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29,939 Article Results

Optimal placement of DGs in a multi-feed radial distribution system using actor-critic learning algorithm

10.11591/ijape.v14.i2.pp319-327
Neelakanteshwar Rao Battu , Surender Reddy Salkuti
Multi-feed radial distribution systems are used to reduce the losses in the system using reconfiguration techniques. Reconfiguration can reduce the losses in the system only to a certain extent. Introduction of distributed generators has vastly improved the performance of distribution systems. Distributed generators can be used for reduction of loss, the improvement of the voltage profile, and reliability enhancement. Distribution generators play a vital role in reducing the losses in the distribution system. Placement of distributed generators in a multifeed system is a complex task to be solved using classical optimization methods. Classical optimization techniques may sometimes fail to provide a converged solution. Installation of distributed generators at suitable locations in a multi-feed system is found in this paper using the actor-critic learning algorithm. Actorcritic learning approach uses temporal difference error as a signal in making judgements regarding actions to be taken for future states in accordance with rewards that have been obtained by applying the present policy. The approach is applied to a standard 16-bus distribution system for reduction of system losses, and the results are discussed.
Volume: 14
Issue: 2
Page: 319-327
Publish at: 2025-06-01

Adaptation of parental expectation of children’s future scale in Indonesian version

10.11591/ijphs.v14i2.25209
Novia Solichah , Nur Ainy Fardana , Samian Samian
Parental expectations play a crucial role in shaping a child's developmental trajectory, serving as a primary motivator for the attainment of future aspirations. Researchers conducted a literature review on parental expectations toward their children, utilizing ten instruments developed in journal literature from 2008 to 2020. Of particular interest was the Parent Questionnaire containing the Chinese Parental Expectation on Child’s Future Scale (CPECF), it constitutes a fundamental framework for comprehending parental anticipations in the realm of child development. This study aimed to adapt and validate the PECF scale, employing established validation procedures endorsed by the International Test Commission. Initially, a cohort of 987 parents participated; however, after data cleansing procedures aimed at eliminating incomplete responses and ensuring accuracy, the analysis focused on 593 respondents. The participants’ ages ranged from 21 to 78 years, with a mean age of 35.93 years. Confirmatory Factor Analysis revealed 17 valid and reliable items. The model demonstrated a good fit. These findings suggest that the PECF scale effectively measures parental expectations, aligning with the original scale. It is anticipated that this scale will serve as a valuable tool for research concerning parental expectations in Indonesia, aiding in understanding and addressing the dynamics.
Volume: 14
Issue: 2
Page: 1040-1051
Publish at: 2025-06-01

Speed control of induction motor using fuzzy logic based on internet of things

10.11591/ijape.v14.i2.pp488-497
Charles Ronald Harahap , F. X. Arinto Setyawan , Desi Budiati
The aim of this research was to propose an innovative method of controlling the speed of an induction motor (IM) using fuzzy logic, integrated with internet of things (IoT). To achieve this aim, fuzzy logic was used to increase the performance of IM in order to obtain stable speed and high system response even in the presence of disturbances. Moreover, fuzzy logic relied on rules that used linguistic variables, and its main advantage was simple yet highly accurate, enabling the system to be efficient for determining parameters compared to the time-consuming and inefficient trial-and-error method. In this research, IoT implementation used Blynk platform to control and monitor IM speed remotely. Additionally, the components used in this research included an inverter, gate driver, Arduino Mega 2560, and NodeMCU ESP8266. Pulse width modulation (PWM) was required to obtain rotational speed of the motor through MOSFET switching process. The gate driver amplified PWM signal from Arduino Mega 2560, allowing MOSFET to operate. As a result, IM achieved a stable speed, and the system response followed the reference using fuzzy logic. In addition to this process, the system could be controlled and monitored remotely. Finally, the control system was successful, and the results were presented to show the viability of the proposed method.
Volume: 14
Issue: 2
Page: 488-497
Publish at: 2025-06-01

Powering the future of electrical load forecasting using a regression learner in machine learning

10.11591/ijape.v14.i2.pp264-274
Sushama D. Wankhade , Babasaheb R. Patil
The primary intent of the present research was to design and execute an electrical load forecasting system using machine learning (ML) techniques. The implementation of an advanced predictive method, specifically an ML algorithm, helped in accurate load forecasting, which is crucial for efficient power grid management, and optimizing resource allocation. Electricity load fluctuates due to various complex factors, making traditional forecasting methods struggle. This is where ML shines. ML algorithms can learn from historical data, identifying intricate patterns and relationships that influence electricity demand. This allows them to make more accurate predictions than static models. In this work, regression learning models in ML are used with the MATLAB platform. Three years of real-time data from the Wavi substation in India are used. Considering day, date, hour of day, max and min temperature of the day, and voltage and current are taken as input parameters to test fourteen different models of assorted regression algorithms. The performance of these models is evaluated using commonly used metrics, root mean square error (RMSE), mean squared error (MSE), and mean absolute error (MAE), along with a few other parameters. The optimized trained model is then tested with real data to obtain the forecasted load. The correlation between the Actual load and forecasted load is found to be 0.999962.
Volume: 14
Issue: 2
Page: 264-274
Publish at: 2025-06-01

Grid connected solar water pumping system

10.11591/ijape.v14.i2.pp412-420
Mula Sreenivasa Reddy , Banda Srinivas Raja , Movva Naga Venkata Kiranbabu , Muzammil Parvez , Syed Inthiyaz , Nelaturi Nanda Prakash , Bodapati Venkata Rajanna , Guntukala Surendher
A grid-connected solar water pumping system (SWPS) uses solar power to pump water while simultaneously drawing power from the grid when necessary. These systems can benefit farmers in a variety of ways, including reliable power, lower electric bills, increased income, and improved economic viability. This study explores a solar photovoltaic (SPV) water pumping system designed to function with a single-phase distribution network. It utilizes an induction motor drive (IMD) and incorporates an advanced power-sharing technique for optimal performance. In addition to transferring power from SPV to IMD, a DC-DC boost converter functions as a grid interface and power factor adjustment device. Maximizing the power extracted from the SPV array is critical for optimizing its utilization. To do this, a control mechanism based on incremental conductance is implemented to track maximum power points. Simultaneously, the IMD connected to the power source inverter is regulated using a simple volt/frequency approach. The suggested system, which includes standalone, grid-interfaced, and mixed-mode situations, is developed and validated in a lab.
Volume: 14
Issue: 2
Page: 412-420
Publish at: 2025-06-01

Optimization and dimensioning of stand-alone systems: enhancing MPPT efficiency through DLGA integration

10.11591/ijape.v14.i2.pp308-318
Moufida Saadi , Dib Djalel , Kadir Erkan
This paper explores optimizing and sizing stand-alone solar power systems using an intelligent maximum power point tracking (MPPT) method, enhanced by artificial neural networks (ANN). The study focuses on both system sizing and energy optimization, integrating genetic algorithms (GA) with deep learning (DL) to optimize the architecture of the ANN for improved performance in predicting solar energy output. The hybrid method, deep learning genetic algorithms (DLGA), efficiently reduces computational complexity and enhances flexibility through parameter tuning, significantly improving the performance of multi-layer perceptron networks. Additionally, a precise sizing methodology based on solar irradiance data was implemented to ensure the system is neither oversized nor undersized. The system's performance was tested and validated using MATLAB/Simulink simulations, which demonstrated superior predictive accuracy, faster convergence, and optimized energy capture. This combined approach of intelligent MPPT and accurate sizing presents a highly effective solution for improving the efficiency and reliability of stand-alone solar energy systems under varying environmental conditions.
Volume: 14
Issue: 2
Page: 308-318
Publish at: 2025-06-01

Methodology for incisive foraging of high-risk junctions and elimination of injected false data in smart grid

10.11591/ijape.v14.i2.pp347-358
Poulami Ghosh , Subrata Biswas , Prithwiraj Purkait
The present work represents a method for identification of the vulnerable nodes in smart grid as well as assessment of the performance of voltage stability indicator technique with the help of weighted least square scheme. in today’s smart grid system, false data injection (FDI) is the major issue to supply uninterruptedly at demand side in advanced metering infrastructure (AMI). The recent blackouts are the consequence of non-identifying FDI as research on FDI is not considered under power system analysis. In our research, vulnerable nodes of a power system network have been identified and a state estimation method was used to eliminate superfluous data for those identified nodes. Voltage stability indicator (VSI) based state estimation have been used successfully to make the smart grid system error free as possible. VSI method has been used first to find the vulnerable nodes of the grid after that the efficient state estimation method i.e. optimal weighted least square (optimal WLS) have been employed to get refined result. Results show that VSI based technique in concurrence with optimal WLS has potential to eliminate undesirable data with sensible level of precision.
Volume: 14
Issue: 2
Page: 347-358
Publish at: 2025-06-01

Solar and battery input super boost DC–DC converter for solar powered electric vehicle

10.11591/ijape.v14.i2.pp479-487
Aerpula Yadagiri , Srinivasa Rao Talagadadeevi , Seetamraju Venkata Bala Subrahmanyeswara Rao , Bitra Janardhana Rao , Syed Inthiyaz , Nelaturi Nanda Prakash , Bodapati Venkata Rajanna , Cheeli Ashok Kumar
The electric vehicle (EV) is increasingly emerging as an attractive solution to reduce reliance on fossil fuels in India. In commercial EVs, solar photovoltaic (PV) technology is employed both to charge the battery and power the vehicle. However, the conventional bidirectional DC-DC converter layout results in underutilization of solar PV power when the battery's state of charge (SOC) reaches maximum capacity. This work offers a unique dual input super boost (DISB) DC-DC converter designed specifically for solar-powered electric vehicles (EVs) to address the aforementioned challenge. The recently suggested converter operates in six different modes to effectively capture solar photovoltaic (PV) power. Notable benefits of this design include a wide range of speed control and fewer conduction devices in each mode, which eventually result in increased overall efficiency. An extensive analysis of the suggested DISB DC-DC converter is carried out by the study, encompassing detailed examination of operating waveforms and dynamic evaluations. Furthermore, the converter's performance and operation under the six different modes are verified through simulation.
Volume: 14
Issue: 2
Page: 479-487
Publish at: 2025-06-01

Speed control of BLDC motor using PID controller

10.11591/ijape.v14.i2.pp401-411
Tirunagari Bhargava Ramu , Sreevardhan Cheerla , Ravi Kumar Kallakuta , Kaja Krishna Mohan , Syed Inthiyaz , Nelaturi Nanda Prakash , Bodapati Venkata Rajanna , Cheeli Ashok Kumar
The current state of science, technology, and industrial revolutions did not occur overnight. Many years of empirical study attempts by human intelligence have led to the world's current status. As a result, new technologies and innovations would constantly propel human civilization forward. Another outstanding invention of the present day is the brushless DC (BLDC) motor. This paper outlines the design of a BLDC motor control system utilizing MATLAB/Simulink software. The main aim of this project is to control the speed and to obtain time domain specifications of PID controller. The application of speed control of motor is vast and also required to maintain the work efficient without any disturbance, the power consumption, and any other fuel to run. On the basis of this the brushless DC motor as application is selected because of reduction in losses and also the power. The PID control system is built to control the speed of the motor and gives the precise output. The universal bridge is used to amplify the current in the output of the application. PID controller reduces the error and increases the stability of the system.
Volume: 14
Issue: 2
Page: 401-411
Publish at: 2025-06-01

Integral backstepping control design for enhanced stability and dynamic performance of VSC-HVDC systems

10.11591/ijape.v14.i2.pp255-263
Chaimaa Lakhdairi , Aziza Benaboud , Hicham Bahri , Mohamed Talea
The increasing demand for efficient and reliable high-voltage direct current (HVDC) transmission systems has underscored the necessity for advanced control strategies to augment system performance. This article presents the design and implementation of an integral backstepping control approach customized for voltage source converter (VSC)-based HVDC systems. The proposed methodology primarily concentrates on tackling the inherent nonlinearities, uncertainties, and disturbances that typically impede the stability and efficiency of VSC-HVDC systems. By incorporating integral action into the backstepping control framework, two key objectives are accomplished: i) precise regulation of the direct voltage at the rectifier station and accurate control of the active power at the inverter station, and ii) effective power factor correction (PFC) at both stations within the HVDC system. These objectives contribute to robust tracking performance, enhanced dynamic stability, and improved overall system efficiency. The theoretical design has been verified through extensive numerical simulations conducted in the MATLAB/Simulink environment, showcasing the efficacy of the proposed control strategy in ensuring stability and performance under varying conditions.
Volume: 14
Issue: 2
Page: 255-263
Publish at: 2025-06-01

Relationship quality and its effects on college student’s psychological well-being

10.11591/ijphs.v14i2.24698
Afinnisa Rasyida , Maria Angelisa Siregar , Alifiah Nur'izza Rachmah , Raden Roro Fitria Rachmawati , Ivena Nathania Victor , Kezia Jeni Hindrawan
The field of psychological well-being is extensively studied globally, encompassing positive relationships as a notable facet. Presently, there is a discourse emphasizing the need for research on relationships to encompass both positive and negative aspects, along with their effects on an individual’s overall well-being. The study aimed to identify the impacts of relationship qualities of three sources (parental, friendship, and romantic relationships) on college students’ psychological well-being. The 251 college students in Surabaya (Indonesia) and 139 college students in Hangzhou (China), selected using purposive sampling technique, were involved in this research. All participants have at least three social networks/sources of relationship, i.e., parents, best friends, and romantic partners. The network of relationships inventory -relationship quality version (NRI-RQV) was given to identify the qualities of relationship participants have from the three sources. Participants’ psychological well-being was observed using the PERMA-Profiler. Data was analyzed using Statistical Package for the Social Sciences (SPSS). In both countries, students highlight that the quality of the relationship between parents and college students has the most substantial influence on their psychological well-being, with parental approval being one of the key components. This finding provides valuable insights for developing an effective support system for college students.
Volume: 14
Issue: 2
Page: 978-988
Publish at: 2025-06-01

Enhancing self-care adherence in tuberculosis patients through family support: a systematic review

10.11591/ijphs.v14i2.24749
Miftahul Falah , Tukimin Sansuwito , Regidor III Dioso , Faridah Mohd. Said , Lilis Lismayanti
Tuberculosis (TB) is a persistent and widespread chronic disease, posing a significant global health challenge and ranking as a leading cause of mortality worldwide. Indonesia, in particular, bears the fourth-highest TB burden globally, especially within the South-East Asia (SEA) region. Alarmingly, TB incidence rates increased by 13% from 2020 to 2021. This research utilized a systematic review methodology, sourcing data from four reputable English databases: PubMed, Google Scholar, OpenAlex, and Dimensions. Both quantitative and qualitative studies published in the last five years (2019-2023) were included. A comprehensive search strategy across the specified databases yielded a total of 1,201 articles. These articles underwent meticulous screening, resulting in six articles being deemed relevant for inclusion in the review. The inclusion criteria focused on studies examining the association between family support and self-care adherence among TB patients. The systematic review identified and analyzed these six pertinent articles, highlighting the pivotal role of family support in influencing TB patients’ adherence to self-care during treatment. Enhanced family support was found to correlate positively with improved adherence levels among TB sufferers. In summary, this literature review underscores the critical importance of family support in enhancing self-care adherence for individuals undergoing tuberculosis treatment. The positive correlation between robust family support and improved adherence levels emphasizes the influential role of the family unit in the overall well-being and treatment outcomes of TB patients.
Volume: 14
Issue: 2
Page: 661-671
Publish at: 2025-06-01

Prediction of wind power with various air speed using neuro-fuzzy logic in MATLAB

10.11591/ijape.v14.i2.pp432-440
Naimur Rahman Tushar , Md. Tanvir Ahmed Shuvo , Dilip Kumar Das , Suman Chowdhury
The energy crisis in Bangladesh has persisted for many years, predominantly reliant on fossil fuels for power generation, which is both economically and environmentally costly. It is imperative to transition away from fossil fuels towards more cost-effective and eco-friendly energy sources. Wind energy presents a viable solution to alleviate this crisis, especially considering Bangladesh's extensive coastline, offering great potential for harnessing significant amounts of electricity. Extensive research has been conducted on the feasibility of deploying wind turbines across various coastal zones to generate power and facilitate irrigation seasons. This research delves into the operational principles and performance parameters of wind turbines. A modified fan is utilized to assess power generation under varying air speeds, with data analysis conducted using neuro-fuzzy logic. The findings reveal a minimal percentage error of 0.09, underscoring the reliability of the proposed fuzzy model in predicting wind power output based on wind speed. This underscores the potential for leveraging wind energy as a sustainable and reliable alternative to fossil fuels in addressing Bangladesh's energy challenges.
Volume: 14
Issue: 2
Page: 432-440
Publish at: 2025-06-01

Comparison of MPP methods for photovoltaic system

10.11591/ijape.v14.i2.pp338-346
Debani Prasad Mishra , Rudranarayan Senapati , Prabin Biswal , Swayamjyoti Satapathy , Smruti Susmita Sahu , Surender Reddy Salkuti
Solar electricity is usually a ubiquitous photovoltaic (PV) power source that converts sunlight into electricity. This makes solar energy a key factor in meeting the growing global demand. However, solar energy production from photovoltaic cells can be limited by many factors, so the power source needs to be optimized to reach the maximum level. One of the crucial technologies to enhance the power production of photovoltaic structures is maximum power point tracking (MPPT) measurement. This technology increases energy production by providing many advantages such as security, freedom, maximum energy efficiency, and environmental protection. MPPT continuously monitors the maximum power point of the photovoltaic structure to ensure the system operates at peak efficiency. This technology is indispensable in today’s solar systems, enabling the use of solar energy and reducing dependence on fossil fuels. By optimizing solar energy production, MPPT technology plays a crucial role in supporting the future of energy. It helps reduce climate change and promotes environmentally friendly practices through the use of renewable energy. MPPT technology also increases solar reliability, reduces maintenance costs, and improves overall performance. This makes MPPT an essential part of the modern solar system, ensuring they are efficient and effective.
Volume: 14
Issue: 2
Page: 338-346
Publish at: 2025-06-01

Generator analysis and comparison of working fluids in the organic Rankine cycle for biomass power plants using Aspen Plus software

10.11591/ijape.v14.i2.pp467-478
Yulianta Siregar , Wahyu Franciscus Sihotang , Nur Nabila Mohamed
The organic Rankine cycle utilizes low-temperature heat (flue heat) in power plants to produce electrical power. Several factors, including the working fluid's temperature and pressure, influence the efficiency of an organic Rankine cycle. This research method includes calculations using the gasification method in calculating electrical energy in PLTBM and calculating the experimental results of a series of organic Rankine cycles by taking into account the temperature and pressure of the working fluid using Aspen Plus Software, which is analyzed using statistical methods. The results of research using the gasification method in PLTBM fuel produced power of 27,279.38 MW/year for coconut shells, 6,489.66 MW/year for rice husks, and 532.62 MW/year for corn cobs. For the organic Rankine cycle series, rice husk waste produces the largest power of 8,336.67 kW, for coconut shells of 569,723.95 kW. For corn cobs of 358,639.63 with an efficiency value of organic working fluid in R-22 of 25.37% and the R-32 organic working fluid of 11.92% at a temperature of 125 °C in coconut shell waste, it can be concluded that the temperature of the working fluid has more influence on the efficiency of the organic Rankine cycle than the pressure of the working fluid.
Volume: 14
Issue: 2
Page: 467-478
Publish at: 2025-06-01
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