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28,451 Article Results

A new approach for optimal sizing and allocation of distributed generation in power grids

10.11591/ijpeds.v16.i3.pp1598-1607
Hudefah Alkashashneh , Ayman Agha , Mohammed Baniyounis , Wasseem Al-Rousan
This paper presents a methodology for optimizing the allocation and sizing of distributed generators (DG) in electrical systems, aiming to minimize active power losses on transmission lines and maintain bus voltages within permissible limits. The approach consists of two stages. First, a sensitivity based analysis is used to identify the optimal candidate bus or buses for DG placement. In the second stage, a new random number generation method is applied to determine the optimal DG sizing. Moreover, a ranking for the optimal locations and sizes is given in case the optimal location is unavailable in real-world scenarios. The proposed methodology is demonstrated through a straightforward algorithm and tested on the IEEE 14-bus and IEEE 30-bus networks. Numerical simulations in MATLAB illustrate the effectiveness of the proposed approach in finding the optimal allocation of DG and the amount of active power to be allocated at the candidate buses, considering the inequality constraints regarding voltage limits and DG allowable power. The paper concludes with results, discussions, and recommendations derived from the proposed approach.
Volume: 16
Issue: 3
Page: 1598-1607
Publish at: 2025-09-01

Micro short circuit fault diagnosis in Li-ion cell

10.11591/ijpeds.v16.i3.pp2103-2111
S. Gomathy , Boopathi Dhanasekaran , Sivabalakrishnan Ramasamy , Radha Jayaram , Sabarimuthu Muthusamy , A. T. Sankara Subramanian
Micro short circuits (MSCs) in lithium-ion battery cells are a critical safety concern, potentially leading to thermal runaway, internal short circuits, overheating, and battery degradation. Compared to normal cells, MSC fault cells exhibit reduced capacity with each charge-discharge cycle and an increasing state of charge (SOC) deviation over time. To differentiate normal cells from MSC fault cells, a fault diagnosis method based on remaining charge capacity (RCC) estimation is proposed. After each charge discharge cycle, the cell’s RCC is compared to a safe threshold value. The method uses the charge cell voltage curve (CCVC) of a fully charged reference cell to estimate RCC via standard CCVC hypothetical conversion. This approach’s accuracy is validated in constant power and constant current charging scenarios. MSC leakage current is calculated by incrementing RCC after each charge, and then converted to MSC resistance. A MATLAB/Simulink model of a battery pack with an MSC fault was developed to test the method across various charge cut-off voltages. The diagnostic procedure’s applicability to ageing cells, constant power, and multi-step charging is further confirmed through experiments with external resistance, enhancing MSC detection before thermal runaway becomes unmanageable.
Volume: 16
Issue: 3
Page: 2103-2111
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

Core machine learning methods for boosting security strength for securing IoT

10.11591/ijeecs.v39.i3.pp1891-1899
Sneha Nelliyadan Pavithran , Jayanna Veeranna Gorabal
Internet-of-things (IoT) revolutionized the mechanism of larger scale of network system offering more engaged, automated, and resilient data dissemination process. However, the resource-limited IoT devices potentially suffers from security issues owing to various inherent weakness. Artificial intelligence (AI) and machine learning (ML) has evolved more recently towards boosting up the security features of IoT offering a secure environment with higher privacy. Till date, there are various review papers to discuss elaborately security aspect of an IoT; however, they miss out to present the actual gap existing between commercial available products and research-based models. Hence, this paper contributes towards discussing the core taxonomy of evolving security methods using ML along with their research trend to offer better insight to existing state of effectiveness. The study further contributes towards highlighting the potential trade-off between the real-world solution and on-going ML based approaches.
Volume: 39
Issue: 3
Page: 1891-1899
Publish at: 2025-09-01

Modelling and optimization of hybrid renewable energy system using SBLA-MAT algorithm

10.11591/ijpeds.v16.i3.pp1897-1913
Arun Kumar Udayakumar , P. Ashok , Mohan Das Raman , Krishnakumar Ramasamy , Mohammad Amir
In order to enhance the reliability and economic feasibility of power systems, this research presents a hybrid control method for the optimal design of hybrid renewable energy sources (RES), including fuel cells, solar photovoltaic (PV), and wind power. Optimization of the power system to enhance efficiency and reduce downtime is achieved using the side blotched lizard optimization with multi-objective artificial tree algorithm (SBL MAT). The research intends to reduce costs in wind, PV, and FC scenarios and make it reliable for load delivery at a low cost and high level of dependability. While a mathematical model of SBL behavior demonstrates the need to discover and implement global optimizing approaches, the MAT algorithm resolves the supervised classification challenge. Possible benefits of the proposed technology include increased reliability and decreased maintenance costs for electrical systems. The proposed approach enables cost-effective and reliable load generation from PV, wind, and fuel cell systems, regardless of the volatility of the weather. Using MATLAB/Simulink, the assessment of parameters like recall, specificity, accuracy and precision is carried out and the results were 99.91%, 99.85%, 99.65%, and 99.325%, respectively. The parameters loss of load expectation (LOLE) and loss of energy expectation (LOEE) are calculated for analysis using both current and future technology.
Volume: 16
Issue: 3
Page: 1897-1913
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

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

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

Modeling and simulation of klystron-modulator for linear accelerators in PRTA

10.11591/ijpeds.v16.i3.pp1822-1831
Wijono Wijono , Dwi Handoko Arthanto , Galih Setiaji , Angga Dwi Saputra , Taufik Taufik , Andang Widi Harto
Approximately 70% of commercial industries worldwide use electron accelerator technology for various irradiation processes. The advantages of irradiation processes compared to thermal and chemical processes are higher output levels, reduced energy consumption, less environmental pollution, and producing superior product quality and having unique characteristics that cannot be imitated by other methods. Research Center for Accelerator Technology (PRTA), BRIN, Indonesia is developing standing wave LINAC (SWL) for food irradiation applications at S-band frequencies (±2856 MHz), electron energy of 6-18 MeV, and an average beam power of 20 kW. This paper aims to model, simulate, and analyze the klystron modulator in the RF linear accelerator (LINAC). The klystron modulator is the main component of the RF LINAC, which functions to supply klystron power with the order of megawatt peak DC, so that the klystron can amplify the low-level RF signal from the RF driver into a high-power RF signal with a power of 2-6 MW peak. The klystron modulator modeling is carried out based on mathematical modeling, then simulated using LTspice to analyze the system performance of the klystron modulator. The results of the klystron modulator modeling simulation show stable system performance and dynamic response. So that it meets the specifications of the 6-18 MeV SWL LINAC being developed by PRTA-BRIN.
Volume: 16
Issue: 3
Page: 1822-1831
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

Improved hybrid DTC technology for eCAR 4-wheels drive

10.11591/ijpeds.v16.i3.pp1566-1585
Njock Batake Emmanuel Eric , Nyobe Yome Jean Maurice , Ngoma Jean Pierre , Ndoumbé Matéké Max
This article deals with the design of a hybrid controller (HyC). It combines fuzzy logic (FL), adaptive neuro-fuzzy inference system (ANFIS). It is combined with direct torque control (DTC). This HyC-DTC combination is designed to improve the technical performance of a 04-wheel drive electric vehicle (EV). A stress test is identically applied to the DTC combined with the FL (FDTC) and to the HyC-DTC in order to certify the suitability of this new control following a cross-validation. This is based on dynamic stability criteria (overshoot, rise time, accuracy), analysis of torque and flux oscillations, and the EV's robustness symbol. The EV's magnetic quantities are managed by a master-slave module (VMSC). Simulations are carried out using MATLAB/Simulink software. The HyC-DTC achieves near-zero accuracy like the FDTC, with overshoot around 0.2% less than the FDTC, and torque oscillation amplitude around 4 times less than the FDTC. However, its rise time is 0.045% greater than that of the FDTC. It is therefore slower, but more precise and suitable for EV transmission systems in terms of safety and comfort.
Volume: 16
Issue: 3
Page: 1566-1585
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

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

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
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