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30,547 Article Results

Parameters optimization of solar PV cell using war strategy

10.11591/ijpeds.v17.i2.pp1418-1425
Radouan Gouaamar , Seddik Bri
Enhancing photovoltaic models' performance and dependability requires optimal parameter extraction. This paper presents a practical method for determining these values from experimental current-voltage data: the war strategy optimization algorithm. RTC France, PWP201, and STP6-120/36 are the three PV models to which the war strategy optimization algorithm was successfully applied. According to the findings, the RMSE values for RTC France were 0.0000077298; PWP201 was 0.0020528; and STP6-120/36 was 0.0014253. These results demonstrate the great potential of the warfare strategy optimization (WSO) to improve the accuracy of photovoltaic models and advance photovoltaic technology.
Volume: 17
Issue: 2
Page: 1418-1425
Publish at: 2026-06-01

High step-up interleaved multilevel hybrid boost converter with switched-capacitor multiplier

10.11591/ijpeds.v17.i2.pp1118-1129
Andi M. Nur Putra , Adrianti Adrianti , Muhammad Imran Hamid
The global integration of renewable energy sources like photovoltaics requires efficient high-step-up DC-DC converters. Conventional boost converters exhibit inherent limitations in achieving high voltage gain efficiently, particularly under high duty cycle operation, where switching losses, device stress, and output voltage ripple become significant. This paper proposes a novel hybrid DC-DC converter that integrates a four-phase interleaved input stage with a five-level switched-capacitor (SC) multiplier network. The proposed topology introduces a modular and structurally decoupled architecture, in which current conditioning and voltage boosting functions are independently realized. This enables scalable voltage gain through modular expansion without requiring extreme duty cycles or additional magnetic components. The interleaved stage reduces input current ripple and improves current sharing, while the multilevel SC network provides a high voltage conversion ratio and balanced voltage stress across components. Comprehensive simulations using PSIM software validate the converter's performance. With a 25 V input, the proposed converter achieves an output voltage of approximately 250 V (gain of 10), a high efficiency of 95.2%, output voltage ripple below 2%, and balanced capacitor voltages. The results confirm that the proposed converter offers an efficient, scalable, and high-performance solution for high step-up applications.
Volume: 17
Issue: 2
Page: 1118-1129
Publish at: 2026-06-01

Performance optimization of hybrid renewable energy systems with real-time load forecasting using grey wolf-based predictive models

10.11591/ijpeds.v17.i2.pp1382-1395
Olumuyiwa Ajibola Awoniyi , Evans Chinemezu Ashigwuike , Chijioke Ejimofor , Timothy Oluwaseun Araoye
The performance optimization of hybrid renewable energy systems (HRES) is crucial for enhancing the efficiency, reliability, and sustainability of energy production. This study focuses on the integration of real-time load forecasting prediction using a grey wolf optimization (GWO)-based predictive model. The proposed methodology aims to address the challenges associated with the intermittent nature of renewable energy sources, such as solar and wind power, by providing accurate forecasts for load demands and solar irradiance. Real-time data from sensors and environmental parameters are incorporated to forecast the energy load and solar irradiance over short-term periods, which are then used to optimize the energy storage and generation components of the HRES. The GWO algorithm, known for its high accuracy and computational efficiency, is employed to optimize the dispatch of power from various sources while minimizing energy losses and ensuring system stability. The integration of GWO with real-time forecasting not only enhances the predictive capability of the system but also improves the overall economic viability of HRES by reducing operational costs and carbon emissions. This study demonstrates the potential of using intelligent optimization techniques and real-time forecasting for the sustainable operation of hybrid renewable energy systems, contributing to the development of smarter and more resilient energy grids.
Volume: 17
Issue: 2
Page: 1382-1395
Publish at: 2026-06-01

Permanent magnet generator for small and medium-scale hydropower: a systematic review

10.11591/ijpeds.v17.i2.pp1462-1474
Ngatono Ngatono , Raja Nor Firdaus Kashfi Raja Othman , M. Nazri Othman , Mohd Zulkifli Ab Rahman
Renewable energy, particularly hydropower, is a key focus in reducing reliance on fossil fuels and mitigating environmental impacts. Permanent magnet generator (PMG) has emerged as a highly efficient option for converting hydro-energy into electricity, offering advantages such as high efficiency, compact design, and minimal maintenance. This review explores the latest developments in PMG technology, particularly for small and medium-scale hydropower applications. A systematic review method was used to analyse 617 papers and narrow them down to 20 relevant studies. Key findings highlight advancements in PMG design, including modular stators, counter-rotating turbines, and cordless designs that enhance efficiency and adaptability in low-speed environments. However, significant challenges remain, including the high cost of magnetic materials like Neodymium Iron Boron (NdFeB), thermal stability issues, and more robust control systems to manage variable water flow conditions. The review concludes that while PMG holds great potential for hydropower applications, Further research is needed to optimize material usage, improve design, and reduce costs. Future work should focus on developing new magnetic materials and innovative rotor designs to ensure PMG can provide a scalable and sustainable solution for global energy needs.
Volume: 17
Issue: 2
Page: 1462-1474
Publish at: 2026-06-01

Optimization techniques for siting solar-powered EV charging stations: A systematic review and methodological classification

10.11591/ijpeds.v17.i2.pp1355-1368
Linda Faridah , Rustam Asnawi , Handaru Jati , Nurwijayanti Kusuma
Solar-powered electric vehicle (EV) charging stations are essential in advancing low-carbon transportation. However, determining optimal locations remains challenging due to spatial, technical, and environmental constraints. This systematic review, conducted under the PRISMA 2020 framework, synthesizes optimization techniques for siting solar-powered EV charging stations from 15 peer-reviewed studies published between 2016 and 2024. The reviewed methods are classified into five major categories: geographic information systems (GIS)-based spatial models, multi-criteria decision-making (MCDM) frameworks, hybrid approaches integrating fuzzy logic and GIS, heuristic/metaheuristic algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO), and artificial-intelligence-based models for predictive site selection. GIS-MCDM hybrid approaches were the most prevalent, offering improved robustness in spatial decision-making. Nevertheless, the literature reveals persistent gaps, including limited empirical validation, insufficient use of real-time data, and weak integration with smart-grid planning. This review provides a structured methodological classification, highlights sustainability considerations, and outlines a research roadmap toward intelligent, data-driven, and sustainable EV infrastructure planning aligned with global energy-transition goals.
Volume: 17
Issue: 2
Page: 1355-1368
Publish at: 2026-06-01

Proximal policy optimization-based type II PPC for EV fast charging

10.11591/ijpeds.v17.i2.pp835-848
Franco Aldrin Joseph Menezes , Gopala Reddy Krishnappa
In recent years, efficient and fast charging is critical for accelerating the adoption of electric vehicle (EV). However, traditional fully rated converters process the total power flow to the battery, but leading to excessive thermal stress, high energy losses, and quick battery degradation. Similarly, existing partial power converter (PPC) designs like type I and type II PPC, improve efficiency by processing only a fraction of the total power; however, they still face challenges such as additional isolation requirements, limited step-down performance, and lack of advanced control for fluctuating state of charge (SoC) conditions. To overcome these challenges, this research proposes a proximal policy optimization (PPO)-enhanced type II PPC for fast EV charging. Initially, the power is routed through a low-frequency (LF) isolation transformer and filtered to mitigate high-frequency noise. A portion of the power is partially processed through a SiC MOSFET-based phase-shifted full-bridge converter, while the remaining power bypasses directly to the battery. The PPO controller efficiently adjusts the phase shift angle in real time, optimizing switching cycles to reduce switching and thermal losses. The proposed PPO-type II PPC achieved better results in terms of peak efficiency (99.36%) and partial power handling (12.21%) when compared to existing type II PPC designs.
Volume: 17
Issue: 2
Page: 835-848
Publish at: 2026-06-01

Investigating reading habits and their impact on reading performance among Indian undergraduate students

10.11591/ijere.v15i3.38490
Komal Kumar Napa , Rajkumar Govindarajan , Sathya Subramanian , Senthil Murugan Janakiraman , Nageswari Devana , Billa Manindhar
This study investigates the reading habits, genre preferences, and reading behaviors of undergraduate students and examines how these factors influence their reading performance. A total of 342 responses were directly collected from students through a structured questionnaire. Descriptive statistics revealed strong inclinations toward analytical genres such as mystery/thriller, science fiction, and true crime, while newspaper reading frequency remained low. Hypothesis testing showed no significant differences in reading scores across gender or academic departments. A significant positive correlation emerged between daily reading duration and newspaper reading frequency. Most notably, students who preferred analytical genres demonstrated significantly higher reading scores (Cohen’s d=1.36). Regression analysis further confirmed genre preference as the strongest predictor of reading performance. These findings highlight the importance of genre engagement and daily reading routines in enhancing reading comprehension and literacy development. The study offers meaningful implications for educators, curriculum designers, and reading intervention programs.
Volume: 15
Issue: 3
Page: 2648-2658
Publish at: 2026-06-01

Spark-powered bioactivity prediction: a comparison of machine learning approaches

10.11591/ijai.v15.i3.pp2423-2430
Nazif Tchagafo , Abderrahmane Ez-Zahout , Ahiod Belaid
The arduous and expensive nature of drug discovery has long been a bottleneck in scientific progress. However, recent breakthroughs in computational power, notably machine learning (ML) and artificial intelligence (AI), are profoundly transforming the field. Automated machine learning (AutoML) presents itself as a significant advancement, streamlining model selection, and hyperparameter tuning. This study delves into the potential of AutoML to accelerate drug discovery by comparing it to classical ML techniques. The focus lies on predicting the bioactivity of epidermal growth factor receptor (EGFR), a critical protein implicated in many cancers. By utilizing the scalability of Apache Spark, vast and diverse datasets encompassing biological, chemical, and genomic data tied to EGFR are processed. This comparative analysis aims to evaluate the comparative performance of both approaches, thereby contributing actionable insights to drug discovery research.
Volume: 15
Issue: 3
Page: 2423-2430
Publish at: 2026-06-01

Modeling academic leadership in secondary schools: evidence from northeastern Thailand

10.11591/ijere.v15i3.39185
Dusadee Butburee , Nawee Udorn , Paitoon Puangyod
This study aimed to develop and empirically test a structural equation model of academic leadership among secondary school administrators in northeastern Thailand. Data were collected from 480 administrators using a structured questionnaire and analyzed through confirmatory factor analysis (CFA) and structural equation modeling (SEM). The results indicate that leadership personality and organizational context significantly influence curriculum leadership and innovation culture, which subsequently shape academic leadership outcomes. The proposed model explains 73.8% of the variance in academic leadership, demonstrating strong explanatory power. These findings contribute to the literature by providing an integrated structural framework that highlights the interplay between leadership capacity and contextual support in enhancing instructional quality and school effectiveness. However, the findings should be interpreted with caution due to the cross-sectional design and reliance on self-reported data.
Volume: 15
Issue: 3
Page: 2001-2010
Publish at: 2026-06-01

Smart capital mobilization in shared-use educational facilities: evidence from mega public universities

10.11591/ijere.v15i3.38993
Van-Dam Vu , Minh-Anh Nguyen Thi , Van-Quynh Ha
Although smart capital and shared facilities can improve efficiency in large public universities, many institutions still rely on fragmented paper-based management. This study evaluates how smart capital, integrating facilities, digital systems, and human readiness, drives behavioral change in shared facility management (FM). A survey of 246 staff members across multiple constituent units of a large Vietnamese public university system was conducted. The study integrates constructs from the technology acceptance model (TAM), technology readiness index (TRI), and information system (IS) success model. Partial least squares structural equation modeling (PLS-SEM) was employed to examine structural relationships and role-based differences. The results indicate that perceived ease of use (PEU) and system quality (SQ) significantly influence system use, while TRI affects adoption indirectly through PEU and perceived usefulness (PU). Differences between facility and academic staff highlight the importance of role-sensitive strategies for shared FM. This study provides an integrated framework for mobilizing smart capital in shared-use governance of mega public universities.
Volume: 15
Issue: 3
Page: 1853-1861
Publish at: 2026-06-01

Vietnamese EFL teachers’ cultural integration in business English classes: an ecological perspective

10.11591/ijere.v15i3.37919
Pham Thi Minh Thuy , Truong Minh Hoa
Cultural integration in English as a Foreign Language (EFL) instruction has become an important focus in Vietnamese universities, particularly in business and finance programs preparing students to navigate intercultural communication in global professional environments. While existing research has explored how language teachers include cultural elements in their instruction, limited attention has been given to understanding how these practices are shaped by the complex ecological systems where personal beliefs, institutional structures, resources, and sociocultural conditions interact dynamically. Addressing this gap, the present study investigates how EFL teachers at a Vietnamese public university integrate cultural content into their instruction. Guided by an ecological framework, the research employed a sequential mixed-methods design, collecting data through 67 questionnaires and 10 semi-structured interviews. Findings indicate that teachers prioritized international and target cultures, while local Vietnamese cultural content was largely underrepresented. Though teachers expressed strong commitment to fostering students’ intercultural competence for international business communication, their pedagogical practices were constrained by ecological factors like limited instructional time, rigid curricula, and a lack of localized, business-relevant resources. In response, several teachers leveraged personal agency and digital tools to adapt cultural content despite structural limitations. The study highlights the need for ecologically responsive cultural instruction in Business English classrooms. 
Volume: 15
Issue: 3
Page: 2618-2631
Publish at: 2026-06-01

Understanding digital competence profiles among in-service and prospective art teachers in Kazakhstan

10.11591/ijere.v15i3.38698
Masoumeh Shiri , Aidar Kuzdeubayev , Aidyn Kozhagulov , Zhazira Stambekova , Rakhat Berikbol , Nurgul Koshkinbayeva
This study investigates digital competence profiles between in-service art teachers and prospective art teachers (students in art teacher education programs) across three universities in Kazakhstan. Addressing a notable gap in understanding how digital skills are distributed in art education, the research employs a comparative descriptive design with a mixed-methods approach, combining a structured survey based on the European DigCompEdu framework and semi-structured interviews. Teachers were measured in the six domains of digital competence: professional engagement, digital resources, teaching and learning, assessment, empowering learners and enabling learners’ digital competence. Data from 197 participants (41 teachers, 156 prospective) showed following profiles: prospective fare better in creative and communication competencies; in-service performances are good on professional engagement and structured pedagogical activities. Face-to-face interviews triangulated findings across the survey and revealed how teacher use of digital tools in teaching and learning is shaped by generational differences prior training, as well as professional experience. These results highlight a necessity to develop role-sensitive digital skills in the field of art education. By triangulating quantitative and qualitative evidence, the study provides a nuanced understanding of digital competence across career stages and supports targeted training initiatives. It also lays the groundwork for future research using performance-based assessments and broader comparative contexts.
Volume: 15
Issue: 3
Page: 2487-2499
Publish at: 2026-06-01

Regenerative braking with battery management system in E-bike

10.11591/ijape.v15.i2.pp565-572
B. P. Divyashree , G. Lakith , H. N. Sukanya , Nagaling M. Gurav , Neeli Mallikarjuna , Unnam Anil
Energy neither be created nor be destroyed, but it can be transformed into other forms as per the law of conservation of energy. This information is epitomized by the regenerative braking system (RBS), which transforms kinetic energy into mechanical energy, thus recuperating waste energy into mechanical energy and making it beneficial. The regenerative braking have significant impact in electric vehicle technology due to the contemporary energy challenges and dwindling resources. Regenerative braking involves apprehending the lost kinetic energy during braking and converting it into a storable or instantly usable form. The recuperated kinetic energy can be reintegrated into vehicle’s power system or stored for further use, often in a battery, especially lithium-ion batteries which are managed by a battery management system (BMS) to ensure optimal performance and longevity. The utilization of various sensors by BMS to monitor parameters such as temperature, current, and voltage, entitling it to assess the battery’s health and determine its state of charge and discharge. Additionally, the BMS protects the battery against cavernous discharge and over-voltage, which can result from rapid discharging and charging currents, thereby optimizing the utilization of battery energy. In this article, the design of an electrical regenerative braking system with a battery management system in an electric bicycle (E-bike) applications are presented. The results show that the system works well in both battery-operated and regenerative modes. When in regenerative mode, the voltage and current stay within the specified range and are suitable for charging batteries. On the other hand, during regular operation, the increase in energy consumption is matched with the battery mode mileage.
Volume: 15
Issue: 2
Page: 565-572
Publish at: 2026-06-01

Analysis of CCS implementation in Indonesia’s coal fired power plants, economic optimization, and potential impact on Java-Bali grid for future decarbonization

10.11591/ijape.v15.i2.pp927-941
Anggit Raksajati , Sanggono Adisasmito , Veri Hendrayawan
This study aims to evaluate impact of retrofitting carbon capture and storage (CCS) technology on coal fired power plants (CFPP) in Indonesia. Using a representative 3×330 MW CFPP, the integration of CCS increases the levelized cost of electricity (LCoE) to 124 USD/MWh. Key cost components include CO₂ capture (21.7%), energy penalty from steam extraction (18.5%), and CO₂ transport and injection (16.7%). Sensitivity analysis indicates that CCS becomes financially viable under a high carbon cap (0.9 tCO₂/MWh) and a carbon tax of 76 USD/tCO₂. Meanwhile, International carbon markets offer a potential revenue at 75 USD/tCO₂ can fully offset CCS costs. Additionally, CAPEX grants can reduce LCoE to 12.4%, serving to mitigate upfront investment for CCS deployment. Within the Java-Bali grid, CFPP account for 58.8% of the generation mix with 41% aged 10-20 years using predominantly subcritical technology while 28% are over 20 years old and follow natural retirement being replaced by renewable energy. CCS retrofitting is more economically and technically viable for mid aged plants with newer technologies and lower emission intensities, supporting grid stability with limited renewable base load availability. This strategy also serves as a transitional pathway toward long term renewable integration until the LCoE of PV+BESS falls below 50 USD/MWh.
Volume: 15
Issue: 2
Page: 927-941
Publish at: 2026-06-01

Evaluating gamified learning strategies in internet of things-based software engineering education

10.11591/ijere.v15i3.39041
Amneh Shaban , Arar Al Tawil
This study examines the effectiveness of gamified formative assessment in undergraduate internet of things (IoT) education, focusing on how content complexity and question format influence student performance. A quasi-experimental comparative design was employed, administering two gamified quizzes to 75 undergraduate students enrolled in two IoT-related courses DevOps for IoT (n=41) and human computer interaction in IoT (n=34) during spring 2025. The gamified platform incorporated visual feedback, progress indicators, and interactive components. Results revealed statistically significant differences in student performance between the two quiz conditions, with human–computer interface (HCI) students substantially outperforming DevOps students. Question-level analysis further indicated that fill-in-the-blank formats impaired performance more than multiple-choice formats, and a pronounced ceiling effect was observed in the HCI assessment. These findings suggest that gamification effectiveness is contingent on alignment between content complexity, question format, and students’ prior knowledge. Educators are advised to calibrate assessment difficulty and question types carefully when designing gamified learning experiences in technical education.
Volume: 15
Issue: 3
Page: 2249-2260
Publish at: 2026-06-01
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