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28,428 Article Results

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

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

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

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

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

Photovoltaic energy harvesting for the power supply of medical devices

10.11591/ijpeds.v16.i3.pp1962-1969
Hamza Abu Owida , Basem Abu Izneid , Nidal Turab
The increasing demand for sustainable and reliable power sources in portable and implantable medical devices has led to growing interest in photovoltaic (PV) energy harvesting. Traditional power sources, such as batteries, are limited by finite energy capacity and frequent replacement or recharging needs, particularly in implantable devices where surgical intervention is required for battery replacement. Photovoltaic energy harvesting, which converts light into electrical energy, offers a promising alternative, especially in environments with consistent light exposure. This review provides an in-depth analysis of the advancements in PV technologies for powering medical devices. It covers various types of PV materials, design innovations, and the integration of energy storage systems. Additionally, the review highlights the application of PV systems in both external and implantable medical devices, while addressing critical challenges such as ensuring biocompatibility, optimizing performance in low-light conditions, and miniaturizing PV systems for implantation. The potential of PV energy harvesting to improve device longevity and reduce the need for invasive procedures is emphasized. This review concludes by outlining the current challenges and future directions needed to achieve widespread clinical adoption, aiming to contribute to the development of sustainable power solutions in healthcare.
Volume: 16
Issue: 3
Page: 1962-1969
Publish at: 2025-09-01

An analytical technique for failure analysis and reliability assessment of grid daily outage performance in distributed power system

10.11591/ijpeds.v16.i3.pp1852-1864
Jacob Kehinde Ogunjuyigbe , Evans Chinemezu Ashigwuike , Kafayat Adeyemi , Ngang Bassey Ngang , Timothy Oluwaseun Araoye , Isaac Ojochogwu Onuh , Benson Stephen Adole , Solomon Bala Okoh , Iboi Endurance
This paper modeled and analyzed the reliability performance of the 132/33 kV substation in Abuja, Nigeria through the historical data collected from the APO substation using MATLAB 2021b. The probability distribution model was applied to determine the daily feeder’s outage using Reliability, availability, mean time to repair (MTR), Failure rate, distribution indices, and mean time between failures (MTBF). Due to the application of smart energy meters, the use of prepaid energy meters has helped to regulate energy demand, reduce network overloading especially during peak hours, and minimize the cost of energy consumed. There are more forced failures in the distribution system due to the switchgear and Transformer failures. There are more forced failures in the distribution system since 2013, which caused a reduction in the number of interruptions even with an increase in several customers linked to the transmission network. The result shows that the system was most available in the year 2015 with an average service availability index (ASAI) value of 98.9971%. The system was least available in year 2011 with an ASAI value of 98.6558%. The paper recommended that there should be interconnections between different feeders through proper configuration of switches or reclosers, to reduce failure occurrence in the network.
Volume: 16
Issue: 3
Page: 1852-1864
Publish at: 2025-09-01

Enhancement of power quality of grid integrated photo voltaic system using active power filter

10.11591/ijpeds.v16.i3.pp2017-2029
Praveen Kamat , Anant Naik
The world's population's energy needs are growing daily, while at the same time, fossil fuels are being reduced at an alarming rate. Fossil fuel burning also increases pollution and causes global warming. Renewable energies are now being extensively used to generate electricity, so the dependence on fossil fuels is considerably reduced. Among the primary sources of alternative energy used to create power is photovoltaic (PV) technology. A grid connected PV system is the most widely recommended. When PV is linked to the grid, two main issues are the maximum power that can be taken out of it and the quality of the electricity placed into it. With the help of neural networks, the maximum power point tracking (MPPT) technology has been developed to increase the PV array's power harvesting. An active power filter (APF) had been created and analyzed using Instantaneous Reactive Power Theory, including the Chebyshev II low-pass filter. As required by IEEE 519, the total harmonic distortion (THD) with injected source current has been confirmed well within 5%. These results demonstrate that this method is a simple and efficient way to inject harmonic-free currents into the grid.
Volume: 16
Issue: 3
Page: 2017-2029
Publish at: 2025-09-01

Wireless charging Class-E inverter for zero-voltage switching over coupling coefficient range

10.11591/ijpeds.v16.i3.pp1752-1764
Anon Namin , Chuchat Donloei , Ekkachai Chaidee
A novel and practical methodology is presented in this study for designing contactless wireless energy systems using resonant-mode Class-E converters, aiming to sustain efficient soft-transition switching under various levels of magnetic coupling, even under coil misalignment. The approach integrates the wireless power transfer (WPT) circuit with the inverter’s series resonant network and analytically derives the relationship between the coupling coefficient and impedance phase angle to identify zero voltage switching (ZVS) conditions. A key contribution is the use of the maximum expected coupling coefficient as a critical design point to ensure ZVS across practical variations. A complete step-by-step design procedure is provided. Simulation and experimental results confirm that the inverter achieves and maintains ZVS for coupling values in the range 0 < k ≤ kdesigned, with efficiencies reaching up to 95%. This work supports the advancement of soft-switching inverter design to enable robust and efficient WPT systems under practical misalignment conditions.
Volume: 16
Issue: 3
Page: 1752-1764
Publish at: 2025-09-01

Islanding detection of integrated DG system using rate of change of frequency over reactive power

10.11591/ijpeds.v16.i3.pp1637-1644
B. V. Seshu Kumari , Ambati Giri Prasad , S. Sai Srilakshmi , Karri Sairamakrishna Buchireddy , Ch. Rami Reddy
This paper offers a passive islanding detection method that is effective for distributed generation. When a distributed generator (DG) keeps a location powered even when access to the external electrical grid is lost, this circumstance is referred to as islanding. The power distribution system currently includes distributed generators (DGs), which provide inexpensive electricity and have fewer environmental impacts. Sometimes, these DGs continue to supply the nearby loads because of line outages and islands made by system separations. As a result, there are scenarios with unacceptable power quality. The islanding is identified if the result of the rate of change of frequency over reactive power exceeds the threshold value. The MATLAB test results from this study demonstrate the effectiveness of the suggested approach for different islanding and non-islanding scenarios.
Volume: 16
Issue: 3
Page: 1637-1644
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

Optimizing energy efficiency and improved security in wireless sensor networks using energy-centric MJSO and MACO for clustering and routing

10.11591/ijeecs.v39.i3.pp1964-1975
Srinivas Kalaskar , Channappa Bhyri
Wireless sensor networks (WSNs) play a pivotal role in various applications, but their energy-constrained nature poses significant challenges to their sustainable operation. In this paper, we propose a novel approach to enhance energy efficiency in WSNs by leveraging energy-centric multi-objective jaya search optimization (MJSO) and multi-objective ant colony optimization (MACO) for clustering and routing. Our method aims to address the energy consumption issues by optimizing clustering and routing strategies simultaneously. The energy-centric MJSO algorithm is employed to intelligently organize sensor nodes into clusters, considering energy consumption, network coverage, and connectivity. The multi-objective MACO algorithm optimizes routing paths by balancing energy consumption and network lifetime objectives. Through integration and simulations, the approach enhances energy efficiency in WSNs for various applications like environmental monitoring and smart cities, advancing energy-efficient clustering and routing. By integrating energy-centric MJSO and MACO into clustering and routing protocols, WSNs can achieve significant improvements in energy efficiency and security while maintaining reliable communication and data delivery.
Volume: 39
Issue: 3
Page: 1964-1975
Publish at: 2025-09-01

Modeling, tuning, and validating of exciter and governor in combined-cycle power plants: a practical case study

10.11591/ijpeds.v16.i3.pp1645-1657
Saleh Baswaimi , Renuga Verayiah , Tan Yi Xu , Nagaraja Rupan Panneerchelvan , Aidil Azwin Zainul Abidin , Marayati Marsadek , Agileswari K. Ramasamy , Izham Zainal Abidin , W. Mohd Suhaimi Wan Jaafar
Exciter and governor systems are critical to regulating power output and maintaining stability in power systems. Despite their significance, there is a lack of practical methodologies that leverage real power plant data for modeling, tuning, and validation. This research paper seeks to fill this gap by presenting a methodology that utilizes a transfer function and control algorithms for tuning and validation. The proposed approach is demonstrated through a case study of a practical combined-cycle power plant in Malaysia. The control algorithm's effectiveness is verified through MATLAB and Simulink simulations. Post-tuning assessments confirm the method’s ability to accurately determine tunable control parameter settings, meeting system requirements while ensuring grid stability and reliability. This versatile approach can be applied to various power plant configurations, making it a valuable tool for optimizing operations.
Volume: 16
Issue: 3
Page: 1645-1657
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
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