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30,938 Article Results

Fuzzy logic direct torque control of induction motors using three-level NPC inverter

10.11591/ijpeds.v17.i1.pp180-194
Jamila Chennane , Lahcen Ouboubker , Mohamed Akhsassi
Induction motor drives are extensively used for their robustness and efficiency, but precise control remains difficult under dynamic conditions. Conventional direct torque control offers a simple structure and fast response, but is limited by torque ripple, flux distortion, and poor low-speed performance. This paper proposes a fuzzy logic-based direct torque control (FDTC) combined with a three-level neutral point clamped (NPC) inverter. A fuzzy inference system (FIS) replaces the hysteresis comparators and switching table, while speed regulation is improved using a PI-fuzzy controller. MATLAB/Simulink simulations under speed variations and load disturbances demonstrate reduced torque and flux ripples, smoother flux trajectories, improved current waveforms, and faster transient response compared with classical DTC. These results confirm that the FDTC–NPC approach provides a robust and efficient solution for advanced applications such as industrial automation, renewable energy, and electric vehicles.
Volume: 17
Issue: 1
Page: 180-194
Publish at: 2026-03-01

Improving photovoltaic efficiency: a systematic study of P&O and INC MPPT techniques

10.11591/ijpeds.v17.i1.pp728-739
Abdelkbir Jamaa , Ahmed Moutabir , Rachid Marrakh , Abderrahmane Ouchatti
Achieving high efficiency in photovoltaic (PV) systems under fluctuating irradiance and temperature conditions relies on effective maximum power point tracking (MPPT) techniques. Among the most commonly adopted approaches, perturb and observe (P&O) and incremental conductance (INC) are favored for their ease of implementation and operational flexibility. Nevertheless, a systematic comparison of their performance under dynamic conditions remains limited. This study conducts a comparative evaluation of P&O and INC algorithms using MATLAB/Simulink, with emphasis on tracking accuracy, convergence speed, and overall efficiency. A standard PV module is exposed to rapid variations in irradiance and temperature to examine algorithm robustness. The results indicate that although P&O achieves fast convergence in steady-state operation, it exhibits noticeable oscillations around the maximum power point, resulting in efficiency losses of up to 3%. Conversely, the INC method offers improved tracking precision and reduced oscillations, yielding efficiency gains of 2-4% over P&O in dynamic environments. These findings underline the trade-off between algorithmic simplicity and tracking accuracy, and provide practical guidance for selecting MPPT strategies in both grid-connected and standalone PV applications. 
Volume: 17
Issue: 1
Page: 728-739
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

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

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

Ferrite-based magnetic shielding for efficiency enhancement in resonant inductive wireless power transfer systems

10.11591/ijpeds.v17.i1.pp572-581
Wan Muhamad Hakimi Wan Bunyamin , Rahimi Baharom
This paper presents a detailed simulation-based investigation of ferrite-based magnetic shielding to enhance the efficiency and electromagnetic performance of resonant inductive wireless power transfer (RIPT) systems, with a particular emphasis on electric vehicle (EV) wireless charging applications. Two system configurations, a baseline coil-only system and a ferrite-shielded system, were modelled and simulated using CST Studio Suite 3D electromagnetic simulation software under identical geometric and electrical conditions to ensure a fair comparative evaluation. Key performance metrics, including power transfer efficiency (PTE), H-field distribution, and magnetic flux confinement, were analyzed to quantify the shielding impact. The ferrite-shielded configuration achieved a PTE improvement from 98.29% to 99.01%, demonstrating stronger flux concentration, reduced leakage, and lower electromagnetic interference (EMI) exposure. Additional analyses highlight the trade-offs in ferrite integration, including potential core loss, material cost, and thermal drift, while also discussing the system’s robustness against coil misalignment and its alignment with SAE J2954 and IEC 61980 standards for EV charging. The study is limited to a simulation-based approach without experimental validation; however, the findings establish a solid foundation for future hardware prototyping and hybrid shielding exploration, integrating ferrite and composite or metamaterial-based structures. Overall, this work contributes to the development of efficient, EMI-compliant, and thermally stable WPT systems suitable for next-generation EV charging infrastructures.
Volume: 17
Issue: 1
Page: 572-581
Publish at: 2026-03-01

Mitigating harmonic distortion in grid-connected PV systems: a comparative evaluation of ANFIS and IC-based MPPT techniques

10.11591/ijpeds.v17.i1.pp303-316
Bouledroua Adel , Mesbah Tarek , Kelaiaia Samia
Integrating photovoltaic (PV) systems into power grids presents notable challenges related to power quality, especially concerning total harmonic distortion (THD) caused by power electronic converters, which do not comply with IEEE 519 and IEC 61000 standards. This study introduces an adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) controller designed to optimize energy extraction while concurrently mitigating harmonic distortion in three-phase grid-connected PV systems. Unlike conventional IC-MPPT methods, which compromise the quality of the power to monitor performance, the proposed ANFIS-MPPT strategy uses intelligent modulation index adjustment to achieve a dual goal. A comparison of the four irradiation levels (450-1000 W/m²) shows a higher performance: ANFIS-MPPT achieves 0.26% THD at 1000 W/m² compared to 0.44% at IC-MPPT (40.9% improvement), and 0.80% versus 1.12% at 450 W/m² (28.6% reduction). The five-layer ANFIS architecture, trained on temperature and radiation data, shows faster convergence and lower oscillation than the conventional approach. The results confirm that MPPT based on ANFIS is an effective solution to improve the energy quality of grid-integrated photovoltaic installations while maintaining optimal energy conversion efficiency.
Volume: 17
Issue: 1
Page: 303-316
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

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

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

A novel high-gain DC-DC converter with fuzzy logic control for hydrogen fuel cell vehicle applications

10.11591/ijpeds.v17.i1.pp617-628
Gaddala Anusha , A. V. V. Sudhakar , Shaik Rafikiran , Ram Ragotham Deshmukh , C. H. Hussaian Basha
Hydrogen fuel cell vehicles (HFCVs) are emerging as a sustainable alternative to conventional internal combustion engines due to their zero-emission characteristics and high energy efficiency. However, the low output voltage of fuel cells poses a significant challenge in meeting the high-voltage requirements of electric traction systems. To address this, this paper proposes a high-gain non-isolated switched-capacitor (SC) DC-DC converter integrated with a fuzzy logic controller (FLC) for efficient power management in hydrogen fuel cell vehicle applications. The proposed converter topology achieves a significant voltage step-up without the use of bulky magnetic components, making it lightweight and compact for automotive integration. A maximum power point tracking (MPPT) controller using fuzzy logic is used to recover optimum energy out of the fuel cell stack during different loads and conditions of the environment. MATLAB/Simulink simulation results validate the high voltage gain, stable operation, and improved dynamic response of the proposed converter under FLC control. The proposed intelligent control strategy enhances fuel cell utilization and ensures effective operation of HFCV powertrains.
Volume: 17
Issue: 1
Page: 617-628
Publish at: 2026-03-01

High efficient DC-AC inverter for low wireless power transfer applications

10.11591/ijpeds.v17.i1.pp453-464
Kyrillos K. Selim , Hanem Saied Ebrahem Torad , Mostafa R. A. Eltokhy , Hesham F. A. Hamed , Mohamed Elzalik
The inverter's simplicity is an important aspect that must be considered especially for electronic devices, as adding the number of power switches increases the complexity and overall cost of the inverter. This work proposes an inverter design that converts DC into AC power. It receives 12 VDC as an input voltage, and it is composed of a boost converter that converts an input voltage of 5-20 VDC to an output voltage of 4-30 VDC and a pulse width modulation controller to produce a square wave with a frequency of 100 kHz to drive the switching MOSFET. The designed inverter can be operated on different loads ranging from 50 Ω to 1000 Ω, tested in both simulations and experimentally. The design was optimized by the LT Spice simulator. The proposed inverter has operating frequencies ranging from 40 kHz to 110 kHz, taking into account different loads. The obtained results showed that both simulation and experimental results converged, whereas the highest efficiency was 96.96% at 55 kHz at a fixed load of 100 Ω. On the other hand, the maximum achieved efficiency when the load was sweeping was 80% at a load of 50 Ω at a fixed frequency of 100 kHz.
Volume: 17
Issue: 1
Page: 453-464
Publish at: 2026-03-01

Enhancing the dynamic stability of electric power systems through the coordinated tuning of generator predictive controllers

10.11591/ijpeds.v17.i1.pp211-222
Hristo Beloev , Yuri Bulatov , Andrey Kryukov , Konstantin Suslov , Yuliya Valeeva , Magdalena Dudek , Iliya Iliev
The paper presents a method for the coordinated tuning of automatic voltage regulation (AVR) and automatic speed control (ASC) systems for a group of generators operating in parallel at a power plant. The method also involves solving the optimization problem using a genetic algorithm. The possibilities of using lead-lag elements in AVR and ASC, which impart predictive properties and improve damping characteristics of the controllers, are also considered. A model of a power plant operating in parallel with an electric power system is presented. This model demonstrates effective damping of oscillations under large disturbances when the proposed method is used to adjust the AVR and ASC control coefficients, along with a self-tuning lead-lag element. In this case, voltage oscillations and frequency overshoot disappear, and there is a significant reduction in the maximum deviations of these parameters. In the illustrative case study, the coordinated tuning of the controllers provides a 6% increase in the transmitted power limit and, as a consequence, the enhancement of the stability margin of the electric power system.
Volume: 17
Issue: 1
Page: 211-222
Publish at: 2026-03-01

A comparative analysis of PoS tagging tools for Hindi and Marathi

10.11591/ijict.v15i1.pp120-137
Pratik Narayanrao Kalamkar , Prasadu Peddi , Yogesh Kumar Sharma
Many tools exist for performing parts of speech (PoS) data tagging in Hindi and Marathi. Still, no standard benchmark or performance evaluation data exists for these tools to help researchers choose the best according to their needs. This paper presents a performance comparison of different PoS taggers and widely available trained models for these two languages. We used different granularity data sets to compare the performance and precision of these tools with the Stanford PoS tagger. Since the tag sets used by these PoS taggers differ, we propose a mapping between different PoS tagsets to address this inherent challenge in tagger comparison. We tested our proposed PoS tag mappings on newly created Hindi and Marathi movie scripts and subtitle datasets since movie scripts are different in how they are formatted and structured. We shall be surveying and comparing five parts of speech taggers viz. IMLT Hindi rules-based PoS tagger, LTRC IIIT Hindi PoS tagger, CDAC Hindi PoS tagger, LTRC Marathi PoS tagger, CDAC Marathi PoS tagger. It would also help us evaluate how the Bureau of Indian Standards’s (BIS) tag set of Indian languages compares to the Universal Dependency (UD) PoS tag set, as no studies have been conducted before to evaluate this aspect.
Volume: 15
Issue: 1
Page: 120-137
Publish at: 2026-03-01

Modeling and optimization of angular misalignment effects in resonant inductive wireless power transfer for electric vehicle charging

10.11591/ijpeds.v17.i1.pp394-404
Samshul Munir Muhamad , Wan Muhamad Hakimi Wan Bunyamin , Rahimi Baharom
This paper presents an enhanced electromagnetic modeling and optimization study on the effects of angular misalignment in resonant inductive wireless power transfer (RIWPT) systems for electric vehicle (EV) charging. A detailed 3D model of a double-layer circular coil was developed in CST Studio Suite to investigate coupling degradation, energy loss, and efficiency behavior under angular deviations ranging from 0° to 25°, at a fixed air gap of 30 mm. Performance metrics including mutual inductance, magnetic field distribution, power transfer efficiency (PTE), and loss characteristics were analyzed to establish quantitative misalignment correlations. Results indicate a steady reduction in PTE from 99.979% at 0° to 88.441% at 25°, accompanied by corresponding increases in field asymmetry and energy dissipation. To mitigate these losses, an impedance-tuning strategy was applied by jointly optimizing transmitter-side series and parallel compensation capacitors, which improved PTE at 5° misalignment from 98.777% to 99.801%, restoring near-resonant operation. Additional analyses evaluated thermal impact, material robustness, and dynamic misalignment effects, providing a more holistic understanding of real-world charging scenarios. The study further discusses real-time tuning feasibility using embedded controllers and aligns performance with SAE J2954 and IEC standards for EV wireless charging. The findings establish validated design guidelines and adaptive tuning frameworks for achieving high-efficiency, misalignment-tolerant RIWPT systems, contributing toward robust and energy-efficient EV charging infrastructure.
Volume: 17
Issue: 1
Page: 394-404
Publish at: 2026-03-01
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