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25,002 Article Results

Metaheuristic algorithms for parameter estimation of DC servo motors with quantized sensor measurements

10.11591/ijape.v14.i1.pp101-108
Debani Prasad Mishra , Sandip Ranjan Behera , Arul Kumar Dash , Prajna Jeet Ojha , Surender Reddy Salkuti
Manufacturing, aviation, and robotics have increased servo motor use due to their precision, reliability, and adaptability in various applications. This study compares three metaheuristic techniques for servo motor model parameter estimation with sensor measurement quantization, focusing on their accuracy and efficiency. Armature resistance, back electromotive force (EMF) constant, torque constant, coil inductance, friction coefficient, and rotor-load inertia are crucial to servo motor behavior prediction, significantly impacting overall system performance. Each approach was rigorously tested and analyzed to evaluate its effectiveness in predicting servo motor characteristics. The results revealed that particle swarm optimization and the firefly algorithm delivered comparable performance, particularly excelling in scenarios where sensor measurement quantization introduced noise or imprecision in the data. These methods demonstrated strong resilience and accuracy under such challenging conditions. In contrast, the genetic algorithm did not perform as well, falling short when compared to the other two techniques in handling noisy or imprecise data, indicating its relative inefficiency in such environments. These findings give servo motor designers and engineers across industries a powerful tool for performance prediction.
Volume: 14
Issue: 1
Page: 101-108
Publish at: 2025-03-01

Analysis and simulation of 7-level and 9-level cascaded H-bridge multi-level inverters

10.11591/ijape.v14.i1.pp11-22
Sujatha Banka , Chava Sunil Kumar , Surender Reddy Salkuti , Sai Sruthi Bhupathiraju , Kasoju Pragathi Balakishan , Paipoti Pooja Chaturya , Rishitha Namineni
Multi-level inverters (MLIs) have created a new revolution in high-power and medium-voltage applications in industry and research. In recent years, cascaded multi-level inverters have gained significant interest due to their ability to generate high-quality output waveforms with reduced total harmonic distortion (THD). This paper discusses the analysis and simulation of 7-level and 9-level cascaded H-bridge multi-level inverters using mathematical models and simulation tools. The proposed research puts emphasis on evaluating the performance and control strategies of these inverters. The control strategies, including pulse width modulation (PWM) techniques, are discussed in depth, with a focus on their effect on output waveform quality and reduction of THD. The simulation results are compared to showcase the advantages offered by the cascaded multi-level inverters in terms of waveform quality. The findings demonstrate the superior performance and power quality advantages offered by these multi-level inverters compared to traditional two-level inverters. Additionally, a passive LC filter is designed and implemented along with a multi-level inverter configuration that helps to keep the THD within the limits specified by IEEE standards.
Volume: 14
Issue: 1
Page: 11-22
Publish at: 2025-03-01

Enhancement LVRT capability of DFIG driven wind conversion system

10.11591/ijape.v14.i1.pp224-234
Abdeslam Jabal Laafou , Abdessalam Ait Madi , Youssef Moumani , Hassan Essakhi
In this paper we present two techniques for protecting the doubly fed induction generator (DFIG) in the event of external disturbances on the electrical network, the crowbar circuit and series dynamic braking resistor (SDBR) techniques. During voltage dips, the first technique is triggered and short-circuits the rotor side converter (RSC) so as to maintain the rotor current within the desired limits. As a result, the DFIG behaves as an asynchronous cage generator that absorbs the reactive power coming from the voltage dip on the network which does not meet the grid code's (GC) requirements. The second technique makes it possible to limit overcurrent’s at the level of the stator and rotor of the DFIG, it will enable the wind power system to continue operating normally once the fault has disappeared and to stay connected to the network throughout the voltage dip. This SDBR technique presents a good compromise between its performance, its simplicity, its efficiency, and its implementation’s cost.
Volume: 14
Issue: 1
Page: 224-234
Publish at: 2025-03-01

A novel fast MPPT strategy with high efficiency for fast changing irradiance in PV systems

10.11591/ijape.v14.i1.pp163-172
Pujari Anjappa , K. Jithendra Gowd
This paper discusses about the photovoltaic (PV) system novel non-iterative maximum power point tracking algorithm with faster converging speed under varying solar irradiation level. PV system is a scattered renewable energy resource and a safe environmental energy source. However, the PV power oscillates around MPP value due to the fluctuations of temperature and insolation effects, leading to nonlinear maximum power tracking issues. For each change in atmospheric condition, output of the PV system changes necessitating the need to search for new maximum power conditions. An efficient maximum power point tracking (MPPT) device that improves the power transmitting efficiency along with a suitable high frequency direct current (DC) to DC power converter device are required for efficient operation. Finally, a comparison is made between existing MPPT algorithms and proposed novel non-iterative MPPT algorithm. The proposed MPPT system show that the overall tracking speed of the proposed MPPT is 5.6 times, 3.8 times faster than perturb and observe (P&O) method and INC method respectively. During the variation of irradiance, the power loss is reduced by 18.84% and 11.29% in comparison with P&O and INC method. The proposed method also minimizes the steady state oscillations.
Volume: 14
Issue: 1
Page: 163-172
Publish at: 2025-03-01

Optimization and management of solar and wind production for standalone microgrid: a Moroccan case study

10.11591/ijape.v14.i1.pp202-211
Mohamed El Hafydy , Youssef Oubail , Mohamed Benydir , Lahoussine Elmahni , Elmoutawakil Alaoui My Rachid
The increasing demand for sustainable and efficient energy solutions has prompted extensive research into optimizing renewable energy sources in microgrid systems. This paper focuses on optimizing renewable energy sources within a standalone microgrid using particle swarm optimization (PSO) as the sole algorithm. The microgrid model proposed integrates photovoltaic (PV), wind, battery storage, and serves a load represented by an agricultural firm. Real-world data from Agdz in Ouarzazate, Morocco, is utilized for analysis. The primary objective is to minimize excess production from PV and wind sources when the battery reaches full charge. This research addresses the increasing demand for sustainable energy solutions by emphasizing a single optimization technique, PSO, for achieving a balanced and efficient energy generation system. The study aims to closely align energy production with load demand to reduce wastage and ensure a reliable energy supply within the microgrid. The evaluation is conducted based on the ability of the PSO algorithm to diminish the gap between total energy production and load demand. The use of the PSO algorithm resulted in a 30% reduction in excess energy, effectively mitigating unnecessary energy wastage when the battery is fully charged. This outcome highlights the algorithm's capacity to adapt and optimize energy production from primary sources to precisely align with the specific requirements of the load
Volume: 14
Issue: 1
Page: 202-211
Publish at: 2025-03-01

Optimized dense convolutional network with conditional autoregressive value-at-risk for chronic kidney disease detection through group-based search

10.11591/ijeecs.v37.i3.pp2009-2020
Chetan Nimba Aher , Archana Rajesh Date , Shridevi S. Vasekar , Priyanka Tupe-Waghmare , Amrapali Shivajirao Chavan
Chronic kidney disease (CKD) is the gradual decrease in renal functionality that leads to kidney failure or damage. This disease is the most severe worldwide health condition that kills numerous people every year as an outcome of hereditary factors and worse lifestyles. As CKD progresses, it becomes difficult to diagnose. Utilizing regular doctor consultation data for evaluating diverse phases of CKD can assist in earlier detection and timely inference. Furthermore, effectual detection methods are vital owing to an increased count of patients with CKD. Here, group search conditional autoregressive value-at-risk based dense convolutional network (GSCAViaR-DenseNet) is introduced for CKD detection. Firstly, chronic data is acquired from the dataset and Min-Max normalization is utilized to pre-process considered chronic kidney data. Thereafter, feature selection (FS) is performed based on Topsoe similarity. Lastly, CKD detection is executed by dense convolutional network (DenseNet) and group search conditional autoregressive value-at-risk (GSCAViaR) is employed to train DenseNet. However, GSCAViaR is designed by incorporating a group search optimizer (GSO) with a conditional autoregressive value-at-risk (CAViaR) model. Additionally, GSCAViaR-DenseNet acquired a maximal accuracy of about 91.5%, sensitivity of about 92.8% and specificity of about 90.7%.
Volume: 37
Issue: 3
Page: 2009-2020
Publish at: 2025-03-01

An internet of things-driven smart key system with real-time alerts: innovations in hotel security

10.11591/ijres.v14.i1.pp145-156
Putra Jaya , Ryan Fikri , Agariadne Dwinggo Samala , Dimas Sanjaya
This paper presents an innovative smart key system designed to enhance the safety and convenience of hotel guests. The system employs an iterative, agile approach encompassing the phases of requirement analysis, design, implementation, and testing. Key components of the input circuitry include limit switches, RFID-RC522 and SW420 vibration sensors, which collectively gather data. This data is processed using an Arduino Uno microcontroller and integrated with internet of things (IoT) technology. On the output side, the system incorporates a solenoid lock and is capable of promptly notifying users via Telegram in response to unauthorized access attempts. Importantly, the system can distinguish between vibrations caused by unauthorized entry and those from legitimate usage. Rigorous testing validates its efficacy, issuing Telegram alerts promptly when detecting security breaches. This technological advancement significantly enhances hotel room security, providing an intelligent real-time solution. The fusion of IoT, Arduino microcontroller, and precise sensor configuration underscores the system's reliability, setting new benchmarks for security in the hospitality sector. The comprehensive approach detailed in this paper offers valuable insights applicable to a wide range of security applications.
Volume: 14
Issue: 1
Page: 145-156
Publish at: 2025-03-01

Self-attention encoder-decoder with model adaptation for transliteration and translation tasks in regional language

10.11591/ijres.v14.i1.pp243-253
Shanthala Nagaraja , Kiran Y. Chandappa
The recent advancements in natural language processing (NLP) have highlighted the significance of integrating machine transliteration with translation for enhanced language services, particularly in the context of regional languages. This paper introduces a novel neural network architecture that leverages a self-attention mechanism to create an autoencoder without the need for iterative or convolutional processes. The selfattention mechanism operates on projection matrices, feature matrices, and target queries, utilizing the Softmax function for optimization. The introduction of the self-attention encoder-decoder with model adaptation (SAEDM) represents a breakthrough, marking a substantial enhancement in transliteration and translation accuracy over previous methodologies. This innovative approach employs both student and teacher models, with the student model's loss calculated through the probabilities and prediction labels via the negative log entropy function. The proposed architecture is distinctively designed at the character level, incorporating a word-to-word embedding framework, a beam search algorithm for sentence generation, and a binary classifier within the encoder-decoder structure to ensure the uniqueness of the content. The effectiveness of the proposed model is validated through comprehensive evaluations using transliteration and translation datasets in Kannada and Hindi languages, demonstrating its superior performance compared to existing models.
Volume: 14
Issue: 1
Page: 243-253
Publish at: 2025-03-01

Multi-objective hunter prey optimizer technique for distributed generation placement

10.11591/ijape.v14.i1.pp146-154
Kesavan Duraisamy , Sudhakiran Ponnuru , Jovin Deglus , Sakthidasan Arulprakasam , Rajakumar Palanisamy , Raja Soosaimarian Peter
Accommodation of distributed generation (DG) units in the distribution power network (DPN) reduces the power losses (PL), improves the voltage profile (VP), and enhances the stability. The size and site for distribution generations have to be optimized to avail favorable results. Otherwise, the DPN may experience greater power losses, higher voltage deviation, and voltage instability issues. This article implements an optimization technique using a hunter-prey optimizer (HPO) algorithm to optimize single and multiple (two) DG units in the radial DPN to minimize total real power losses (RPL) and total voltage deviation (TVD). The effectiveness of the HPO algorithm is assessed on the IEEE benchmark 69-bus radial DPN and a real-world Cairo-59 bus RDS. The simulation outcome after the optimized inclusion of DGs shown significant RPL reduction and considerable voltage enhancement. Furthermore, the optimized results of HPO algorithm were compared to the different algorithms and the comparison proved that the HPO can provide a more promising and authentic outcome than other algorithms.
Volume: 14
Issue: 1
Page: 146-154
Publish at: 2025-03-01

Optimal distributed generator placement for loss reduction using fuzzy and adaptive grey wolf algorithm

10.11591/ijape.v14.i1.pp155-162
Daruru Sarika , Palepu Suresh Babu , Pasala Gopi , Manubolu Damodar Reddy , Suresh Babu Potladurty
This research provides a new methodology for locating distributed generation (DG) units in distribution electrical networks utilizing the fuzzy and adaptive grey wolf optimization algorithm (AGWOA) to decrease power losses and enhance the voltage profile. Everyday living relies heavily on electrical energy. The promotion of generating electrical power from renewable energy sources such as wind, tidal wave, and solar energy has arisen due to the significant value placed on all prospective energy sources capable of producing it. There has been substantial research on integrating distributed generation into the electricity system due to the growing interest in renewable sources in recent years. The primary reason for adding distributed generation sources for the network is to supply a net quantity of power, lowering power losses. Determining the amount and location of local generation is crucial for reducing the line losses of power systems. Numerous studies have been conducted to determine the best location for distributed generation. In this study, DG unit placement is determined using a fuzzy technique. In contrast, photovoltaic (PV) and capacitor placement and size are determined simultaneously using an adaptive grey wolf technique based on the cunning behavior of wolves. The proposed method is developed using the MATLAB programming language; the results are then provided after testing on test systems with 33-bus and 15-bus.
Volume: 14
Issue: 1
Page: 155-162
Publish at: 2025-03-01

Performance analysis of conventional multilevel inverter driven PMSM drive in EV applications

10.11591/ijape.v14.i1.pp37-45
Rakesh G. Shriwastava , Pravin B. Pokle , Ajay M. Mendhe , Nitin Dhote , Rajendra M. Rewatkar , Rahul Mapari , Ranjit Dhunde , Hemant R. Bhagat Patil , Ramesh Pawase
This paper describes the simulation and hardware analysis of a two-level inverter-driven permanent magnet synchronous motor (PMSM) drive in EV applications. The design of various sections of PMSM Drive is discussed in detail. This proposed work is based on the voltage source converter (VSC) fed four-pole, 373 W. This paper highlights the design and implementation using a microcontroller of (PMSM) drive for various operating conditions. The experimental results show that the control and power circuit used in the design can achieve excellent and consistent speed performance. The performance along with test results of the speed and load variation of the PMSM drive is studied for steady-state conditions. The performance of the motor has been checked by increasing the inverter frequency with the speed of the motor and also keeping the frequency remains constant by varying the load and speed. Hardware analysis indicates the improved performance of the motor and the drive. It has good speed and torque responses and is suitable for EPS applications.
Volume: 14
Issue: 1
Page: 37-45
Publish at: 2025-03-01

Energy storage participation for frequency regulation of microgrid in PV-dominated power system

10.11591/ijape.v14.i1.pp109-117
Nirdesh Singh , Dinesh Kumar Jain
The frequency stability of a power grid is effectively managed through the inertia and power reserves supplied by synchronous generators. Due to increasing concerns about the greenhouse effect and global warming, renewable energy sources (or microgrids) are increasingly replacing traditional fossil fuel-based methods of electricity generation. As microgrid deployment proliferates, power systems' inherent complexity and non-linear dynamics have escalated, rendering conventional controllers inadequate across diverse operating conditions. Factors such as reduced energy inertia, heightened penetration of renewable energy sources, and significant power fluctuations within confined transmission systems have heightened the vulnerability of microgrid frequencies to instability. This paper elucidates the concept of microgrids, examines frequency fluctuations in the presence of solar and diesel generators alongside load variations, and presents simulation-based analyses. Moreover, it provides a succinct overview of frequency control methodologies. Validation outcomes demonstrate the efficacy of the proposed controller in maintaining system frequency amidst fluctuating load demands and renewable energy inputs.
Volume: 14
Issue: 1
Page: 109-117
Publish at: 2025-03-01

High order sliding mode control for grid integration of photovoltaic systems

10.11591/ijape.v14.i1.pp118-126
Noureddine Ech-cherki , Oumaima Echab , Youssef Errami , Abdellatif Obbadi , Smail Sahnoun , Mohssin Aoutoul
The article suggests employing second-order sliding mode control (SOSMC) to manage photovoltaic systems (PVS) connected to the electrical grid. These systems face complexities due to non-linearities, variability, uncertainties, disturbances, and climate changes. The proposed control strategy utilizes two converters: one at the photovoltaic generator (PVG) side for maximum power point tracking (MPPT) to optimize energy generation and another at the grid connection point to regulate power injection into the grid and maintain the DC bus voltage (Vdc) while achieving unit power factor (UPF). Both converters are equipped with SOSMC controllers, enabling independent adjustment of active (P) and reactive (Q) power. This approach aims to enhance the energy efficiency and robustness of PVS under varying climatic conditions. The performance of the system is evaluated under standard and variable irradiation conditions using the MATLAB/Simulink environment. Simulation results indicate that SOSMC significantly improves system performance and efficiency compared to conventional vector control (CVC). Notably, it reduces active power overshoot by 100%, decreases Vdc response time, and lowers total harmonic distortion (THD) of the current to 1.19%, demonstrating its effectiveness across different irradiation levels.
Volume: 14
Issue: 1
Page: 118-126
Publish at: 2025-03-01

Optimizing standalone dual PV systems with four-port converter technology

10.11591/ijape.v14.i1.pp81-89
Sharma Sha , Rajambal Kalayanasundaram
This paper analyses the four-port converter (FPC) based PV system. The discussed FPC is developed for hybrid energy sources (HES) with the merits of a single converting stage, fewer switches, and simple topology. By tapping two source ports from the midway of its two switching legs, the FPC presented in this work is developed from the basic full bridge converter (FBC). The pulses are produced using the phase angle control with pulse width modulation (PPAS) technique. Different modes of operation of the FPC are analyzed elaborately to give an insight into its topology. To efficiently manage power distribution among the ports and regulate their voltage, two key control variables have been utilized: duty ratio and phase angle. An in-depth presentation is provided on the design and modeling of a four-port converter. It provides autonomous management of power allocation among terminals and regulation of load voltage. Finally, simulated key waveforms of the FPC and simulation results to demonstrate the decoupled regulation of power sharing and load voltage of a PV system under varying input and output conditions are presented. The experimental prototype of the four-port converter results is discussed and presented in detail.
Volume: 14
Issue: 1
Page: 81-89
Publish at: 2025-03-01

Analysis of the soft switching modes for energy loss measurement of high frequency closed-loop boost converter

10.11591/ijape.v14.i1.pp64-73
Ajoya Kumar Pradhan , Sarita Samal , Prasanta Kumar Barik , Smrutiranjan Nayak
This manuscript explains the analysis of the soft switching technology to measure the energy loss of high-frequency closed loop boost converter with zero-current switching (ZCS) and zero-voltage switching (ZVS) techniques. To get these attributes, the use of soft power converters that utilize soft switching techniques is essential. This paper examines the ZCS/ZVS AC/DC converter design, used in high-power systems for renewable energy and battery charging. This converter architecture ensures semiconductor switches turn on and off at zero voltage and current. It smooths rectifier diodes, reducing switching and reverse recovery losses. It has better power quality, efficiency, and input power factor. Practical study has been done to verify the converter's theoretical analysis. Empirical research shows gentle switching enhances system efficiency. Energy losses are reduced by 26% while turning on and 20% when turning off compared to the ZVS and ZCS. The prototype converter is built to corroborate simulation results. Compared to ZVS and ZCS, switching losses are lower and efficiency decline is modest across the operating range. This shows that the simulation and experimental results are consistent.
Volume: 14
Issue: 1
Page: 64-73
Publish at: 2025-03-01
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