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28,296 Article Results

Intelligent MPPT system improved with sliding mode control

10.11591/ijpeds.v16.i3.pp1926-1938
Said Dani , Asmaa Drighil , Khadija Abdouni , Khalid Sabhi
The sharp rise in global energy demand over recent decades has necessitated the exploration of alternative energy sources. Solar energy, known for being both pollution- and fuel-free, stands out as a preferred choice. However, its efficiency is sensitive to factors like temperature fluctuations and solar irradiation. To optimize energy extraction, a maximum power point tracking algorithm is crucial for photovoltaic systems. This paper proposes a robust sliding mode control enhanced with an artificial neural network to achieve the Maximum Power Point in a stand-alone PV system. The artificial neural network determines the reference voltage, which is then regulated by the sliding mode control to match the photovoltaic array voltage. The performance of the suggested controller is compared to that of a proportional integral-based neural network controller and the perturb and observe method using MATLAB/Simulink. The results show that the suggested method provides excellent tracking performance and rapid convergence even under quickly changing weather conditions, highlighting its efficiency and robustness.
Volume: 16
Issue: 3
Page: 1926-1938
Publish at: 2025-09-01

Accurate state of health estimation using hybrid algorithm for electric vehicle battery pack performance and efficiency enhancement

10.11591/ijpeds.v16.i3.pp1438-1445
Rajesh Kumar Prakhya , Puvvula Venkata Rama Krishna
Temperature fluctuations, overcharging, and over-discharging are all issues that can cause fast deterioration, capacity loss, and thermal runaway in lithium-ion batteries (LIBs). To overcome these challenges, a hybrid model combining a stacked recurrent neural network (SRNN) and bidirectional long short-term memory (biLSTM) is presented for a reliable state of health (SoH) estimate. This model finds subtle patterns in battery data using SRNN layers to capture sequential dependencies and biLSTM modules to solve long-term temporal correlations while avoiding vanishing gradient concerns. The effectiveness of model is assessed by performance measures such as root mean square error (RMSE), mean absolute error (MAE), and maximum error (MAX), which demonstrate its superiority for precise SoH estimation. The stacked RNN-based SoH estimation achieves superior accuracy, with RMSE, MAE, and MAX error levels of 1.5%, 0.8%, and 4.84%, respectively, compared to GRU’s higher errors (3.8%, 3%, and 5.5%). Stacked RNN hierarchically processes sequential battery data, effectively capturing complex temporal relationships, and ensuring accurate and reliable SoH estimation for LIBs.
Volume: 16
Issue: 3
Page: 1438-1445
Publish at: 2025-09-01

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

Optimizing slow-charging EV loads with a two-layer strategy to enhance split-phase voltage quality and mitigate issues in PDNs

10.11591/ijpeds.v16.i3.pp1472-1483
Attada Durga Prasad , Manickam Siva , Alla Srinivasa Reddy
Power distribution networks (PDN) were mostly affected by the voltage imbalances created by the slow charging of electric vehicles (EV), were there random load into the PDN system, causing split-phase voltage quality (SPVQ) issues. Hence, to mitigate the problems associated with EVs’ slow charge in distributed phases of the power system, a multi-layer charging strategy is proposed considering the following constraints in the system: voltage deviation (VD) and voltage harmonics (VH) in split phase (SP). Further multi-layer control is associated with an inner layer equipped with hybrid non-dominated sorting genetic algorithm (NSGA-II) to select the optimal phase for charging the EV and send it to the output layer where a SP current algorithm is utilized so that voltage quality can be fed in loop to inner layer so that iterations were performed to satisfy the convergence condition. Simulation results in MATLAB demonstrate a voltage unbalance (VU) reduction of up to 32.81%, a maximum VD reduction of 9.11%, and a VH reduction of 6.25% at key grid nodes. The proposed method significantly enhances PDN efficiency and maintains voltage quality within national standards across 1,000 to 5,000 EV connections. The generated results reflected the optimal improvement in SPVQ, and the harmonics content reduced further; PDN operational efficiency also improved to a greater extent.
Volume: 16
Issue: 3
Page: 1472-1483
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

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

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

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

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

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
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