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Variable frequency drive based on full-bridge class D for single-phase induction motor

10.11591/ijpeds.v16.i3.pp1701-1710
Budi Pramono Jati , Jenny Putri Hapsari , Muhamad Haddin , Sri Arttini Dwi Prasetyowati
The issue with induction motors lies in speed regulation, which can be addressed by adjusting the motor voltage; however, this affects torque. In contrast, a variable frequency drive (VFD) changes the motor frequency while maintaining a constant voltage. A VFD controller with constant sinusoidal voltage and adjustable frequency can be implemented using an Arduino and a class D full-bridge MOSFET amplifier inverter. This paper discusses the electronic speed control (ESC) of induction motors using VFD regulation, demonstrating how changes in frequency affect motor speed. The system involves an induction motor controlled by a VFD comprising three main components: an AC-to-DC converter, a class-D full-bridge MOSFET inverter, and a variable-frequency sinusoidal signal source. VFDs operate with constant voltage and variable frequency. This method includes the design and testing of VFD hardware and software. The VFD components include: a class-D full-bridge switching inverter, a sinusoidal signal frequency generator (30–70 Hz), an Arduino with custom software, an SMPS power supply, and a step-up transformer. The results indicate that the class-D full-bridge inverter can effectively regulate motor speed through VFD control. The motor speed is almost directly proportional to the frequency: at 30 Hz, the speed is 860 RPM; at 50 Hz, 1472 RPM; and at 70 Hz, 2035 RPM.
Volume: 16
Issue: 3
Page: 1701-1710
Publish at: 2025-09-01

Advances in medical power electronics: applications and challenges

10.11591/ijpeds.v16.i3.pp1983-1990
Hamza Abu Owida , Jamal I. Al-Nabulsi , Nidal Turab , Muhammad Al-Ayyad
Power electronics plays a crucial role in modern medical applications by providing efficient power management, conversion, and regulation across a wide range of devices. In high-power systems, such as medical imaging equipment, power electronics ensure precise control, stable operation, and optimal performance, which are essential for accurate diagnostic imaging. On the other hand, in low-power devices such as wearable health monitors and implantable medical devices, power electronics focus on enhancing energy efficiency and miniaturization. This is vital for extending battery life, reducing the need for frequent recharging or replacement, and improving patient comfort and mobility. This review examines the role of power electronics in diverse medical applications, highlighting its importance in enabling stable performance in critical life-support systems, therapeutic devices, and portable health monitors. Key technologies and power management integrated circuits are explored for their contribution to improving the efficiency, reliability, and longevity of medical devices. The review also addresses significant challenges, including miniaturization, energy efficiency, and regulatory compliance. Future trends such as the development of advanced semiconductor materials, innovations in energy harvesting techniques, and wireless power transfer technologies are also discussed. These advancements are expected to revolutionize the field, driving the next generation of medical devices and shaping the future of healthcare technology.
Volume: 16
Issue: 3
Page: 1983-1990
Publish at: 2025-09-01

Resonant converter for fast-charging applications

10.11591/ijpeds.v16.i3.pp1832-1839
Remala Geshma Kumari , Narahari Krishna Kumari , Kankipati Shravya
Resonant converters (RCs) are gaining attention from the research community due to their significant contributions to the architecture of electric vehicle (EV) charging infrastructure. The primary part of RC is responsible for enabling constant-current (CC) charging, which helps lower inrush current, decrease losses, and improve efficiency. While the load current stays constant during charging using the CC approach, the source current grows linearly with charging time. However, pulling a high source current increases the rating of the inverter switches, which stresses them, raises their temperature, increases heat sink demand, and causes conduction loss—all of which are undesirable. Consequently, the rated CC is provided by the P2 topology of RC, which has a lower peak current source than other topologies and will improve charger performance. However, this assertion must be verified by mathematical modeling, design with theoretical calculations, specifications, and MATLAB simulation before execution. By providing a constant load current of 5 A at a DC source voltage of 200 V, the P2 RC and the conventional LCL RC are designed to compare source current values.
Volume: 16
Issue: 3
Page: 1832-1839
Publish at: 2025-09-01

Design and optimization of hybrid microgrid renewable energy system for electricity sustainability in remote area

10.11591/ijpeds.v16.i3.pp2063-2071
Theresa Chinyere Ogbuanya , Taiwo Felix Adebayo
Off-grid hybrid electrical systems have become a viable option for sustainable energy solutions, meeting the energy supply needs of rural communities. These systems use a broad approach to tackle sustainability, dependability, and environmental protection problems. The suggested hybrid system combines battery storage, biogas generators, and solar photovoltaic (PV) to provide a reliable and strong energy source for Ivoko Village in Enugu State using particle swarm optimization (PSO) and HOMER Pro Software. The paper compares three different configurations of sustainable power systems (HRES) to determine the best architecture that is suitable for rural areas. The result shows that case-1 (biogas/PV/bat) is the best option, with net present cost (NPC) and cost of energy (COE) values of $1,225,914 and 0.2865$/kWh, respectively. The results show that the PSO-based hybrid power system is more cost-effective than the HOMER-based optimizer. The NPC and lower COE for meeting peak demands emphasize the increasing role of biogas system generators as a cost-effective local power source. This highlights the PSO's potential in maximizing hybrid renewable power systems for rural areas, offering a financially viable and sustainable energy solution.
Volume: 16
Issue: 3
Page: 2063-2071
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

Digital twin-based performance evaluation of a photovoltaic system: A real-time monitoring and optimization framework

10.11591/ijpeds.v16.i3.pp2072-2081
Mustafa Fadel , Fajer M. Alelaj
The digital twin (DT) technology implementation in photovoltaic (PV) systems provides an innovative approach to real-time performance monitoring and predictive maintenance. In this paper, an end-to-end DT framework for real-time performance analysis, fault detection, and optimization of a 250 W PV system is proposed. A physics-based equation and AI-based prediction hybrid DT model is developed through MATLAB/Simulink, trained from real data acquired by means of a testbed. The DT simulates the dynamic physical PV system behavior and adjusts itself using self-correcting algorithms to enhance precision in prediction and forecast power output at high fidelity. Results indicate that the DT gives the true response of the PV system with very small differences attributable to model approximations and sensor faults, 95% error minimization after compensation, and a root mean square error (RMSE) of 2.8 W, indicating its applicability for real-time monitoring and predictive main-maintenance. The work here focuses on the feasibility of applying DTs towards the autonomous optimization of distributed renewable energy systems.
Volume: 16
Issue: 3
Page: 2072-2081
Publish at: 2025-09-01

Optimization of two-stage DTMOS operational transconductance amplifier with Firefly algorithm

10.11591/ijpeds.v16.i3.pp1417-1428
Udari Gnaneshwara Chary , Swathi Mummadi , Kakarla Hari Kishore
This paper presents a methodology for optimizing dynamic threshold MOSFET (DTMOS) two-stage operational transconductance amplifiers (OTAs) tailored for biomedical applications through the utilization of the Firefly algorithm. The optimization process focuses on enhancing key performance metrics such as gain, bandwidth, and power efficiency, which are critical for biomedical signal processing, neural interfaces, and wearable healthcare devices. The methodology encompasses circuit architecture definition, Firefly algorithm implementation, fitness evaluation, and result analysis. The optimization results reveal a significant enhancement in performance metrics. Specifically, the number of transistors in the design is 25. The initial overall gain was 76.65 V/V, with a power efficiency (µ) of 1.6. After optimization, the overall gain was significantly improved to 84.029 dB using the Firefly algorithm, demonstrating superior performance compared to existing algorithms. The power efficiency (µ) was also enhanced to 1.702, underscoring the efficiency improvements achieved through optimization. Simulation results and statistical analysis confirm that the Firefly algorithm effectively achieves optimal configurations, improving the robustness of OTA designs against parameter variations. These enhancements validate the algorithm's efficacy in addressing power-performance trade-offs and its suitability for diverse biomedical applications. Physical prototyping of the optimized design further demonstrates real-world functionality, underscoring its practical applicability.
Volume: 16
Issue: 3
Page: 1417-1428
Publish at: 2025-09-01

Predicting transmission losses using EEMD – SVR algorithm

10.11591/ijpeds.v16.i3.pp2122-2129
Hesti Tri Lestari , Catherine Olivia Sereati , Marsul Siregar , Karel Octavianus Bachri
This work introduces a predictive model for evaluating transmission losses in the Java-Bali electrical system using ensemble empirical mode decomposition (EEMD) and support vector regression (SVR) techniques. Transmission losses, a critical aspect of energy efficiency, are affected by several operational aspects, such as load flow, energy composition, peak load, and meteorological factors such as transmission line temperature. Transmission losses data were decomposed into many intrinsic mode functions (IMFs) by EEMD, effectively capturing both high-frequency (short-term) and low-frequency (long-term) trends. The SVR algorithm, utilizing a radial basis function (RBF) kernel, was subsequently employed to predict the deconstructed IMFs, facilitating accurate predictions of transmission losses. The proposed EEMD-SVR model achieved a mean absolute error (MAE) of 5.43%, with the highest error observed during the period of abrupt load shifts. These results confirm the model’s strength in identifying long-term transmission loss patterns, making it suitable for system planning and operational forecasting. While the model exhibited high prediction accuracy, especially in recognizing long-term trends, it faced limitations in accurately predicting abrupt changes in transmission losses. Therefore, future improvements should aim to enhance responsiveness to sudden changes in the system dynamics. The result suggests that the EEMD SVR model can proficiently assist power system operators in monitoring and mitigating transmission losses.
Volume: 16
Issue: 3
Page: 2122-2129
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

Smart energy management in renewable microgrids: integrating IoT with TSK-fuzzy logic controllers

10.11591/ijpeds.v16.i3.pp1620-1627
Moazzam Haidari , Vivek Kumar
Hybrid microgrids powered by renewable energy sources are gaining popularity globally. Photovoltaic (PV) and permanent magnet synchronous generator (PMSG)-based wind energy systems are widely used due to their ease of installation. However, wind and solar energy are unpredictable, leading to fluctuating power generation. Simultaneously, load demand varies randomly, making it necessary to integrate storage devices to maintain a balance between generation and consumption. To enhance system economy, a small battery is combined with a hydrogen-based fuel cell and electrolyzer for efficient energy storage and management. A robust energy management system (EMS) is critical to ensure power quality and reliability across all microgrid components. Maximum power point trackers (MPPTs) are employed to maximize renewable energy utilization. Frequency stability and ensuring power balance is important in autonomous microgrids, especially during rapid load or source variations. This paper presents a novel fuzzy rule-driven Takagi-Sugeno-Kang (TSK) controller for the EMS, ensuring fast, precise responses and improved microgrid reliability.
Volume: 16
Issue: 3
Page: 1620-1627
Publish at: 2025-09-01

Improving electrical energy efficiency through hydroelectric power and turbine optimization at the El Oued water demineralization plant in Algeria

10.11591/ijpeds.v16.i3.pp1881-1896
Khaled Miloudi , Ali Medjghou , Ala Eddine Djokhrab , Mosbah Laouamer , Souheib Remha , Yacine Aoun
This paper presents an investigation into the energy potential of the Albian aquifer in the Algerian Sahara at the El Oued water demineralization plant, focusing on its capacity to generate electrical power due to its high-pressure and high-temperature water reserves. We designed and implemented a turbine-generator system to convert hydraulic energy into electricity, achieving an average annual energy output of 1,804,560 kWh, which translates to a financial gain of approximately 345,888,600 DZD per year from energy savings. The selection of a Francis turbine was justified based on its efficiency, which ranges from 90% to 95%, and the system design was simulated using MATLAB-Simulink, demonstrating its robustness and effectiveness in managing the electrical network parameters. Our economic analysis indicates a high return on investment, confirming the feasibility of utilizing the Albian aquifer as a strategic asset for clean and reliable energy production in the region.
Volume: 16
Issue: 3
Page: 1881-1896
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

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

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

Synchronous generator system identification via dynamic simulation using PSS/E: Malaysian case

10.11591/ijpeds.v16.i3.pp1658-1672
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
The synchronous generator (SG) plays a crucial role in power systems by serving as a stable and reliable source of electrical energy. The performance of an SG hinges on its standard parameters, which can be derived through dynamic tests. This study introduces a method for determining the standard parameters of an SG from dynamic tests conducted via power system simulation for engineering (PSS/E). The proposed method entails conducting several key tests on the generator, including a direct-load rejection test, excitation removal test, quadrature-axis load rejection test, arbitrary axis load rejection test, and open-circuit saturation test. The results obtained from these tests are then utilized to calculate the standard parameters of the SG accurately. To validate the effectiveness of the method, simulation data from the SG, as well as the designed initial data, are utilized. Statistical analysis reveals that the maximum relative error is equal to or less than 2.7% of the design values for all standard parameters, emphasizing the robustness and accuracy of the proposed method. The methodology presented in this study can complement field or site measurements, as it enables the verification of system parameters through dynamic simulations.
Volume: 16
Issue: 3
Page: 1658-1672
Publish at: 2025-09-01
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