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29,922 Article Results

Boost efficiency performance through the enhancement of duty cycle based MPPT algorithm

10.11591/ijape.v14.i3.pp541-550
Ahmed Badawi , I. M. Elzein , Walid Alqaisi , Al Hareth Zyoud
The use of direct power control (DPC) has become popular as an effective control strategy for pulse width modulated (PWM) converters. The incremental conductance algorithm (INC) is utilized to control the duty cycle (D) in tracking the optimal point to increase power efficiency in wind energy conversion systems (WECS). WECS parameters are adjusted to achieve unity power factor, allowing the system to extract maximum power (𝑃𝑚𝑎𝑥) from WECS. Simulation results show that wind speed has a significant impact on the captured power, with a proportional relationship between wind speed and power. Control strategies are employed to optimize the (D) to reach the desired operating point. A DC-DC boost converter is connected to WECS, where the (D) controls the MOSFET to maintain 𝑉𝑜𝑢𝑡 at the optimal level on the DC link. Various wind speed profiles are simulated in this study to evaluate system efficiency, especially under conditions of rapid wind speed fluctuations. The controller based on (D) demonstrates superior tracking performance through the DC link, ensuring that 𝑉𝑜𝑢𝑡 remains at an optimal level.
Volume: 14
Issue: 3
Page: 541-550
Publish at: 2025-09-01

Investigation of DC-AC converter control techniques with enhanced MOSFET gate driver

10.11591/ijape.v14.i3.pp676-687
Elmourabit Bouazza , Akaaboune Jalil , Oulaaross Mohamed , Benchagra Mohamed
To promote the use of photovoltaic (PV) systems and reduce costs, it is crucial to develop innovative approaches for grid integration, thereby contributing to global power generation. This article presents the development of an integrated power circuit using the TOSHIBA-TLP350 as a gate driver for the implementation of a single-phase H-bridge inverter, combined with inductor–capacitor–inductor (LCL) filters. This circuit was designed and controlled using a high-frequency pulse width modulation (PWM) signal generated by an ATmega328P microcontroller board, with a predefined program, to facilitate the filtration and reduction of both current and voltage harmonics present at the output of the filters. The study primarily focuses on a grid-connected mode of operation but also demonstrates adaptability to the islanded mode. The proposed application in this article can be adapted to other renewable energy conversion systems. The effectiveness of this achievement is demonstrated through detailed experimental results, highlighting the potential benefits for cost reduction and performance improvement of photovoltaic systems.
Volume: 14
Issue: 3
Page: 676-687
Publish at: 2025-09-01

Design of a binary weighted multilevel voltage source inverter for renewable energy purposes

10.11591/ijape.v14.i3.pp712-721
Abdulkareem Mokif Obais , Ali Abdulkareem Mukheef
The flexibility and linearity of renewable energy generation techniques motivate the efforts to find high-performance circuitries capable of integrating the generation stations of renewable energy with the utility grid. As a result of its potential for power modules exploited in new generations of semiconductor switching devices, the voltage source inverter (VSI) has become widespread in the applications of renewable energy systems. In this paper, a new configuration of multilevel VSI is introduced. It is constructed of a unidirectional voltage supply having 15-nonzero levels and feeding a single-phase VSI equipped with an extra-freewheeling circuit. The output voltage of this configuration has 31 different voltage levels following a sinusoidal path. The unidirectional voltage supply is built of eight solid-state switching devices and four binary weighted DC voltage sources, which are realized by using appropriate solar panels. The simulation results of the introduced configuration have revealed almost sinusoidal output voltage and current for both inductive and resistive appliances. The number of employed switching devices is largely reduced compared to a conventional multilevel VSI. No harmonic reduction circuit or traditional pulse width modulation technique is employed in the current design. This system is designed and tested on PSpice.
Volume: 14
Issue: 3
Page: 712-721
Publish at: 2025-09-01

Mitigating mismatch power losses in photovoltaic systems under partial shading: a comparative study of series-parallel and alternative configurations

10.11591/ijape.v14.i3.pp588-599
Raghad Adeeb Othman , Omar Sharaf Al-Deen Yehya Al-Yozbaky , Ali Abbawi Mohammed Alabbawi
Utilizing the photovoltaic effect, photovoltaic (PV) systems are a popular technique for capturing solar energy and turning sunlight into electricity. However, environmental factors, especially shade, significantly impact photovoltaic system efficiency. Shadows cast on PV panels by surrounding structures, trees, accumulated dirt, clouds, and debris can seriously impair their performance. The purpose of this study was to investigate how shade affects photovoltaic systems utilized in residential settings. Series-parallel (SP) topology for PV system have been investigated. Additionally, in this work, a PV system of 5 kW of the residence home has been proposed and multi cases of shading examined. Through the results obtained when partial shading was applied, it was found that the highest efficiency of the system was when partial shading irradiance (Ir = 500 W/m2) was applied to one column (5 modules) as 82.84%, while the worst and least equipped case was when the shading was applied to the corners and random shading at (8 modules), where the efficiency decreased to approximately 39.24% and 40.64% respectively.
Volume: 14
Issue: 3
Page: 588-599
Publish at: 2025-09-01

Study of the development of tandem solar cells to achieve higher efficiencies

10.11591/ijape.v14.i3.pp647-655
Debani Prasad Mishra , Jayanta Kumar Sahu , Umamani Subudhi , Arun Kumar Sahoo , Surender Reddy Salkuti
Tandem solar cells are the brand-new age revolution within the photovoltaic (PV) enterprise thanks to their higher power conversion efficiency (PCE) capability as compared to single-junction solar cells, which are presently dominating, however intrinsically restrained. With the appearance of steel halide perovskite absorber substances, manufacturing extremely efficient tandem solar cells at an inexpensive price can profoundly regulate the future PV landscape. It has been formerly seen that tandem solar cells primarily based on perovskite have confirmed that they can convert mild more efficiently than stand-alone sub-cells. To reap PCEs of greater than 30%, numerous hurdles have to be addressed, and our understanding of this interesting era has to be accelerated. On this, a technique of aggregate of substances was followed and via a modified numerical technique, it was decided what preference of substances for the pinnacle and bottom sub-cell consequences in a better fee of electricity conversion efficiency (PCE). Through this study, it was discovered that the use of germanium telluride (GeTe) backside subcellular together with perovskite (MAPbI3-xClx) as pinnacle subcell can offer an excessive performance of 46.64% compared to a tandem mobile with perovskite (MAPbI3)/CIGS and perovskite (MAPbI3)/GeTe which produce decrease efficiencies. SCAPS-1D was used to evaluate and simulate the overall performance of the developed tandem cells.
Volume: 14
Issue: 3
Page: 647-655
Publish at: 2025-09-01

Potential as biogas energy and organic fertilizer: a mixture of rice husks and cow dung on full scale anaerobic digestion

10.11591/ijape.v14.i3.pp533-540
Hashfi Hawali Abdul Matin , Syafrudin Syafrudin , Suherman Suherman , Budiyono Budiyono , Iqbal Syaichurrozi
Rice husk is a biomass that can potentially be converted into biogas energy. In this research, a study was carried out regarding the effect of alkaline pretreatment and then a study related to the potential for developing biogas from rice husks in Indonesia and a study related to the potential utilization of biogas by-products in the form of slurry as solid organic fertilizer. So, the main objective is to determine the effect of alkaline pretreatment of rice husks on the potential development of rice husks as raw material for biogas production on a full-scale anaerobic digestion (AD). Research related to the effect of alkaline pretreatment using 3% NaOH by immersion in the substrate for 24 hours was carried out on a lab scale. The variable TS is set at 27%, C/N ratio is 35, uses a 2-liter digester, and measurements are carried out every other day for 60 days. Furthermore, the up-scale was carried out with an AD fixed dome model with a volume of 6 m3. In this study, it was found that pre-treatment with 3% NaOH increased biogas productivity by 1.6 times higher. The potential for rice husk to be converted into biogas energy can reach 3.5 million liters of biogas by 2022. The by-product of biogas in the form of slurry also has the potential to be used as solid organic fertilizer directly. Parameter tests that have been carried out show that the slurry in biogas from rice husks that have gone through a 60-day AD fermentation process complies with the Indonesian National Standard (SNI) 7763:2018 concerning solid organic fertilizers.
Volume: 14
Issue: 3
Page: 533-540
Publish at: 2025-09-01

OFF-grid efficiency evaluation of an inverter dependent on solar PV generator in Iraq

10.11591/ijape.v14.i3.pp761-768
Bilal Abdullah Nasir , Kutaiba Khalaf Khaleel , Mohammed Ahmed Khalaf
The solar photovoltaic (PV) inverter weighted efficiency is more precise and favorable as it mainly deems the inverter output power properties when exposed to disparate solar PV irradiance. The European metrical efficiency (𝜂𝐸𝑈𝑅𝑂), presently, is the bulk broadly admissible in inverter efficiency calculation. This is due to, historically, the European countries have been the biggest exporters and spent of solar PV inverters everywhere in the world. The European efficiency (𝜂𝐸𝑈𝑅𝑂) is a concluded metric relying on a standardized European irradiance profile. However, the rendition weightings embedded in this metric may not be fully representative or appropriate for photovoltaic inverters deployed in regions characterized by different climatic conditions, particularly in equatorial and subtropical environments. Accordingly, this study aims to validate the proposed assumption and develop a novel metrical efficiency equation for inverters operating in the Iraqi climate, specifically Baghdad city, relying on the IEC 61683:1999 criterion and the inverter load-duration curve. The proposed formula, validated with field data from an SMA-SB-4000-TL inverter, estimated the energy outcome of a 5.0 kW off-grid SPV system in Baghdad with a 2% deviation from measured values. These results validate the use of η_EURO tailored to Baghdad conditions as a reliable alternative to 𝜂𝐸𝑈𝑅𝑂 or 𝜂𝑀𝐴𝑋. This enhances the accuracy of system energy yield estimation, investment return calculations, and payback period assessment for solar PV systems.
Volume: 14
Issue: 3
Page: 761-768
Publish at: 2025-09-01

Artificial neural network based sensorless position estimation and direct torque control for stepper motor

10.11591/ijaas.v14.i3.pp702-710
Nagasridhar Arise , Thiruveedula Madhu Babu , Srinidhi Gollapudi , Tarun Kumar Dommeti , Abhishek Kummari , Mahith Shambukari
This study describes and illustrates how sensorless location estimation is achieved through the application of artificial neural network (ANN) control. Control stepper motor torque directly. Using stepper motors directly leads to a lot of problems; therefore, automated control systems are now commonly preferred. Stepper motors have several drawbacks when used directly, including the potential for steps to occasionally be missing while the motors are running. When physical sensors are not available, the proposed method estimates rotor position and speed using electrical signals and ANN algorithms. Simulation and experiment results demonstrate accurate position estimation (±1.5°) and efficient torque control. The sensorless direct torque control (DTC)-ANN approach increases the performance, reliability, and cost of stepper motors in robotics, computer numerical control (CNC) machines, and 3D printing.
Volume: 14
Issue: 3
Page: 702-710
Publish at: 2025-09-01

Implementation of fuzzy in DQ control of PV based inverter with plug-in electric vehicles

10.11591/ijape.v14.i3.pp666-675
Hanumesh Hanumesh , Arul Ponnusamy , Dhamodharan Selvaraj , Tanuja Koppa Shankaregowda , Venugopal Narasimhachar , Ananda Marilingappa Halasiddappa
In modern power systems, photovoltaic (PV) generation plays a vital role in sustainable energy supply. PV systems generate DC power, which is converted to AC using built-in converters for grid integration. The quality of power injected into the grid is crucial, especially in the presence of plug-in electric vehicles (PEVs) and non-linear loads, which introduce harmonics and dynamic disturbances. To enhance power quality, advanced control strategies are employed. This paper presents a comparative study of direct-quadrature (DQ) control techniques using traditional proportional-integral (PI) controllers and fuzzy logic controllers (FLCs) in a grid-connected PV system. The DQ control method simplifies the regulation of active and reactive power by transforming three-phase signals into a rotating reference frame. While PI controllers are widely used, they often struggle with non-linearities and load variations. FLCs, on the other hand, offer adaptive control without requiring precise mathematical models, making them more effective under dynamic conditions. The system under study includes PV generation, PEVs, and non linear loads. Performance metrics such as total harmonic distortion (THD), voltage stability, and power factor are analyzed. Results show that fuzzy controllers significantly improve power quality and system response.
Volume: 14
Issue: 3
Page: 666-675
Publish at: 2025-09-01

Intelligent control solutions for enhancing dual-fold Luo converter efficiency in EVs

10.11591/ijpeds.v16.i3.pp1789-1800
P. Siva Subramanian , B. Marisekar , P. Mohana Karthiga , R. Ramya
This research proposes the design and application of a smart controller for a dual-fold Luo converter tailored specifically for E-vehicle applications. The dual-fold Luo converter, known for its ability to efficiently step up and step down voltage levels with reduced components, is augmented with a smart control strategy to enhance its performance in the context of electric vehicles. The smart controller utilizes advanced techniques, such as artificial neural networks or fuzzy logic, to adaptively regulate the converter's operation, thereby improving efficiency, transient response, and overall reliability. By leveraging real-time data from the E-vehicle system, the controller dynamically adjusts key parameters to optimize performance under varying load and operating conditions. Key design considerations include the selection and training of the smart controller to achieve desired voltage regulation, efficiency, and robustness in the face of uncertainties inherent in E-vehicle operation. The proposed design methodology is validated through simulation studies, demonstrating superior performance compared to conventional control techniques. The results illustrate the efficacy of the smart controller in enhancing the dynamic response of the dual-fold Luo converter, making it a promising solution for E-vehicle power management systems. This research contributes to the advancement of power electronics in electric transportation, facilitating the development of more efficient and reliable E-vehicle systems in the pursuit of sustainable mobility.
Volume: 16
Issue: 3
Page: 1789-1800
Publish at: 2025-09-01

Parallel operation of transformers to optimize a 33 KV loop of power system

10.11591/ijape.v14.i3.pp579-587
Ethmane Isselem Arbih Mahmoud , Ahmed Abbou , Abdel Kader Mahmoud
This research investigates the viability of a perpetually scalable generation system to accommodate the anticipated growth in domestic load demands on the 33 kV loop network over the period from 2025 to 2040. This is achieved by analysis current situation of network through the voltages, loading lines, and transformers, within the permissible loading limits of the system. In this context, it is assumed that the loop is supplied by an ideal infinite power source. A numerical model utilizing the Gauss-Seidel (GS) method is developed and executed within the PSS/E simulator. The current operational state of the network will be simulated, with a focus on analyzing the voltage profile, which is expected to remain within the range of 0.095 to 1.05 per unit (p.u.). Demand forecasts are based on industrial growth projections for the cities interconnected with the 33 kV loop. The simulation results will demonstrate the feasibility of increasing active power transmission while maintaining effective control over reactive power by the year 2040. Furthermore, solutions will be proposed to address the identified critical path issues. To meet the projected demand, these solutions will involve doubling the capacity of the existing transformers. The proposed system will mitigate load imbalances and stabilize voltage fluctuations by effectively managing rapid variations in reactive power demand. As a result, it improves power quality for industrial consumers.
Volume: 14
Issue: 3
Page: 579-587
Publish at: 2025-09-01

Optimum control and design of a small hydro power plant for agriculture investment in Iraqi desert

10.11591/ijape.v14.i3.pp560-568
Jamal Ahmed Hameed , Thamir Hassan Atyia , Saba Fadhil Ahmed Jaf , Zubaidah Ghaze Abdulkareem , Ghanim Thiab Hasan
The aim of this paper is to conduct a mathematical and physical analysis to get a systematic treatment of design parameters and thus optimize water wheels. By today's standards, one finds empirical formulas instead, which take into account the practical experience of previous constructions, estimates of particular wheelbase shapes and sizes. So, based on the basic design and optimization standards for water wheels implementation, this paper attempts to design a water wheel power source in desert areas. Since the water wheels mainly use the gravitational force of water, there is only a slight hydrodynamic power losses. In addition to the high torque due to the large inertia of the water wheel. The obtained results indicate that the optimum operating range of the trailing water wheels is at a diameter of (2-7 m) and the Q water flow of about (0.1 m3/s). So, it can conclude that the implementing design has good efficiency and offer an economic benefit when use for the agriculture investment in desert areas.
Volume: 14
Issue: 3
Page: 560-568
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

Hybrid deep learning and active contour for segmenting hazy images

10.11591/ijra.v14i3.pp429-437
Firhan Azri Ahmad Khairul Anuar , Jenevy Jone , Raja Farhatul Aiesya Raja Azhar , Abdul Kadir Jumaat
Image segmentation seeks to distinguish the foreground from the background for further analysis. A recent study presented a new active contour model (ACM) for image segmentation, termed Gaussian regularization selective segmentation (GRSS). This interactive ACM is effective for segmenting certain objects in images. However, a weakness of the GRSS model becomes apparent when utilized on hazy images, as it is not intended for such conditions and produces inadequate outcomes. This paper introduces a new ACM for segmenting hazy images that hybridizes a pretrained deep learning model, namely DehazeNet, with the GRSS model. Specifically, the haze-free images are estimated using DehazeNet, which fuses the information with the GRSS model. The new formulation, designated as GRSS with DehazeNet (GDN), is addressed via the calculus of variations and executed in MATLAB software. The segmentation accuracy was evaluated by calculating Error, Jaccard, and Dice metrics, while efficiency was determined by measuring processing time. Despite the increased processing time, numerical experiments demonstrated that the GDN model achieved higher accuracy, as indicated by the lower error and higher Jaccard and Dice than the GRSS model. The GDN model can potentially be formulated in the vector-valued image domain in the future.
Volume: 14
Issue: 3
Page: 429-437
Publish at: 2025-09-01

Multi-robot coverage algorithm in complex terrain based on improved bio-inspired neural network

10.11591/ijra.v14i3.pp348-360
Fangfang Zhang , Mengdie Duan , Jianbin Xin , Jinzhu Peng
Biological neural network (BNN) algorithms have become popular in coverage search in recent years. However, its edge activity values are weak, and it is simple to fall into a local optimum at a late stage of coverage. When applied to complex environments, the 3D BNN network structure has high computational and storage complexity. In order to solve the above problems, we propose an algorithm for multi-robot cooperative coverage of complex terrain based on an improved BNN. The algorithm models the complex terrain using a 2.5-dimensional (2.5D) elevation map. Combining the dual-layer BNN network with the 2.5D elevation map, we propose an elevation value priority mechanism. This mechanism lets the robot make elevation-based decisions and prioritizes higher terrain areas. The dual neural network's first layer plans the robot's path in normal mode. The second network layer helps the robot escape the local optimum. Finally, the algorithm's full coverage effect in complex terrains and the speed of covering high terrain are verified by simulations. The experiments show that our algorithm preferentially covers high points of the region and eventually covers 100% of complex terrain. Compared with other algorithms, our algorithm covers more efficiently and takes fewer steps than others. The speed of covering high terrain areas has increased by 34.51%.
Volume: 14
Issue: 3
Page: 348-360
Publish at: 2025-09-01
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