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ANFIS and PI based performance analysis of three phase three wire distribution system for THD reduction

10.11591/ijape.v14.i3.pp752-760
Khammampati R. Sreejyothi , J. Jayakumar , P. Venkatesh Kumar
Due to the rising usage of nonlinear loads and power electronic devices in businesses, one of the key power system concerns today is inadequacy of power quality (PQ). This article presents compensation of current harmonics in distribution system in source side by using adaptive neuro fuzzy inferences system (ANFIS) controller. DSTATCOM optimized proportional integral (PI) controller and ANFIS regulator are utilized for DC link voltage regulation. The ANFIS controller showed better performance compared to PI controller during compensating harmonics time. This paper compared two control schemes results PI and ANFIS. Three-phase three-wire inverter is used for DSTATCOM circuit. In the results compared DC capacitor voltage and total harmonic distortion (THD) values of source current. The THD with PI controller is 7.92% while by using ANFIS controller it is reduced to 2.76%. The concert of proposed method is analyzed with MATLAB/Simulink software.
Volume: 14
Issue: 3
Page: 752-760
Publish at: 2025-09-01

Implementing fuzzy control for a DC-DC boost converter using FPGA

10.11591/ijape.v14.i3.pp656-665
V. Radhika , Karuppannan Srinivasan , R. Kiruba
This research explores the use of field programmable gate arrays (FPGA) to mitigate static voltage errors and reduce voltage spikes in DC-DC boost converters. Given the dynamic nature of the load impedance in these converters, FPGA is well-suited for designing systems with adaptive behavior. The study implements a fuzzy control algorithm on FPGA in a simulation environment with a small sampling period. The parallel processing capability of FPGA enables the simultaneous execution of fuzzy control algorithms, enhancing the system's responsiveness to rapid changes in load conditions. This approach minimizes voltage overshoot and effectively suppresses voltage spikes. By leveraging FPGA’s high-speed parallelism and flexibility, the research demonstrates significant improvements in the dynamic performance of the DC-DC boost converter. The results highlight FPGA’s potential as a robust platform for controlling power electronic systems, ensuring improved stability and efficiency under varying load conditions.
Volume: 14
Issue: 3
Page: 656-665
Publish at: 2025-09-01

AI-driven solutions for Li-ion battery performance and prediction

10.11591/ijape.v14.i3.pp569-578
Sthitprajna Mishra , Chinmoy Kumar Panigrahi , Subhra Debdas , Atri Bandyopadhyay , Srikanth Velpula , Amit Kumar Sahoo , Pabitra Kumar Tripathy
Batteries serve as crucial power sources for essential portable devices like electric vehicles, smartphones, and laptops. The widespread adoption of Li-ion batteries, while beneficial, has unfortunately led to a surge in adverse incidents. The sudden failure of batteries in both industrial and lightweight applications poses significant economic risks across various industries. Consequently, researchers are intensifying their focus on enhancing battery state estimation, management systems, and predicting remaining useful life (RUL). This paper is structured into three main sections. Firstly, it delves into the acquisition of battery data, encompassing both commercially available and freely accessible Li-ion battery datasets. Secondly, the exploration extends to techniques for estimating battery states through advanced battery management systems. The paper investigates battery RUL estimation, categorizing and evaluating diverse prognostic methods applied to Li-ion batteries based on crucial performance parameters. The review includes scrutiny of commercially and publicly available datasets for various battery models and conditions, considering different battery states and the role of advanced battery management system (BMS). In the final section, the paper concludes with a comparative analysis of Li-ion battery RUL prediction, incorporating exploration into various RUL prediction algorithms, and mathematical models, and introducing an AI-based cloud monitoring system.
Volume: 14
Issue: 3
Page: 569-578
Publish at: 2025-09-01

Gated dilated causal convolution-based encoder-decoder network for IoT intrusion detection

10.11591/ijape.v14.i3.pp722-732
Aarthi Gopalakrishnan , Sharon Priya Surendran , Aisha Banu Wahab
The internet of things (IoT) is perhaps the greatest modern development, as it affects our daily lives and is rapidly expanding in its application zones. The IoT is used in everyday activities, so security is more crucial because intrusion detection will introduce and eliminate attacks. In this paper, a novel deep learning based intrusion detection technique (DEBIT) has been proposed that detects the intrusion using deep learning techniques efficiently. Initially, the data from IoT user is preprocessed and classified using the novel gated dilated casual convolution based encoder-decoder (GDCC-ED) method, which classifies the data into attack and non-attack. The proposed DEBIT framework has been assessed using a MATLAB simulator. The performance of the proposed DEBIT framework has been assessed based on specific parameters, including recall, detection rate, accuracy, F1 score, and precision. Based on experimental results, the suggested method is 99.5% more accurate than pigeon-inspired optimization (PIO), Res-TranBiLSTM, and blockchain-based African buffalo (BbAB), which are 85.4%, 92.5%, and 85%, respectively.
Volume: 14
Issue: 3
Page: 722-732
Publish at: 2025-09-01

Enhanced multi-mode control of Z-source virtual synchronous generator for photovoltaic systems using fuzzy logic controller

10.11591/ijape.v14.i3.pp701-711
Vempalle Rafi , Pradyumna Kumar Dhal , Shaik Hussain Vali , Sadhu Radha Krishna , Uppuluri Suryavalli , S. Vinoth John Prakash
An enhanced multi-mode control solution for a Z-source virtual synchronous generator (ZVSG) that makes use of a fuzzy logic controller (FLC) is proposed by this study for use in photovoltaic (PV) systems. As a potential grid integration option for PV systems, the ZVSG has great potential due to its steady and adjustable power production. A stable voltage and frequency output can be maintained by the ZVSG when it is running in a variety of modes, such as grid-connected, standalone, and islanding, according to the control approach that has been provided. The FLC is used for the purpose of controlling the switching frequency of the ZVSG as well as the DC-link voltage. The performance of the ZVSG is improved by the FLC-based control approach that has been proposed. This technique reduces the steady state error and offers a rapid dynamic response. The results of the simulation show that the recommendation for a control approach improves the performance of the ZVSG across a wide variety of operating modes and load conditions.
Volume: 14
Issue: 3
Page: 701-711
Publish at: 2025-09-01

Optimizing retail systems: using big data and power business intelligence for performance insights

10.11591/ijaas.v14.i3.pp945-954
Huu Dang Quoc , Ha Le Viet
In the rapid development of information technology, using enterprise data to support timely management decisions is crucial in helping businesses operate effectively and improve competitiveness. This study uses Microsoft power business intelligence (MPBI) to analyze data in retail systems, allowing managers to grasp the business situation in real time, track advanced sales, optimize inventory control, and analyze customer behavior and supply chain visibility. From the data generated by the business, the study uses the streaming extract transform load (ETL) model to support real-time data aggregation, then converts to the MPBI data visualization system to convert data into visual charts, helping businesses easily monitor, track, analyze, and make decisions to promote business activities. The study proposes a data structure to organize retail information storage. It proposes a system of calculation formulas and data synthesis, making integrate and convert tabular data into visual charts. Through analysis of real data from the LH83 retail system, the study shows the feasibility of implementing a data visualization system and the difficulties encountered when businesses want to deploy this model.
Volume: 14
Issue: 3
Page: 945-954
Publish at: 2025-09-01

Minimizing the switching losses in the SiC MOSFET by using buried oxide

10.11591/ijape.v14.i3.pp613-619
Ali Hlal Mutlaq , Sura Hamad Faraj , Majeed Rashid Zaidan , Ghanim Thiab Hasan , Ahmed Saad Names
For optimizing the efficiency of the power switching devices, it is important to reduce the switching power losses. One method to minimize the switching power losses is to reduce the gate drain charge (QGD). In this paper, a 1.2 kV SiC MOSFET device with a buried oxide has been proposed to minimize QGD. The proposed design has been conducted by using the TCAD simulation program. The on-resistance (Ron,sp), QGD have been measured and analyzed based on the width and thickness of the buried oxide layer and compared with the measurement of traditional SiC MOSFET. The obtained results indicate that the QGD of 1.2 kV SiC MOSFET with buried oxide with WBO of 0.25 μm and TBO of 0.3 μm was reduced to about 31.3% which mean a minimize of power losses. The comparison results indicate that the proposed device with a buried oxide layer can be effectively used as an optimum solution for minimizing the power switching losses.
Volume: 14
Issue: 3
Page: 613-619
Publish at: 2025-09-01

Battery cycle life and throughput optimization in wireless communication system with energy harvesting capability

10.11591/ijape.v14.i3.pp600-612
Omar Enassiri , Youssef Rochdi , Ouadoudi Zytoune
This research paper proposes a novel approach to address the energy challenges faced by internet of things (IoT) devices. The wireless communication system involves a transmitter equipped with energy harvesting module that charges both a rechargeable battery and a capacitor through an energy storage management system (ESMS). This ESMS is based on a reinforcement learning algorithm to dynamically switch between the battery and the capacitor, ensuring efficient power utilization. This reinforcement learning algorithm enables the device to learn and adapt its energy consumption patterns based on environmental conditions and usage, optimizing energy usage over time. Additionally, the system employs a rainflow counting method to estimate the state-of-health (SoH) of the battery, ensuring its longevity and overall system performance. By combining these approaches, the proposed system aims to significantly improve the energy efficiency and lifespan of IoT devices, as well as the amount of data sent for different temperature ranges, ultimately enhancing their cost-effectiveness and performance.
Volume: 14
Issue: 3
Page: 600-612
Publish at: 2025-09-01

Evaluation of sensorless VF-MRAS and FOC-MRAS of IM electrical drive system

10.11591/ijape.v14.i3.pp513-521
Moustapha Diop , Abdoulaye Kebe , Ibrahima Gueye
This paper evaluates the performance of sensorless vector and scalar control methods, namely field-oriented control-based model reference adaptive system (FOC-MRAS) and voltage frequency-based model reference adaptive system (VF-MRAS), applied to an induction motor (IM) driven by a space vector modulation inverter. In motorized systems, conventional control methods use mechanical sensors, which can be cumbersome and costly. To overcome these limitations, sensorless control techniques based on speed estimation have been introduced. In this paper, MRAS-based sensorless speed control for IM drives using rotor flux is used. This adaptive system uses a reference model based on rotor flux and implements closed-loop control. The estimated speed derived from the current and voltage models is compared to the desired speed and adjusted by the proportional-integral (PI) controllers. The performances of the approaches are evaluated in terms of speed regulation and minimization of electromagnetic torque and rotor flux ripples, through a comparative analysis of sensor and sensorless controls under various operating conditions, including variable loads and speed reversal. The simulation results obtained, using consistent criteria for both methods, confirm the effectiveness of sensorless control.
Volume: 14
Issue: 3
Page: 513-521
Publish at: 2025-09-01

The application potential of net zero energy building using rooftop photovoltaics case study of apartments in Gorontalo Province

10.11591/ijape.v14.i3.pp743-751
Abdi Gunawan Djafar , Niniek Pratiwi , Yasin Mohamad , Zhiqiang John Zhai
Gorontalo Province is one of the developing regions in Indonesia. The province has been actively building apartments since 2009. The construction increases population density and energy use intensity. Consequently, demand for electricity power rises. Renewable energy such as rooftop photovoltaics has the potential as a power source for the apartments, considering the abundant solar radiation in Gorontalo which is located near the equator line. Three apartments representing three levels of the inhabitant’s income are selected as study case for the application of photovoltaic (PV) on roof to achive net zero energy building. Simulation of PV energy to power the buildings is conducted using photovoltaic geographical information system (PVGIS). By utilizing monthly electrical bill data, it is found that PV on roof is sufficient to cover the building energy demand and achieve net zero energy building (NZEB). However, there is uncertainty of the fluctuation of energy demand due to the tenant’s energy consumption behaviour. The consumption intensity is limited only by the installed power on each apartment unit. PV on roof alone is unable to provide the need if it is employed to power the unit to the maximum extent.
Volume: 14
Issue: 3
Page: 743-751
Publish at: 2025-09-01

Comparative analysis of MPPT techniques for photovoltaic systems: classical, fuzzy logic, and sliding mode approaches

10.11591/ijape.v14.i3.pp688-700
Mohamed El hafydy , Mohamed Benydir , Elmahni Lahoussine , Elmoutawakil Alaoui My Rachid , Youssef Oubail
This study presents a comprehensive comparative analysis of maximum power point tracking (MPPT) strategies for photovoltaic systems, focusing on the classical perturb and observe (P&O) method, an artificial intelligence based fuzzy logic controller (FLC), and a robust sliding mode control (SMC) technique. These methods aim to maximize power output by dynamically adapting to rapid and unpredictable environmental variations, such as changes in solar irradiance. Simulations performed the MATLAB/Simulink environment under diverse real-world scenarios demonstrate that SMC and FLC outperform the conventional P&O approach, particularly under conditions of sudden and severe environmental in fluctuations. The findings highlight the advanced controllers’ ability to sustain optimal power extraction, minimize energy losses, and maintain system stability across varying operating conditions. These results underscore the potential of SMC-based MPPT systems to enhance the efficiency and resilience of renewable energy applications, making them highly viable for deployment in real-world scenarios characterized by volatile environmental conditions.
Volume: 14
Issue: 3
Page: 688-700
Publish at: 2025-09-01

Model predictive control based frequency regulation of microgrid with integration of distributed energy resources

10.11591/ijape.v14.i3.pp551-559
Sarbjeet Kaur , Surbhi Gupta
Power generation sector has become more prevalent in the use of renewable energy sources resulting in more complex and non-linear network. Microgrids are becoming the best alternative solution in remote areas where the distribution network is infeasible. However, the intermittent nature of distributed renewable energy resources can result in a generation and demand mismatch instigating frequency variation which is a crucial concern. Thus, modern power system requires increasing intelligence and flexibility to cope up with the generation-load mismatch. Efficient control techniques are of vital importance in maintaining the frequency near the nominal value, and the selection of the controller is crucial in maintaining the reliable, effective, and steady functioning of the power system. The present study demonstrates frequency control in islanded microgrid with disruptions in load demand using the model predictive control by efficiently managing the energy storage with integration of large-scale renewable energy sources. The effectiveness and superiority of the proposed model predictive controller (MPC) is presented by comparing its performance with proportional integral controller and proportional integral tuned with adaptive neuro fuzzy inference system (ANFIS) through simulations in MATLAB environment.
Volume: 14
Issue: 3
Page: 551-559
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

Single photovoltaic panel constant regulated voltage based on modified DC-DC buck-boost converter topology

10.11591/ijape.v14.i3.pp620-630
Ro’ad Baladi Al Komar , Arwindra Rizqiawan
This research proposes a single photovoltaic panel constant regulated voltage based on novel topology. A modified DC-DC buck-boost converter was chosen because characteristics of voltage boost and low input current ripple. A comprehensive analysis of the proposed converter cells was elaborated in this study. Furthermore, a control technique is designed for the proposed converter. A double-loop control method using proportional integral (PI) is employed in this research. The outer loop controls the output voltage, while the inner loop is used to control the inductor current. By employing double-loop control, the presence of ripple current and voltage can be reduced even further. Simulation and experimental results validate the converter’s effectiveness, demonstrating stable voltage output under varying input voltage (33-36 V) and load conditions, maintaining a 40 V output with an overshoot within ±5%. The results show that the modified buck-boost converter can achieve improved efficiency and ripple reduction compared to conventional models, making it a viable solution for renewable energy systems.
Volume: 14
Issue: 3
Page: 620-630
Publish at: 2025-09-01

Performance comparison of core loss in induction motor using non-oriented electrical steels

10.11591/ijape.v14.i3.pp640-646
Chittimilla Shravan Kumar Reddy , Ezhilarasi Arivukkannu , Kartigeyan Jayaraman
Induction motor (IM) enjoy certain advantages that include simple design, robust construction, reliable operation, low initial cost, easy operation and simple maintenance besides offering reasonable efficiency. Modelling and definition of procedures leading to good estimation of core losses in induction motors from material test data is still a challenge, is considered as problem statement. The major objective of this paper is to estimate the core loss in an induction motor (IM) by analyzing a selection of non-grain oriented electrical steel materials and then identifying for each represented whether it can be used both as stator and rotor core material. As core loss is influenced by factors such as air gap, B-H theory, eddy currents and excess loss coefficients and Steinmetzuhl factor, this study is intended to improve the electromagnetic performance of the motor. Influencing core loss are the amounts of flux density and elasticity of material. This study was accomplished by using three sorts of non oriented electrical steel: DI MAX-M15, DI MAX-M19, and DI MAX-M36. A 5 HP induction motor was the subject for finite element method (FEM) simulations whose results have been verified by empirical relations, which show the merit of using non oriented electrical steel as core material.
Volume: 14
Issue: 3
Page: 640-646
Publish at: 2025-09-01
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