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30,185 Article Results

Extension of Hermite-Hadamard type inequalities to Katugampola fractional integrals

10.11591/ijaas.v15.i1.pp1-18
Dipak Kr Das , Shashi Kant Mishra , Pankaj Kumar , Abdelouahed Hamdi
In this study, we introduce several new Hermite-Hadamard type general integral inequalities for exponentially (s,m)-convex functions via Katugampola fractional integral. The Katugampola fractional integral is a broader form of the Riemann–Liouville and Hadamard fractional integrals. We utilized the power mean integral inequality, the H¨older inequality and a few additional generalizations to derive these inequalities. Numerous limiting results are derived from the main results presented in the remarks. Furthermore, we provide an example illustrating our theoretical findings, supported by a graphical representation.
Volume: 15
Issue: 1
Page: 1-18
Publish at: 2026-03-01

Blade number and angle effect the archimedes spiral wind turbine performance

10.11591/ijape.v15.i1.pp393-402
Rosadila Febritasari , Muhammad Ibnul Abidin
The efficiency and performance of Archimedes spiral wind turbine (ASWT) are affected by the design and number of turbine blades which can convert the kinetic energy of the wind into mechanical energy to turn a generator that can produce electricity as much as possible in low wind speed. This study aims to obtain the optimal ASWT design in low wind speed in terms of aerodynamic performance. The method is conducted by numerically computational fluid dynamics (CFD) simulation on the fixed-opening angle and the blades number variations. The results show that the smallest C_D value is -2.18 at the 65° of opening angle, the largest C_L value at the 45° of opening angle is 0.37, and the largest C_M value is 0.61 at the 65° of opening angle and 4 blades. Therefore, it can be concluded that the Archimedes wind turbine with 4 blades and 65° pitch is the optimal.
Volume: 15
Issue: 1
Page: 393-402
Publish at: 2026-03-01

Impact of ferrite materials on wireless power transfer efficiency for electric vehicles battery chargers

10.11591/ijape.v15.i1.pp361-372
Wan Muhamad Hakimi Wan Bunyamin , Rahimi Baharom
This paper investigates the impact of ferrite materials on the efficiency of wireless power transfer (WPT) systems designed for electric vehicle (EV) and E-bike battery chargers. The study employs 3D full-wave electromagnetic simulations in CST Studio Suite 2024 to evaluate how Laird Performance Materials 33P2098-0M0 ferrite influences magnetic coupling, field confinement, and overall transfer efficiency. Two configurations were analyzed: coil-only and coil-with-ferrite plates, under a fixed 20 mm air gap and an operating range of 30–50 kHz. The inclusion of ferrite materials significantly improved magnetic-flux directivity and coupling strength, resulting in a peak efficiency of 99.21% at 41.3 kHz, compared to 99.09% at 38.1 kHz for the coil-only design. The enhanced configuration also reduced magnetic leakage and improved resonance stability, as verified through mesh-independent simulations and analytical validation with less than 2% error. The proposed model correlates ferrite permeability with mutual inductance and resonant-frequency tuning, confirming the theoretical basis of the efficiency gain. This work bridges a gap in small-scale EV and E-bike WPT research by quantifying the measurable benefits of ferrite integration and providing design guidelines for compact, thermally stable, and high-efficiency wireless charging systems.
Volume: 15
Issue: 1
Page: 361-372
Publish at: 2026-03-01

Hydrothermal synthesis and defect-driven optical characterization of CdS nanoparticles for semiconductor and solar applications

10.11591/ijape.v15.i1.pp440-448
Deepti Bhargava , R. K. N. R. Manepalli , M. C. Rao , P. Venkata Ramana Rao , N. S. Subba Rao , A. Narendra Babu , P. Sree Brahmanandam
Nanoparticles (NPs) play a crucial role in advancing technology, particularly by enhancing the performance of energy storage in semiconductor applications. The synthesis of NPs with reduced particle size and increased surface area, along with a higher number of active sites, facilitates improved ion diffusion, making them highly suitable for such applications. Various methods have been employed to reduce the size of NPs, depending on factors such as purity and controlled composition. The present study focuses on controlling both the size and composition of cadmium sulfide (CdS) NPs, aiming to achieve a high surface-to-volume ratio. These NPs were synthesized using a hydrothermal method in a high-pressure autoclave. The evaluation of the synthesized inorganic CdS-NPs for technological applications requires experimental validation of their characteristics, including particle size, energy band gap, thermal stability, temperature response, as well as optical and electronic properties. The results obtained using the proposed methods reveal a bandgap of 2.28 eV, a hexagonal wurtzite structure with an average crystallite size of 10.26 nm, reduced effective mass, and an intense absorption peak at a higher wavelength. These characteristics indicate that the synthesized CdS nanoparticles are suitable for various applications, including high-power semiconductors, solar energy harvesting, optoelectronic devices, and materials for energy and electrical engineering.
Volume: 15
Issue: 1
Page: 440-448
Publish at: 2026-03-01

Trapezoidal PWM scheme for voltage gain inverter

10.11591/ijape.v15.i1.pp90-97
Harikrishna Naraboyana , I. Kumaraswamy
The trapezoidal modulating wave-based high voltage gain 9-level inverter (HVG9LI) addresses significant difficulties related to the growing usage of capacitors, DC sources, and semiconductor switches. The proposed HVG9LI generates a nine-level resultant voltage with few components, exhibiting the capacity to double the output voltage gain. Furthermore, the HVG9LI utilizes a trapezoidal modulating wave and variable frequency carrier (TM-VFC) pulse width modulation method to increase the resulting voltage and enhance the voltage output quality. The performance and practicability of the HVG9LI with TM-VFC are evaluated across several modulation techniques and indices implemented by using MATLAB/SIMULINK and tested experimentally.
Volume: 15
Issue: 1
Page: 90-97
Publish at: 2026-03-01

Extending battery life and reducing charging costs in electric vehicles through converter selection for on-board chargers

10.11591/ijape.v15.i1.pp14-22
Jangam Kishore Babu , Ganney Poorna Chandra Rao , Puvvula Venkata Rama Krishna , Swathi Karike , Sailaja Kethireddy , Sareddy Venkata Rami Reddy , B. Nagi Reddy , Rekha Rangam
The electric vehicle (EV) sector is among the quickly expanding industries today. Global commitment to reducing pollution levels promotes interest in EVs. Fuel combustion engines emit around 10% of the globe's greenhouse gas emissions, which exacerbate the greenhouse effect. The emissions from electric vehicles are 17–27% less than those from internal combustion engines. The short battery life, high cost of charging, and lack of charging stations are some disadvantages of electric vehicles. The goal of this study is to suggest the ideal converter for the on-board charger (OBC), one that can extend battery life by lowering charging current at extremes of state of charge (SOC) and lower charging costs by increasing power factor (PF). The current control range than the isolated converter using transformers. Lastly, an analysis of the MATLAB/Simulink output findings is conducted to verify the effectiveness of the suggested OBC design with a non-isolated converter.
Volume: 15
Issue: 1
Page: 14-22
Publish at: 2026-03-01

High impedance fault discrimination in microgrid power system using stacking ensemble approach

10.11591/ijape.v15.i1.pp98-109
Arangarajan Vinayagam , Raman Mohandas , Meyyappan Chindamani , Bhadravathi Gavirangapa Sujatha , Soumya Mishra , Arivoli Sundaramurthy
High impedance (HI) faults in microgrid (MG) power systems are non-linear, intermittent, and have low fault current magnitudes, making them challenging to detect by typical protective systems. Consequently, it is imperative to implement a sophisticated protection system that is dependent on the precision of fault detection. In this study, a stacking ensemble classifier (SEC) is proposed to discriminate HI fault from other transients within a photovoltaic (PV) generated MG power system. The MG model is simulated with the introduction of faults and transients. The features of data set from event signals are generated using the discrete wavelet transform (DWT) technique. The dataset is used to train the individual classifiers (Naïve Bayes (NB), decision tree J48 (DTJ), and K-nearest neighbors (KNN)) at initial and meta learner in the final stage of SEC. The SEC outperforms other classification methods with respect to accuracy of classification, rate of success in detecting HI fault, and performance measures. The outcomes of the classification study conducted under standard test conditions (STC) of solar PV and the noisy environment of event signals clearly demonstrate that the SEC is more dependable and performs better than the individual base classification approaches.
Volume: 15
Issue: 1
Page: 98-109
Publish at: 2026-03-01

Constrained multi-objective optimization of high frequency transformer design for dual active bridge converter in solid state transformers using genetic algorithms

10.11591/ijape.v15.i1.pp328-351
Jayrajsinh B. Solanki , Kalpesh J. Chudasama
This study presents a novel multi-constraint and multi-objective optimization based approach that applies genetic algorithms (GAs) for developing high-frequency transformer (HFT) designs for dual active bridge converters (DABs) in solid-state transformers (SSTs). SSTs are increasingly adopted in modern power systems due to their higher efficiency, compact structure, and improved operational reliability when compared with conventional transformers. Developing HFTs for SSTs involves several challenges, particularly the need to balance competing objectives such as improving efficiency, limiting losses, and reducing the area product while satisfying multiple design constraints. To address these challenges, this work applies a constrained multi-objective GA implemented in MATLAB to optimize the design of an HFT for a DAB converter. The methodology allows for the simultaneous optimization of multiple design objectives while taking into consideration restrictions like efficiency, leakage inductance, temperature limits, core winding area, and sizes. Our comparison with particle swarm optimization (PSO) indicates that the GA achieves more consistent convergence and consistently lower total losses. The case studies reinforce this observation, giving compact and high-performance HFT designs tailored for SST applications. The optimization approach provides a reliable and scalable method for developing thermally robust and space-efficient HFTs suitable for next-generation SST platforms and renewable-energy applications.
Volume: 15
Issue: 1
Page: 328-351
Publish at: 2026-03-01

Elk herd optimizer for cost-efficient hybrid energy systems under renewable uncertainty

10.11591/ijape.v15.i1.pp430-439
Ly Huu Pham , Hung Duc Nguyen , Chi Trung Truong , Quoc Trung Nguyen
This paper suggests a new method, called elk herd optimizer (EHO), for effectively addressing the optimal generation cooperation problem involving thermal, hydro, solar, and wind power plants (WPPs), in which the uncertainty of wind speed and solar radiation from renewable power plants is considered. The primary goal of this study is to minimize the costs from thermal, wind, and solar power plants (SPPs) while adhering to all operational constraints associated with these power plants and the overall power system. Two systems were tested to evaluate the performance of EHO method alongside two other techniques: the coot optimization algorithm (COOT) and the tunicate swarm algorithm (TSA). Both systems were optimally scheduled over a 24-hour period; however, the second system accounted for uncertainties in generation and cost from solar and WPPs. From the result analysis, EHO method was able to achieve a lower cost compared to COOT, TSA, and other previously employed methods for optimizing generation across all plants. Therefore, EHO is recommended as an effective optimization tool for addressing the uncertainties associated with solar radiation and wind speed.
Volume: 15
Issue: 1
Page: 430-439
Publish at: 2026-03-01

Current state of production of аlternative energy on the Absheron Peninsula

10.11591/ijape.v15.i1.pp37-45
Ramil Sadigov Ali , Nazila Alverdiyeva Farman , Gunay Mammadova Israphil , Vusala Isaqova Gudrat , Turkan Hasanova Allahverdi , Muhammad Madnee
The article is devoted to the study of the relationship between sustainable development and the introduction of innovative technologies, and the formation of smart cities. The Azerbaijan Republic is a land-poor country and has exhausted most of its natural resources. Therefore, the use of renewable energy sources and scientific research in this direction are important and topical issues for the country's scientists. Wind demand: in 10 months (from January to October) showed 3.000 GWh-4.000 GWh in Absheron (2020-2024 years). Since bioenergy can be produced in any weather, it is more reliable than solar and wind energy in Azerbaijan's regions. Seasonal variations in the availability of agricultural residues can lead to uneven energy production and create difficulties in ensuring a constant supply. The study is innovative given the importance of non-competition with food production, as well as the unique environmental, economic, and technological implications of each biofuel production method.
Volume: 15
Issue: 1
Page: 37-45
Publish at: 2026-03-01

Artificial neural network-optimized bridgeless Landsman converter for enhanced power factor correction in electric vehicle applications

10.11591/ijape.v15.i1.pp238-247
Podila Purna Chandra Rao , Radhakrishnan Anandhakumar , T. Vijay Muni , L. Shanmukha Rao
Electric vehicles (EVs) are gaining popularity globally due to their energy-efficient battery storage systems, low carbon emissions, and eco-friendly operation. By transforming both the transportation and electrical sectors, EVs could create a synergistic relationship that reduces fossil fuel use and improves renewable energy integration. However, this convergence emphasizes the necessity for appropriate power factor correction (PFC) methods, especially in EV battery charging systems, to alleviate supply-end PQ concerns. Use of a bridgeless Landsman converter (BLC), noted for its efficiency and link voltage monitoring, is innovative in this research. A proportional-integral (PI) controller tuned by an artificial neural network (ANN) improves prediction and classification, especially response time. The ANN-based PI controller optimises system performance in real time using adaptive control. Using a hysteresis controller attached to a pulse width modulation (PWM) generator regulates the converter's steady-state switching frequency for accurate and consistent output. The proposed approach reduces harmonic distortions and improves operating efficiency. This comprehensive architecture improves power factor and addresses significant PQ concerns in EV charging infrastructure. Integrating improved control tactics and converter design shows that this approach may support electric car technology developments. MATLAB simulations show that power factor correction (PFC) charges EV batteries quickly and effectively. Findings suggest the technique could increase power quality, system efficiency, and EV uptake.
Volume: 15
Issue: 1
Page: 238-247
Publish at: 2026-03-01

Optimization of load frequency control systems using PSO technique

10.11591/ijape.v15.i1.pp177-185
Debani Prasad Mishra , Rudranarayan Senapati , Lingam Yashwanth , Peesodi Uday , Surender Reddy Salkuti
This paper investigates the improvement of low-frequency load control (LFC) by optimizing integral part (PID) control using particle swarm optimization (PSO). Load frequency control is important to ensure energy stability by maintaining the balance between production and consumption. Conventional proportional integral derivative controllers are widely used for this purpose; however, their performance can be further improved through optimization. This work uses particle swarm optimization, a nature-inspired algorithm, to set the parameters of the proportional integral derivative controller. PSO was chosen because it can search for good solution space and find a good agreement between control parameters, thus improving the dynamic and stable response of the system. This article provides a comprehensive evaluation of the proposed approach, including simulation results and comparisons with standard PID controllers. The effectiveness of the optimized PID controllers in reducing the frequency difference and improving the overall efficiency of the power plant under different conditions is demonstrated. This study provides insight into the use of artificial intelligence to improve control parameters in the power grid, providing a promising way to improve the efficiency and reliability of frequency controllers.
Volume: 15
Issue: 1
Page: 177-185
Publish at: 2026-03-01

Simulation of three phase grid interconnections with HVDC link with three level MMC converter

10.11591/ijape.v15.i1.pp289-297
Madhubabu Thiruveedula , Nenavath Ramesh Babu , Penagonda Akash , Guthula Sravya Bhavana , Devasoth Arjun , Gavvala Chethan
This paper presents the simulation and analysis of a three-phase grid interconnection system using a high voltage direct current (HVDC) link with a three-level modular multilevel converter (MMC). The HVDC link enhances modern power transmission by reducing losses, increasing transfer capacity, and improving grid stability. The three-level MMC, known for its modular design, scalability, and low harmonic distortion, is employed for efficient grid integration. The system, modeled in MATLAB/Simulink, includes a three-phase alternating current (AC) grid, HVDC link, and MMC operating in both rectification and inversion modes to enable bidirectional power transfer. Proportional-integral (PI) controllers synchronize the MMC with the grid, ensuring stable operation under varying conditions such as load changes and disturbances. Simulation results indicate high efficiency, low harmonic distortion, reduced switching losses, and decreased voltage stress on components. The HVDC link also improves reliability by damping power oscillations and providing reactive power support. Overall, the integration of HVDC and MMC offers a robust, efficient, and sustainable solution for future high-performance grid interconnections, serving as a strong basis for further advancements in HVDC transmission systems.
Volume: 15
Issue: 1
Page: 289-297
Publish at: 2026-03-01

Optimal design of three-phase solar PV integrated unified power quality conditioner (UPQC)

10.11591/ijape.v15.i1.pp1-13
Yogesh S. Pawar , Mahesh Kadu , Pawan C. Tapre , Dinesh S. Wankhede , Rajendra M. Rewatkar , Swapna M. Choudhary , Rakesh G. Shriwastava
This research investigates the utilization of a unified power quality conditioner (UPQC) to address power quality issues in the electrical grid and mitigate harmonics introduced by non-linear loads. The UPQC system is augmented by a combination of photovoltaic (PV) and battery energy storage system (BESS). Typically, the PV system supplies active power to the load. However, in cases where the PV system cannot provide sufficient power, the BESS is activated to ensure a continuous power supply, particularly during prolonged voltage interruptions. To enhance system reliability and reduce dependency on environmental conditions, a hybrid PV-BESS system is proposed. The inclusion of the BESS improves long-term voltage support capabilities, simplifies the DC-link voltage regulation algorithm, and facilitates the production of clean energy. For efficient phase synchronization operation of the UPQC controller under unbalanced and distorted grid voltage conditions, a self-tuning filter (STF) integrated with the unit vector generator (UVG) technique is employed.
Volume: 15
Issue: 1
Page: 1-13
Publish at: 2026-03-01

Robust hall sensor signal conditioning for BLDC motor control using RC filters and optocoupler isolation

10.11591/ijape.v15.i1.pp373-382
Hasni Anwar , Intidam Abdessamad , El Fadil Hassan , Lassioui Abdellah , El Ancary Marouane , El Asri Yassine
Brushless DC (BLDC) motors require accurate rotor position feedback to guarantee reliable electronic commutation. However, hall-effect sensor signals are often degraded by high-frequency switching noise from the inverter, which can cause false commutations and control errors. Moreover, a direct connection to control hardware may introduce ground loops and jeopardize sensitive electronics. This study proposes a hardware-based hall signal conditioning method that integrates RC low-pass filters, designed with a 1.59 kHz cutoff frequency, to attenuate inverter-induced noise, and 4N35 optocouplers to provide galvanic isolation. Unlike existing approaches that rely primarily on algorithmic noise rejection or digital filtering, the proposed solution offers a compact, low-latency hardware implementation suitable for real-time embedded control. Experimental validation using a dSPACE DS1104 board shows a 14.7 dB improvement in signal-to-noise ratio (SNR) and a 36% reduction in timing jitter, ensuring clean and isolated hall signals for stable six-step commutation. These improvements directly translate into smoother torque production, enhanced speed stability, and increased protection of control electronics, making the method applicable to both research and industrial BLDC motor systems operating in noisy environments.
Volume: 15
Issue: 1
Page: 373-382
Publish at: 2026-03-01
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