managed by a central control unit. This article presents the implementation of a DPFC model in MATLAB/Simulink. The simulation outcomes indicate that the DPFC significantly contributes to improved voltage stability and enhanced power transfer capability, thereby reinforcing system performance and reliability.
Volume: 16
Issue: 3
Page: 1801-1811
Publish at: 2025-09-01

Torque sharing function optimization for switched reluctance motor control using ant colony optimization algorithm

10.11591/ijpeds.v16.i3.pp1537-1551
Dhiyaa Mohammed Ismael , Thamir Hassan Atyia
Switched reluctance motors (SRMs) are gaining popularity in industrial and automotive applications due to their robust design, fault tolerance, and high torque density, particularly in wide-speed-range operations. However, SRM performance is often limited by torque ripple, speed oscillations, and inefficiencies, which can lead to mechanical stress, vibration, and acoustic noise. Addressing these challenges requires the effective optimization of control strategies. This study aims to enhance the performance of SRM drives by employing an ant colony optimization (ACO) algorithm to optimize the torque sharing function (TSF). The proposed method iteratively tunes TSF parameters to minimize torque ripple and improve speed stability under varying operating conditions. Simulation results demonstrate significant improvements: torque ripple is reduced from a range of –20 Nm to 10 Nm without optimization to below 10 Nm with ACO-based optimization. Similarly, current peaks decrease from 60 A to 5.5 A, ensuring smoother motor operation and enhanced efficiency. Comparative analysis confirms that the ACO-based TSF provides superior tracking of speed set points, reduced mechanical stress, and improved reliability, making it well-suited for high performance applications in both industrial and automotive sectors.
Volume: 16
Issue: 3
Page: 1537-1551
Publish at: 2025-09-01

Machine learning techniques for solar energy generation prediction in photovoltaic systems

10.11591/ijpeds.v16.i3.pp2055-2062
J. Sumithra , J. C. Vinitha , M. J. Suganya , M. Anuradha , P. Sivakumar , R. Balaji
For photovoltaic (PV) systems to be as effective and dependable as they possibly can be, it is vital to make an accurate prediction of the amount of power that will be generated by the sun. Using machine learning, it is now much simpler to forecast the amount of solar energy that will be generated. These approaches are more accurate and are able to adapt to the ever changing conditions of the nature of the environment. We take a look at the most recent machine learning algorithms for predicting solar energy and examine their methodology, as well as their strengths and drawbacks, in this paper. Using performance metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE) makes it possible to evaluate important algorithms like support vector machines, decision trees, and linear regression. The results show that machine learning could help make predictions more accurate, lower the amount of uncertainty in operations, and help people make decisions in real time for PV systems. The study also points out important areas where research is lacking and suggests ways to move forward with the use of machine learning in systems that produce renewable energy.
Volume: 16
Issue: 3
Page: 2055-2062
Publish at: 2025-09-01

Comparative reliability and performance analysis of PV inverters with bifacial and monofacial panels

10.11591/ijpeds.v16.i3.pp1970-1982
Muneeshwar Ramavath , Rama Krishna Puvvula Venkata
In the realm of solar energy systems, the reliability and performance of photovoltaic (PV) inverters play a critical role in ensuring efficient energy conversion and long-term operation. This study delves into a comprehensive reliability-oriented performance assessment of PV inverters, with a particular focus on the comparative analysis between bifacial and monofacial panels. Reliability evaluation is carried out by considering a yearly mission profile with a one-minute sample at Hyderabad, India. A test case of a 3-kW PV system for grid-connected applications is considered. By integrating reliability metrics with performance indicators, we aim to provide a holistic evaluation of PV inverters operating under varying conditions inherent to both panel types. The research methodology involves detailed simulations and field data analysis to capture the nuances of inverter performance influenced by the unique characteristics of bifacial panels, such as their ability to capture light from both sides, compared to the traditional monofacial panels. In this paper, performance parameters such as junction temperature, MCS, and B10 lifetime (system level (SL) and component level (CL)) are evaluated. Key findings highlight the impact of these differences on inverter reliability. The Bi-PV panel exhibits a decreasing trend. In India, CL reliability (B10) is decreased from 34 years to 1.5 years, and SL reliability (B10) is decreased from 24 years to 1 year. In comparison with monofacial panels, the thermal stress on the PV inverter due to the bifacial panel is increased, and reliability is decreased.
Volume: 16
Issue: 3
Page: 1970-1982
Publish at: 2025-09-01
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