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30,185 Article Results

Voltage compensation using fuel cell fed dynamic voltage restorer

10.11591/ijpeds.v17.i1.pp663-673
Ryma Berbaoui , Rachid Dehini
One of the basic tasks of the dynamic voltage restorer (DVR) is to maintain voltage stability in distribution systems by correcting any deviations or disturbances in the three-phase supply. Whether they are increases or decreases. However, one of its disadvantages is its power source, as it cannot supply itself with power from the electrical grid like parallel compensators, which obtain power directly from the grid. This article presents an energy study of a dynamic voltage regulator (DVR) when operated using a power source represented by fuel cells, which are considered a clean and renewable source. On the other hand, excess energy from the regenerator or fuel cells can be output and injected into the distribution network for utilization via a parallel compensator (CP). The parallel compensator also compensates for reactive energy on the reactive load side to increase the power factor measured at the source side of the distribution system. This integrated system also uses neural networks to identify voltage disturbances and determine the voltages (modules/arguments) that must be added to the voltages in the power grid for correction. This analytical study was completed using a simulation system to confirm the effectiveness of this integrated system. The distinctive feature of this study is the integration of fuel cells and neural network-based control in the DVR system, providing a sustainable and intelligent alternative to conventional configurations, which makes it different from traditional DVRs that operate with batteries and supercapacitors. Its efficiency in compensating for voltage drops and surges is evident, and it also improves the power factor and ensures reliable operation of voltage-sensitive devices.
Volume: 17
Issue: 1
Page: 663-673
Publish at: 2026-03-01

Solar power forecasting using a SARIMA approach for Indonesia's grid integration

10.11591/ijpeds.v17.i1.pp293-302
Ricky Maulana , Syafii Syafii , Aulia Aulia
Indonesia’s transition toward a renewable energy-dominated power grid is progressing to meet increasing energy demands while reducing dependence on fossil fuels. According to the National Energy General Plan, their goal is to have 23% of the energy mix come from renewables by 2025 and 31% by 2050. Accurate forecasting of photovoltaic (PV) power output is crucial to address the intermittent nature of solar energy and ensure grid stability. A seasonal autoregressive integrated moving average (SARIMA) model was developed to estimate day-ahead photovoltaic power output in Padang City, Indonesia. Using NASA solar irradiance data from March 1-31, 2024, the SARIMA(1,0,1)(4,0,3)24 model achieved high accuracy with an NRMSE of 4.19%. To evaluate its performance, a comparative evaluation was conducted between the SARIMA model and two machine learning methods, namely artificial neural network (ANN) and long short-term memory (LSTM), in which SARIMA achieved the lowest forecasting error. These findings indicate that SARIMA remains an effective and interpretable statistical method for short-term PV forecasting, supporting reliable energy planning and power grid operations towards Indonesia's renewable energy goals.
Volume: 17
Issue: 1
Page: 293-302
Publish at: 2026-03-01

Study of neural controller based MPPT in comparison with P&O for PV systems

10.11591/ijpeds.v17.i1.pp797-808
Djaafar Toumi , Mourad Tiar , Abir Boucetta , Ikram Boucetta , Ahmed Ibrahim
This study investigated the performance of two prominent maximum power point tracking (MPPT) strategies: the established perturb and observe (P&O) technique and an artificial neural network (ANN)-based controller. Through simulations conducted in MATLAB/Simulink, a 50 W photovoltaic (PV) array was evaluated under dynamic irradiance and temperature variations. Notably, data generated by the P&O system served as the training dataset for the ANN model. The simulation results indicate that the ANN controller effectively and accurately identifies the PV system’s optimal operating point even amidst fluctuating environmental conditions. When compared to the conventional P&O method, the ANN approach demonstrated superior characteristics, including a significantly faster response, diminished oscillations around the maximum power point, and enhanced tracking accuracy during rapid environmental shifts. These findings underscore the substantial potential of ANN-based MPPT strategies for improving both the efficiency and operational stability of photovoltaic power systems.
Volume: 17
Issue: 1
Page: 797-808
Publish at: 2026-03-01

Leveraging distillation token and weaker teacher model to improve DeiT transfer learning capability

10.11591/ijict.v15i1.pp198-206
Christopher Gavra Reswara , Gede Putra Kusuma
Recently, distilling knowledge from convolutional neural networks (CNN) has positively impacted the data-efficient image transformer (DeiT) model. Due to the distillation token, this method is capable of boosting DeiT performance and helping DeiT to learn faster. Unfortunately, a distillation procedure with that token has not yet been implemented in the DeiT for transfer learning to the downstream dataset. This study proposes implementing a distillation procedure based on a distillation token for transfer learning. It boosts DeiT performance on downstream datasets. For example, our proposed method improves the DeiT B 16 model performance by 1.75% on the OxfordIIIT-Pets dataset. Furthermore, we present using a weaker model as a teacher of the DeiT. It could reduce the transfer learning process of the teacher model without reducing the DeiT performance too much. For example, DeiT B 16 model performance decreased by only 0.42% on Oxford 102 Flowers with EfficientNet V2S compared to RegNet Y 16GF. In contrast, in several cases, the DeiT B 16 model performance could improve with a weaker teacher model. For example, DeiT B 16 model performance improved by 1.06% on the OxfordIIIT-Pets dataset with EfficientNet V2S compared to RegNet Y 16GF as a teacher model.
Volume: 15
Issue: 1
Page: 198-206
Publish at: 2026-03-01

A new boost LED driver

10.11591/ijpeds.v17.i1.pp602-616
Dzhunusbekov Erlan , Orazbayev Sagi
Reducing the cost, increasing efficiency, and improving the reliability of LED drivers are critical due to the widespread adoption of LED lighting. This paper presents a research study on a novel boost LED driver designed to minimize voltage pulsations across power switches, thereby reducing dynamic losses in all power components. A small number of Schottky diodes were used to reduce conduction losses. To reduce switching losses in semiconductors, a quasi-resonant switching (QRS) at zero current was implemented for driving transistors. The operating principle is analyzed using computer modeling and validated experimentally in critical conduction mode (CrCM). In the initial evaluation, one version of the proposed driver achieved a high efficiency of up to 98.7% at 120 W input power. Additionally, the size and value of the main inductor were significantly reduced. The proposed driver provides an efficient and scalable solution for high-power LED lighting. Lower dynamic losses and reduced impulse voltages create opportunities for integrating the control circuit and power switches into a single chip.
Volume: 17
Issue: 1
Page: 602-616
Publish at: 2026-03-01

THD and spectral performance analysis of two-triangle RPWM for inverter applications

10.11591/ijpeds.v17.i1.pp370-382
G. Jegadeeswari , R. Sundar , S. P. Manikandan , E. Poovannan , C. Rajarajachozhan , M. Batumalay , Sukumar Kalpana
Pulse width modulation (PWM) is essential for voltage source inverters (VSI) to generate high-quality voltage outputs. Conventional deterministic PWM generates predictable harmonics, causing clusters that increase acoustic noise. Random PWM (RPWM) disperses harmonic power over a wider frequency range, reducing noise and electromagnetic interference. Many RPWM techniques improve inverter quality, but only partially suppress dominant harmonics and lack effective harmonic spreading. Most studies focus on simulations with limited FPGA implementation or hardware validation. The use of digital tools like VHDL, ModelSim, and MATLAB co-simulation remains underutilized. This paper proposes two-triangle RPWM strategies to enhance harmonic dispersion and reduce total harmonic distortion (THD). Co-simulation results are shown for both SPWM and RPWM, along with comparisons of fundamental voltages, THD, and HSF across different modulation indexes. Additionally, synthesis data for the Xilinx XC3S500E FPGA processor is supplied. The last section offers a comparative analysis and experimental validation of SPWM and RPWM. These techniques enable enhanced inverter performance, lower acoustic noise, and process innovations in power electronic systems.
Volume: 17
Issue: 1
Page: 370-382
Publish at: 2026-03-01

Hybrid renewable energy for cold chain in Indonesia: technical and economic evaluation

10.11591/ijpeds.v17.i1.pp674-682
I Made Aditya Nugraha , I Gusti Made Ngurah Desnanjaya , Anis Khairunnisa , Mahaldika Cesrany
Cold storage plays a crucial role in preserving temperature-sensitive products, particularly in the fisheries and food sectors. However, its operation is highly energy-intensive and often constrained by unstable electricity supply in many Indonesian regions. This study quantitatively evaluates a hybrid renewable energy system integrating photovoltaic (PV) panels, diesel generators, batteries, and the utility grid to ensure sustainable cold storage operations. Using measured load profiles, solar irradiation data, and annual operating costs, the system achieved a 60% reduction in diesel fuel consumption, 30-50% lower CO₂ emissions, and annual savings exceeding IDR 100 million compared to conventional generator-based systems. The system demonstrated 83.5% overall efficiency, with a payback period of 4.4 years and a positive net present value (NPV), confirming its economic viability. The novelty of this research lies in presenting the first comprehensive techno-economic analysis of a PV-diesel-battery-grid hybrid system specifically designed for fisheries-based cold storage facilities in Indonesia, considering local solar potential and grid reliability. Despite its feasibility, implementation challenges remain, including a lack of skilled technicians, limited financial incentives, and bureaucratic constraints. To overcome this, the study recommends PV subsidies, low-interest green loans, and public–private partnerships aligned with Indonesia's energy transition roadmap and cold chain development goals.
Volume: 17
Issue: 1
Page: 674-682
Publish at: 2026-03-01

Smart accommodation solution: innovative boarding house locator in Bayombong municipality

10.11591/ijict.v15i1.pp1-12
Carmelo Alejo D. Bisquera , Vilchor G. Perdido , Napoleon Anthony M. Mendoza
The search for affordable and conveniently located student accommodation is a common challenge, especially for students unfamiliar with their surroundings. This study presented the development and evaluation of a geographical information system (GIS)-enabled boarding house locator developed for Nueva Vizcaya State University (NVSU) students. The platform simplified the accommodation search process by providing a digital solution that integrates spatial data, real-time updates, and filtering options. The platform significantly reduced the time and cost of traditional housing searches. It helped students save 181.25 minutes per search and an average of 35 PHP in transportation costs compared to conventional methods like physical visits and word-of-mouth. Usability testing with 175 participants revealed high satisfaction, with the platform receiving an average rating of 4.83 for usability and 4.75 for performance. Key features such as interactive maps, location-based searches, and real-time updates enhanced the user experience by providing accurate, and up-to-date listings. The GIS-based platform outperformed traditional search methods in terms of efficiency and user satisfaction and offered a digital solution to common housing challenges faced by students. The results suggested the platform had strong potential for wider application at other universities. Overall, this system provides a scalable, cost-effective solution to improve student accommodation search and management.
Volume: 15
Issue: 1
Page: 1-12
Publish at: 2026-03-01

Integrating smart technologies for sustainable crop management in hydroponics

10.11591/ijict.v15i1.pp39-45
Jeyaprakash N. , Jayachandran M. , Poornavikash T.
Hydroponics has become a game-changing technique in agriculture's constantly changing terrain, upending traditional soil-based farming. The smart hydroponics management system, a cutting-edge method intended to maximize plant development and resource use, is presented in this study. The approach aims to push the limits of conventional farming, drawing inspiration from sustainable horticultural concepts as well as the principles described in Howard M. Resh's book on hydroponic production. This abstract integrates cuttingedge sensor technology and automation methodologies to capture the core of the smart hydroponics management system. It presents the system as a complete answer to the problems facing modern agriculture, rather than just a technique of cultivation. By drawing comparisons with seminal works in computer vision, the unique character of the system is highlighted, demonstrating a dedication to advanced and flexible agricultural techniques.
Volume: 15
Issue: 1
Page: 39-45
Publish at: 2026-03-01

Modeling and analysis of batteryless off-grid photovoltaic with adaptive multi-motor

10.11591/ijpeds.v17.i1.pp267-281
I Wayan Sutaya , Ida Ayu Dwi Giriantari , Wayan Gede Ariastina , I Nyoman Satya Kumara
This paper presents a model of a batteryless off-grid photovoltaic (PV) system with an adaptive multi-motor load. This model is developed as an effort to enhance the power output of batteryless off-grid PV systems for motor loads. Instead of using a single large-capacity motor, as commonly done in previous studies, the model distributes the load into several smaller motors and controls them adaptively. This approach allows for better control of the total load impedance to support maximum power point (MPP) tracking. A case study involving three three-phase induction motors, each with an operating power of 200 W, is conducted, where the power production of the proposed model is analysed by comparing it with the theoretical MPP and a fixed-load motor system that represents a single large motor. Under 1000 W/m² irradiance and using an 852 Wp PV array, the proposed model achieves a power output of 842 W, which corresponds to 98.83% of the MPP. In contrast, the system without this model only generates 298 W, or just 35.02% of the MPP. The testing process spans a 5-second period during the motor starting state. The power production analysis of the proposed model is presented in graphical form using MATLAB/Simulink.
Volume: 17
Issue: 1
Page: 267-281
Publish at: 2026-03-01

D-STATCOM control for distribution grids with distributed sources based on MMC structure using FCS-MPC algorithm

10.11591/ijpeds.v17.i1.pp425-437
Pham Viet Phuong , Le Hoai Nam , Pham Chi Hieu , Tran Hung Cuong
This paper proposes a D-STATCOM structure based on a modular multilevel converter (MMC) with the use of FCS-MPC control method for the purpose of compensating reactive power and stabilizing voltage in the distribution grid. The D-STATCOM is effectively used in cases involving non-sinusoidal and unstable voltages, which often occur in the distribution grid due to the effects of unbalanced nonlinear loads and power injection from renewable energy systems. The proposed structure also has the capability of reactive power compensating flexibility in fault conditions to stabilize the grid voltage. In this paper, a new control strategy, which is based on the combination of an outer PI controller and an inner FCS-MPC controller, was introduced. The outer PI controller is used to reduce static deviations in control values and to provide a reference value for the FCS-MPC controller. The inner FCS-MPC controller calculates the optimal switching state for the purpose of reducing the switching frequency of the MMC. The implementation process begins with the construction of a mathematical model and a control model. Simulations were carried out by MATLAB/Simulink to demonstrate the responsiveness of the control algorithm and the performance of D-STATCOM under the conditions of non-sinusoidal and unstable voltages.
Volume: 17
Issue: 1
Page: 425-437
Publish at: 2026-03-01

Analysis of different converter topologies for EV applications

10.11591/ijpeds.v17.i1.pp518-532
Bodapati Venkata Rajanna , Kondragunta Rama Krishnaiah , Sakimalla Prabhakar Girija , Shaik Hasane Ahammad , Mohammad Najumunnisa , Syed Inthiyaz , Gouthami Eragamreddy , Giriprasad Ambati , Nitalaksheswara Rao Kolukula
Electric vehicles (EVs) are gaining global prominence due to their high efficiency, low noise, and minimal carbon emissions. A critical aspect of EV performance lies in the interaction between energy storage systems (ESS) and power converters. Nonetheless, power delivery from storage units tends to be unreliable and needs strong converter units for effective and stable energy transmission. Several forms of direct current-to-direct current conversion systems used in electric vehicles are thoroughly examined in the paper, including both isolated and non-isolated designs such as those with the cuk, flyback, and push-pull architectures. The paper looks at converter categorization, control methods such as proportional-integral and artificial neural networks, as well as the method of modulation using unipolar and bipolar sinusoidal pulse-width modulation (PWM). Additionally, the role of optimization algorithms in improving converter performance is explored. Simulations were conducted using MATLAB/Simulink to evaluate each topology under varying load and input voltage conditions. The results demonstrate that the Push-Pull converter has the best efficiency for high-power applications, while the Cuk and Flyback converters are best for applications requiring continuous current and low-power, compact designs, respectively. This research offers insights for choosing optimal converter structures to improve energy efficiency and reliability of systems in electric vehicles.
Volume: 17
Issue: 1
Page: 518-532
Publish at: 2026-03-01

Enhanced adaptive reconfiguration for optimizing power generation and switching efficiency in PV arrays under PSC

10.11591/ijpeds.v17.i1.pp777-785
D. Manimegalai , Kandadai Nagaratnam Srinivas , Gayathri Monicka Subarnan
Photovoltaic (PV) arrays suffer significant power losses under partial shading conditions (PSC), which can degrade system performance. This paper proposes a novel weighted objective function that balances power output maximization with switching action minimization during dynamic PV array reconfiguration. An enhanced firebug swarm optimization (FSO) algorithm is employed to optimize this function efficiently. Simulation results under five shading patterns demonstrate approximately 6% improvement in power output over conventional methods, while also reducing the number of switch operations. The proposed approach enhances energy yield and extends device lifespan, offering a robust solution for real-time PV optimization under PSC.
Volume: 17
Issue: 1
Page: 777-785
Publish at: 2026-03-01

A novel hybrid PI and adaptive super-twisting sliding mode controller for high-performance integrated speed and flux regulation of IMDs

10.11591/ijpeds.v17.i1.pp414-424
Duc Thuan Le , Ngoc Thuy Pham
This paper presents a novel hybrid control strategy that integrates a proportional-integral (PI) regulator with an adaptive super-twisting sliding mode controller (ASTA) defined on a nonsingular terminal sliding mode control (NTSMC) surface for high-performance induction motor drives (IMDs). This enhanced hybrid PI-ASTA-NTSMC architecture jointly exploits the steady-state accuracy of PI control and the finite-time robustness of a higher-order sliding mode formulation. The adaptive mechanism of the super-twisting algorithm dynamically adjusts the switching gains according to the instantaneous sliding variable, ensuring consistent performance under time-varying loads and parameter variations. The NTSMC surface guarantees singularity-free finite-time convergence, while the adaptive ASTA law suppresses chattering and enhances disturbance rejection. Simulation results across multiple operating conditions show that the proposed controller significantly outperforms PI and PI-FOSMC schemes. It achieves the fastest transient, reducing settling time to 0.0407 s (39.4% and 31.5% faster than PI and PI-FOSMC), with overshoot lowered to 0.0091 rad/s and ISE/IAE minimized to 0.0035 and 0.0256, confirming its superior tracking precision. Additionally, reductions in the speed and torque RMSE indicate smoother control effort and improved closed-loop performance. The Lyapunov-based analysis confirms global finite-time stability of the overall system. With its enhanced robustness, low sensitivity to sampling noise, and continuous higher-order sliding structure that suppresses chattering, the proposed hybrid PI–ASTA–NTSMC offers a computationally efficient and practically attractive solution for integrated speed–flux control in industrial IM drives.
Volume: 17
Issue: 1
Page: 414-424
Publish at: 2026-03-01

Development of numerical model-based photovoltaic emulator for half-cut cell PV panel with multiple peaks output characteristics curve emulation capability

10.11591/ijpeds.v17.i1.pp343-358
Jordan S. Z. Lee , Jia Shun Koh , Rodney H. G. Tan , Nadia M. L. Tan , Thanikanti Sudhakar Babu
This study introduces a photovoltaic (PV) emulator focusing on a developed numerical model specifically for half-cut cell PV panels under partial shading conditions (PSCs), addressing a gap in research focused on full-cell models. The emulator uses a DC-DC buck converter and PI control to accurately replicate half-cut cell PV panel characteristics. A cost-effective hardware prototype validated the model's effectiveness in emulating multi-peak PV behavior under dynamic PSCs with up to three peaks and user-defined shading. This flexible and affordable platform enables efficient testing of MPPT algorithms and grid integration for PV systems using increasingly prevalent half-cut cell technology. Simulation results show high accuracy, with MAPE in power as low as 0.175% under uniform irradiance conditions and less than 0.302% under multi-peaks PSCs. Hardware validation confirms reliability with low MAPE in the power of 0.499% under uniform conditions and below 0.614% multi-peak PSCs, demonstrating the developed half-cut cell PV panel numerical model's accuracy in reproducing dynamic shading effects for renewable energy research.
Volume: 17
Issue: 1
Page: 343-358
Publish at: 2026-03-01
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