bluuebunny/crossref_metadata_2025 huggingface dataset:
Transformation and future trends of smart grid using machine and deep learning: a state-of-the-art review
Authors: Fahim Khairul Eahsun , Islam Md. Rakibul , Shihab Nahid Ahmed , Rahman Olvi Maria , Labib Al Jonayed Khondaker , Das Adri Shankar
Published: July 2024

A smart grid is a cutting-edge energy system designed to take over old-fashioned energy infrastructure in the twenty-first century. With comprehensive communication and computation capabilities, its primary objective is to increase energy distribution's dependability and efficiency while minimizing unfavorable effects. A number of approaches are needed for effective analysis and well-informed decision-making due to the massive infrastructure and integrated network of communications of the smart grid. In this study, we examine the architectural elements of the smart grid as well as the uses and methods using machine learning (ML) and deep learning (DL) with regard to the smart grid. We also clarify present research limitations and propose future directions for machine learning-driven data analytics. In order to improve the stability, reliability, security, efficiency, and responsiveness of the smart grid, this paper examines the implementation of several machine learning methodologies. This paper also covers some of the difficulties in putting machine learning solutions for smart grids into practice.
Coupled inductor interleaved boost converter with ANN and RNN based MPPT algorithm for PV system
Authors: Kavin K. S. , Karuvelam P. Subha , Kumar Naresh , Kar Siddheswar , Rahiman Riyaz A. , Patwa Sharda
Published: July 2024

An efficient machine learning approach for accomplishing the maximum power point tracking (MPPT) system for photovoltaic (PV) systems is proposed in this work. PV system is one of the most suitable renewable energy sources (RES) for electric vehicles (EV) based operations due to its ubiquitous availability and speed of installation. The deployment of PV-powered EVs reduces the quantity of carbon dioxide emitted into the atmosphere substantially. The primary objective of this research is to integrate a PV system with an EV load and to provide a constant power supply to the EV load with no distortions. A coupled inductor interleaved boost converter is used to raise voltage level of the PV because it has a wide conversions range with low leakage reaction times. Furthermore, the converter produces a consistent output with no fluctuations and high voltage gain. With the application of artificial neural network (ANN) based MPPT and recurrent neural network (RNN) based MPPT, the converter operational performance enhanced with steady dc link voltage is obtained. Consequently, it is stated that the employment of ANN and RNN-based MPPT controllers in PV-based systems offers improved DC link voltage regulation and lower power losses, thereby boosting system effectiveness. The MATLAB platform is used to test every component of the system's performance, and the findings show that the proposed system is more efficient than alternative approaches.
Enhancing solar power generation through AC power prediction optimization in solar plants
Authors: Krishnan G. Hari , Thrinath B. V. Sai , Reddy M. Ramprasad , Sudhakar Thukkaram
Published: July 2024

As the world embraces sustainable energy solutions, the accurate prediction of AC power generation in solar power plants becomes imperative for efficient energy management. This research endeavors to address this critical need through a meticulous exploration of five distinctive predictive algorithms: linear regression, gradient boosting, neural networks, support vector regression (SVR), and ensemble techniques. Leveraging a merged dataset comprising environmental parameters like ambient and module temperatures, irradiation, and historical yield, our study embarks on a comprehensive evaluation journey. The essence of this endeavor lies in the recognition that renewable energy sources, particularly solar power, are instrumental in mitigating environmental concerns associated with traditional energy generation. To unleash the full potential of solar power, a nuanced understanding of predictive methodologies is indispensable. Linear regression serves as a cornerstone, validating its foundational role. However, the crux of innovation lies in the advanced algorithms – gradient boosting, neural networks, SVR, and ensemble methods – each striving to optimize prediction accuracy. A novelty of this research stems from its holistic approach to predictive modelling. By meticulously comparing the performance of multiple algorithms, we uncover insights that transcend mere theoretical applications. Our findings assume significance in the context of renewable energy's societal impact.
Efficiency enhancement in hybrid renewable energy system using polycrystalline silicon cell
Authors: Kumar Mugachintala Dilip , Himabindu D. , Kumar Yarrem Narasimhulu Vijaya , Mohana Thota , Shashank Ramagiri , Rajanna Bodapati Venkata
Published: July 2024

Accessing the unelectrified rural population is currently not possible through grid expansion, as connectivity is neither economically viable nor encouraged by large companies. Additionally, conventional energy options, such as broom-based systems, are being gradually phased out of rural development programs because to growing oil prices and the unbearable effects of this energy source on consumers and the environment. A hybrid generator using solar and wind can solve this issue. Proven hybrid systems are the best choice for delivering high-quality power. Nowadays, hybrid renewable energy systems are becoming popular. The power system provides electricity to remote and isolated areas. Villages and residents in the forest area had their electricity cut off due to the forest environment. While creating a renewable energy source near the load. Solar power and wind power are renewable sources, solar power works in the morning and wind can make morning and night time to synchronize both output voltage and frequency to provide provides the ability to charge continuously, without interruption. The main objective of the project is to provide mixed renewable energy without interruption.
An overview of the future smart charging infrastructure for electric vehicles
Authors: Sutikno Tole
Published: July 2024

Smart charging is a technology that allows electric vehicles (EVs) to communicate with charging devices. This paper presents an overview of smart EV charging. Smart charging is a future solution for businesses, allowing them to remotely monitor EV charging events, manage charging stations, and concentrate on their core operations. It also simplifies payments, regulates electricity consumption, and makes charging stations easy to manage. Smart charging solutions assist utility companies in developing their own EV charging networks by stabilizing the grid, adapting to changing demands, and easily managing multiple charging stations. Furthermore, the visibility of all actions at charging stations facilitates keeping track of business activities. Smart charging is a critical component of electric vehicles (EVs) because it provides future-proof features such as cloud connectivity, standardized socket types, and backend compatibility. Smart EV charging includes an admin panel for managing multiple charging points, automatic payments and billing, end-user mobile and web apps, charging station roaming, dynamic load management (DLM), and energy management. These features enable charging stations to better manage their resources, attract more users, and protect the local grid against peak loads.
Control of a stand-alone variable speed wind turbine generator system
Authors: Sunil Kumar Chava , Banka Sujatha , Chandini Shaik , Vaishnavi Jakkoju , Himabindu Gorla , Meghana Gudibandi
Published: July 2024

The focus of the work is on optimizing the wind power system to generate high-quality power from renewable energy sources. This article describes how to control a stand-alone PMSG wind turbine system using perturb and observe (P&O) maximum power point tracking (MPPT) controller. This aids in the regulation of output voltage levels and the maximum power provided to the load. The present study employs P&O MPPT control algorithm to optimize energy extraction from the wind resource, while simultaneously ensuring a stable voltage throughout the load. The goal of MPPT approaches is to establish a reference speed so that the wind energy conversion system (WECS) control system can follow the MPPT trajectory. The MPPT controllers can keep the system running smoothly irrespective of the wind speed fluctuations. There is a significant power output improvement over conventional controllers when using the proposed MPPT controller, according to the comparison results. The DC-DC boost converter was implemented for enhancing the low AC voltage given by the permanent magnet synchronous generator (PMSG).
Reading comprehension studies in the last decade: global trends and future direction of Indonesia language researches
Authors: Suyanto Edi , Samhati Siti , Aisyah Nenden Lilis , Antrakusuma Bayu
Published: July 2024

The publication trend related to reading comprehension studies in the last decade has sharply grown. Nevertheless, studies offering comprehensive bibliometric and bibliographic reviews related to reading comprehension studies have not been conducted nor also found in the journal or conference proceeding. The purpose of this study is to present a bibliographic and bibliometric review of the numerous documents studying reading comprehension skills. A bibliometric analysis was performed to carry out this study whereby 1,681 eligible documents from the Scopus database published from 2013 to 2022 were used as research materials. Results showed that in 2013-2022, the publication trend of reading comprehension studies slightly increased while the citation trend on the documents regarding reading comprehension skills tended to fall sharply. Additionally, at least there were several major emerging themes of reading comprehension studies such as methodology, language, educational level, reading disability, reading intervention, reading comprehension predictor, and moderating factor of reading comprehension. This study implies that researchers in the field of Indonesian language education can focus on the utilization of Indonesian textbooks in investigating learners’ reading comprehension skills, develop innovative and effective reading interventions to enhance learners’ reading comprehension skills, and explore some other moderating factors of reading comprehension skills such as ethnicity, culture, geographical location, and textbook topic.
Academic achievements of medical student related to interactive problem-based learning in blended learning context
Authors: Troyanskaya Marija , Garnova Natalya , Filippova Alla , Ustyuzhina Olga , Pronkin Nikolay
Published: July 2024

The purpose of the current study is to prove the effectiveness of using interactive elements in problem-based learning (PBL) for medical students. The simultaneous use of interactivity and a problem-solving approach makes it possible to improve the pedagogy of distance learning and improve the training of medical specialties. In the study, 120 medical students of 4-5 university courses were enrolled, who were divided into 3 groups, a control group and two experimental ones, who received intervention one in the form of PBL, the second - PBL and also interactive elements in blended learning. Participants in the groups were randomly selected but with an equal representation of men and women aged 21 to 23 years. The results were measured using the university 12-point system and the presence of statistically significant differences was established using the student’s t-test. It was found that in experimental groups, the results of the post-test of academic achievement were statistically significantly higher than the pre-test. At the same time, the best changes were recorded in the group with PLB and interactive training at the same time. There were no statistically significant differences between genders within each group or between groups; however, females performed slightly better on average than males. Practically, the results of the study can be used to improve the academic training of physicians during distance learning and to improve practical problem-solving skills. The current study can be used in further analysis of PBL of medical students subject to the global integration of digital technologies in educational systems.
Optimizing students’ practical skills through project-based learning: case study in vocational high schools
Authors: Dzulkurnain Mohammad Iskandar , Aminuddin Afrig , Hammood Waleed A. , Abdullah Khairul Hafezad , Alam Miah Mohammad Badrul
Published: July 2024

Competition in the global era requires graduates from vocational schools to be more skilled in hard and soft skills to adapt to the industrial world. Adaptation of vocational education institutions to the industrial world is vital; thus, they can continuously update the skills of their graduate candidates. Hence, this research aims to describe the implementation of the Center of Excellence curriculum and project-based learning in a vocational high school as a form of school adaptation to the development of the industrial world in the 21st century. This research was included in a qualitative research design adopting a case study. The research respondents consisted of vocational high school residents in Central Java. Data was collected through interview techniques and observations and then analyzed interactively and descriptively. The research results then reported that the school was fully committed to implementing the Center of Excellence curriculum regarding teaching human resources and learning facilities. The project-based learning process also seemed to run optimally. Students could accept it, considering that project-based learning was implemented because it was an adaptive model to accommodate 21st century competencies. However, there is still room for improvement and optimization in order to effectively implement this operational curriculum and enhance students' ability to acquire 21st century skills.
Factors that influence global literacy: what is the most dominant?
Authors: Pratama Anggi Tias , Sudrajat Ahmad Kamal , Anazifa Rizqa Devi , Kurniawati Atik
Published: July 2024

Global literacy is a crucial ability to maintain the world’s peace. Several studies show that demographic factors influence the development of a person’s competence. However, the influence of demographic factors on global literacy has not yet been explored, especially in high school students. This research was conducted to determine the factors that most influence students’ global literacy in biology learning. The factors used in this research are gender, school profile (public or private school), and interest in learning biology. This study used a cross-sectional survey design with 2,759 students participating. Students’ global literacy was analyzed from a questionnaire of four aspects: exploration, communication, using the internet, and act for society. This study found that all the proposed factors influence students’ global literacy, but the factor that has the most dominant influence is the school profile. This research provides a new view regarding the influence of demographic factors on students’ global literacy. The government and related parties can use these results to design effective learning innovations to develop students’ global literacy.
Improving trigonometric competency with GeoGebra: a quasi-experimental study in a high school
Authors: Carriazo-Regino Yulieth , Hurtado-Carmona Dougglas , Bermudez-Quintero Andrés
Published: July 2024

This quasi-experimental study examines the efficacy of GeoGebra in enhancing trigonometric competence among tenth-grade students in Montería, Colombia. Comparing an experimental group that used GeoGebra with a control group receiving traditional teaching, key competencies such as reasoning and argumentation, communication, representation and modeling, and problem posing and solving were evaluated. Pre-intervention results showed that 88.19% of students in the experimental group had insufficient performance in reasoning and argumentation. After the implementation of GeoGebra, this figure decreased to 5.5%. In competencies of communication, representation, and modeling, the insufficient performance reduced from 85.7% to 5.5%, and in problem posing and solving, from 80.3% to 5.7%. These significant improvements demonstrate the positive impact of GeoGebra on the development of mathematical competencies. The study concludes that GeoGebra is an effective tool for strengthening trigonometric competence in high school students, highlighting the importance of integrating digital technologies in mathematics education. The findings suggest the need for more research on the use of technological tools in mathematics education and support investment in technological resources and teacher training.
First-year students’ mathematical skills: assessing and developing an innovative strategy for teaching mathematics
Authors: Padernal Rogie Espia , Tupas Sylvino Venus
Published: July 2024

In order to succeed in advanced mathematics and other related courses while in college, students must have a strong foundation in the subject of mathematics. Thus, this study aimed to determine the level of students’ fundamental skills in mathematics in the areas of number sense, mathematical representation, spatial skills, estimation, patterns, and problem-solving when they are grouped according to the school of origin, strand, and program enrolled. Likewise, to test if there is a significant difference in fundamental mathematics skills when grouped according to the demographics. A descriptive comparative research design was utilized, and 278 first-year students participated. The results revealed that students performed better on their fundamental skills in mathematics in the area of patterns and performed lowest mean in spatial skills. Students who graduated from public schools performed well in all areas compared to private school students; in terms of program enrolled, fundamental skills in math varies. Furthermore, there is a significant difference in students’ fundamental skills in mathematics when grouped according to the school of origin and strand, otherwise in program enrolled. This study suggests that mathematics teachers must utilize a different teaching strategy suited to students’ needs following the learner-centered approach in teaching.
The influence of accounting students’ personality traits toward their entrepreneurship intention
Authors: Ahmad Noor Lela , Fazil Nadiah Farhanah Mohd , Yusof Rohaila , Jamaluddin Nor Sa’adah , Yahaya Rusliza
Published: July 2024

This paper intends to explore entrepreneurship intention among the youth by examining their personality traits. The respondents of this study were accounting students in their final year from seven public universities across Malaysia. A validated questionnaire was employed and distributed to representatives of each university, obtaining a total of 756 responses. The collected data was analyzed using descriptive statistics and utilized partial least square-structural equation modelling (PLS-SEM) to analyze the hypotheses. The results revealed that personality traits influence entrepreneurship intention of accounting students’ and conscientiousness being the most significant trait with a coefficient of 0.612. This paper suggests that personality traits namely conscientiousness, extraversion, openness to experience and agreeableness can boost entrepreneurship attitude, thus it should be optimized systematically into the education context to shape young personalities that are inclined towards entrepreneurship. Essentially, Ministry of Higher Institution, universities, colleges, and schools are advised to shape entrepreneurial personalities through the education curriculum and frequent practical sessions with inspiring entrepreneurs in the industry. Further, integrating the elements of personality traits into entrepreneurship education can serve as a guide for financial management of a business.
How do elementary school teachers shape their students' self-regulated and creativity in learning mathematics?
Authors: Bistari Bistari , Hamdani Hamdani , Rustam Rustam , Dashela Tarina , Mumtazah Nadia Wardah , Veven Veven
Published: July 2024

So far, mathematics learning has only focused on a curriculum that prioritizes outcomes over processes, so attitudes are rarely the target of learning. In fact, a positive attitude, especially self-regulated and creativity, is needed in learning mathematics and must have been formed since elementary school. This research, with the aim of describing efforts to establish independence and creativity in learning mathematics by elementary school teachers in West Kalimantan, uses a qualitative descriptive method with a questionnaire as a research instrument. The results of the study show that: (i) the formation of self-regulated learning by the teacher is very good, especially in the indicators of disciplined behavior. However, it needs to be improved on indicators of behaving based on one's own initiative; and (ii) the formation of learning creativity by the teacher is very good, especially on the indicator of having a great curiosity. However, it needs to be improved on indicators of diligent behavior and not getting bored easily.
Variable frequency drive trainer kits for electronic control system subjects in vocational secondary schools
Authors: Hamid Mustofa Abi , Sudira Putu , Triyono Mochamad Bruri , Rizqillah Muhamad Aqil , Irwanto Irwanto , Setiawan Dedi , Desmira Desmira , Martias Martias , Hakiki Muhammad , Subramaniam Tamil Selvan , Abdurrahman A.
Published: July 2024

The objective of this study is to create a variable frequency drive (VFD) trainer kit, assess the practicality of the developed VFD educational tool, and evaluate its impact on the academic performance of industrial electronic engineering students, particularly in the area of electronic control systems. The study utilizes the ADDIE model and customized to meet the requirements and consists of the following phases: analysis, design, development, implementation, and evaluation. There were 130 respondents consisting of 122 vocational students, 1 industry expert/practitioner in the field of VFD, 1 vocational training center instructor, 4 vocational teachers, and 2 lecturers. Data were collected using questionnaires with 4 Likert scales from strongly agree to strongly disagree, feasibility assessment sheets from media experts and material experts, interviews, and electronic control system learning outcomes tests. The learning media receives a “highly feasible” and the job sheet obtains 67 “highly feasible”. Moreover, the level of effectiveness of the learning media receives a score of 0.724, indicating high effectiveness. Therefore, they have proven to be effective in enhancing student learning outcomes and developing their proficiency in controlling the speed of electric motors. This will help bridge the gap between the industry's skill requirements and the skills taught in schools.
The impact of continuous professional development activities on student learning outcomes and employability
Authors: Nassereddine Mohamad , Nassreddine Ghalia
Published: July 2024

The fast development of engineering technologies forces a wide range of students to choose the technological path for their careers. Universities focus on theoretical study with limited practical exposure. To ensure students are prepared for the industry requirements, engineering universities set a core industrial experience for all students. This industrial experience aims to bridge the gap between academia and industry and to ensure students have gained the required industrial. The work in this paper highlights the importance of continuous professional development (CPD) hours for engineering students. The paper studies the impact of CPD hours on the critical skills of the student learning outcomes. A descriptive analytical methodology is applied to examine this impact. Thus, a survey of 34 questions was created and distributed to students at engineering schools in different universities across the MENA and Gulf Region. A sample of 234 answers is collected and analyzed using a statistical package for the social sciences (SPSS). The results show that students agree that CPD activities can enhance their learning outcomes, teamwork skills, public speaking, and technical competencies. The results show that student believes that CPD activity may enhance their chance of securing employment within a short timeline after graduation.
Integrating environmental social and governance values into higher education curriculum
Authors: Alenezi Mamdouh , Alanazi Fayez
Published: July 2024

This paper proposes a framework for integrating Environmental, Social, and Governance (ESG) principles into higher education institutions. The framework consists of six components: curriculum integration, research and innovation, campus operations, community engagement, leadership and governance, and assessment and reporting. Each component is supported by eight implementation strategies that provide practical guidance for institutions looking to advance their sustainability efforts. The proposed framework is informed by a literature review that highlights the importance of ESG considerations in higher education, the challenges and opportunities associated with integrating sustainability into higher education institutions, and the role that institutions can play in promoting sustainable development. The framework is also supported by case studies that illustrate how institutions have successfully implemented sustainability initiatives and the benefits that have accrued as a result. The proposed framework has the potential to make a significant contribution to the advancement of sustainability in higher education institutions and promote sustainable development in the broader community. It is hoped that the framework will be useful to institutions, policymakers, and other stakeholders interested in promoting sustainability in higher education.
The effect of the mathematics instruction model on enhancing mathematical thinking
Authors: Iamcham Narunat , Chanchusakun Saranya
Published: July 2024

The objectives of this research were to study the efficacy of the mathematics instructional model (BRIGHT model) based on realistic mathematics education (RME) and model-eliciting activities (MEAs) approaches to enhance mathematical thinking (MT) for upper primary school students as follows: i) to compare the mathematics achievement of students before and after studying with the BRIGHT model, ii) to compare the MT of students before and after studying with the BRIGHT model, and iii) to evaluate the students' and mathematic teachers' satisfaction on learning activities by using the BRIGHT model. The results of this research were as follows: i) the mathematics achievement and MT of students after studying were significantly higher than before studying with the BRIGHT model; ii) the student satisfaction with learning activities using the BRIGHT model was satisfied all aspects of the assessment. The mean scores from highest to lowest were as follows: benefits that student received, learning atmosphere, and learning activities, respectively; and iii) the satisfaction teachers and educational superiors were very satisfied with the learning management process and applying the BRIGHT model. Therefore, learning through the BRIGHT mathematical modeling has shown all aspects of students' and mathematic teachers' expected development.
Folk art classification using support vector machine
Authors: Bhatt Malay , Mehta Apurva
Published: July 2024

Tremendous amounts of effort have been carried out every year by the governments of all the countries to preserve art and culture. Art in the form of paintings, artifacts, music, dance, and cuisines of every country has the utmost importance. The study of Tribal arts provides deep insight into our history and acts as a milestone in the roadmap of our future. This paper focuses on three popular folk arts namely: Gond, Manjusha, and Warli. 300 images of each artwork have been collected from various online repositories. To generate a robust system, data augmentation is applied which results in 7510 images. A feature vector based on a generalized co-occurrence matrix, local binary pattern, HSV histogram, and canny edge detector is constructed and classification is performed using a linear support vector machine. 10- fold cross-validation produces 99.8% accuracy.
One time pad for enhanced steganographic security using least significant bit with spiral pattern
Authors: Rihartanto Rihartanto , Budi Utomo Didi Susilo , Rizal Ansar , Diartono Dwi Agus , Februariyanti Herny
Published: July 2024

Data is an important commodity in today’s digital era. Therefore, data needs to get adequate security to prevent misuse. A common data security practice in the transmission of information is cryptography. Another approach is steganography, which hides secret messages in other media that are not confidential and can be accessed by the public. In this study, the spiral pattern is used for data placement using the least significant bit (LSB) method. Modifications were made to the 2-bits LSB to increase the data capacity that can be hidden. In order to increase security, the data is first converted into a datastream using random numbers as one time pad (OTP). exclusive-OR (XOR) operation is performed on datastream and OTP to get encrypted data to be hidden. The results showed that the image quality of the steganography results at a capacity close to 100% was still fairly good, as indicated by a peak signal-to-noise ratio (PSNR) value greater than 46 dB. Visually, the steganographic image does not look different from the original one. Likewise, the use of random numbers as OTP succeeded in changing the hidden data significantly, as indicated by the avalanche effect value above 50%.
Efficient traffic signal detection with tiny YOLOv4: enhancing road safety through computer vision
Authors: Santhiya Santhiya , Johnraja Jebadurai Immanuel , Leelipushpam Paulraj Getzi Jeba , Veemaraj Ebenezer , Sharance Randlin Paul , Keren Rubee , Karan Kiruba
Published: July 2024

As decades go by, technology advances and everything around us becomes smarter, such as televisions, mobile phones, robots, and so on. Artificial intelligence (AI) is applied in these technologies where AI assists the computer in making judgments like humans, and this intelligence is artificially fed to the model. The self-driving technique is a developing technology. Autonomous driving has been a broad and fast-expanding technology over the last decade. This model is carried out using the tiny you only look once (YOLO) algorithm. YOLO is mainly used for object detection classification. Tiny YOLO model is explored for the traffic signal detection. ROBI FLOW dataset is used for object detection which contains 2000+ image data to train the tiny YOLO model for traffic signal detection in real time. This model gives an improved accuracy and lightweight implementation compared to other models. Tiny YOLO is fast and accurate model for real-time traffic signal detection.
A study and analysis of input output linearization control of permanent magnet synchronous motor based on fuzzy observer
Authors: Belbekri Tahar , Bellali Badreddine
Published: July 2024

This article describes the nonlinear control of input output linearization type without speed sensor of permanent magnet synchronous motor (PMSM). This machine which has several advantages such as simple structure and high efficiency. Its control requires speed determination by sensor. Due to several disadvantages of using the speed sensor, we replaced it with a so-called Luenberger observer. The simulation results show that the observer considerably improves the performance of the PMSM in particular in overshooting during start-up and during speed reversal. It also shows good robustness when applying load torque. To obtain high operating performance of the PMSM, it basically needs to replace the proportional integral (PI) controller with another controller based on fuzzy logic. This artificial intelligence technique allowed us to obtain more efficient results than the traditional method.
Optimizing resilience in large-scale integration of renewable energy sources: Exploring the role of STATCOM device
Authors: Chandarhasn Chelladurai , Percis Edwin Sheeba
Published: July 2024

Modern power grids in regions with high renewable energy sources face unique challenges. Incorporating renewable energy, like wind and solar, can cause voltage, frequency, and power fluctuations, leading to instability. This study focuses on Tamil Nadu's extra high voltage transmission system, which has significant wind generation. It explores the impact of large-scale renewable energy integration and proposes the use of static synchronous compensators (STATCOM), a part of flexible alternating current transmission systems (FACTS). STATCOM actively monitors and controls the grid, ensuring stability under unpredictable conditions. It is observed that the system maintains the grid stability with base rotor angle and voltage of 1.0 per unit during sudden loss 120 MW generator. Also, during the sudden loss of all renewable resources, the grid maintains the stability with rotor angle of 60 degree (base value). The findings provide insights into challenges and solutions, fortifying grid stability for accommodating more renewable energy without compromising reliability or efficiency.
Solar pumps automation system using programmable logic controller for pumped hydro storage
Authors: Syafii Syafii , Azizah Farah , Salfikri Iqbal
Published: July 2024

Pumped hydro storage (PHS) is an energy storage technology that uses electrical energy to pump water to a higher reservoir. The water is then released back into the lower reservoir to generate electricity. If the water source is limited, the pump must be stopped to prevent damage. The automation system can improve the pump's performance and protect it from damage. Therefore, a Solar pumps automation system using a programmable logic controller for pumped hydro storage is developed to avoid damage due to overheating that can damage the pump. With this automation system, the pump will automatically stop working when no water flows. The automation system at PHS will use a programmable logic controller or PLC as the controller, with a water flow sensor and an ultrasonic sensor to measure water levels. Arduino will assist in reading the analogue input on the PLC. The research shows that all the sensors work well with an error under 0.4%. The pump will turn on when the water level is less than 30 cm, while the pump will turn off when the water flow is less than 20 liters/minute. The pump can flow water stably at a water flow value level of 25-26 liters/minute.
Simulation model development and experimental validation of a PFC converter
Authors: Martins Antonio Pina , Morais Vítor A.
Published: July 2024

The most common interface to the electric grid of small power loads, which is based on a diode bridge followed by a bulk capacitor, generates a large number of low-frequency harmonics in the input current. To comply with the IEC 61000-3-2 and IEEE 519 standards it is needed to optimize the interface in terms of current harmonics and the topology composed by a diode bridge and a DC/DC boost converter operating in the critical conduction mode is one having a greater number of comparative advantages. There is a large number of controllers in the market but also a lack of the associated simulation models exists. This paper focuses on the development, validation and testing of a simulation model that mimics an existing integrated circuit and allows for an accurate prediction of the real behavior of the complete converter. The experimental results validate the model with high fidelity and confirm the added value of the topology and control method applied either in transient and steady-state operation.
Innovative GMPPT searching algorithm and precise backstepping control for grid-connected PV system in challenging shading environments
Authors: Bahri Mohamed , Talea Mohamed , Bahri Hicham , Aboulfatah Mohamed
Published: July 2024

Photovoltaic (PV) systems encounters different problems of weather conditions that lowers their generated power. For this reason, maximum power point tracking (MPPT) have been designed to track the maximum power at all times and thus minimize these losses. However, under complexes partial shading condition (PSC) these losses are even higher. Classical MPPT algorithms fails to track the global MPP (GMPP) which further augment the power losses. Alternately, a grid connected topology of the PV system is chosen but needs a control method to phase the inverter current with the grid. This paper introduces a novel algorithm named power search algorithm (PSA) that memorizes the highest peak as it scans the PV curve then returns and locks it. Due to its simplicity, this proposed method is suitable for practical use and manages to track the GMPP with high efficiency of 99.5% and a mean response time of 0.04 s. Comparison was made with a gray wolf optimization (GWO) technique. Simulation was done in MATLAB/Simulink. Results shows that the proposed algorithm performed better than the GWO in all aspect of efficiency, tracking time and oscillations around GMPP. Also, a backstepping control was used to inject a good synchronized power to the grid.
Determination of minimal total harmonic distortion for single-phase multilevel inverter
Authors: Wong Quan Ming , Sea Yee Wei , Chew Wei Tik , Yong Wui Ven , Zaidi Ahmad Firdaus Ahmad , Ahmad Noor Syafawati , Ong Siok Lan , Leong Jenn Hwai
Published: July 2024

Multilevel inverters (MLIs) offer numerous advantages, such as low voltage stresses on power switches, low switching losses, and high efficiency. Switching angles applied to MLI must be selected carefully to generate an output voltage waveform with low total harmonic distortion (THD). This paper proposes an improved algorithm to determine the switching angles with low THD for MLI. The proposed algorithm has been implemented using a MATLAB script to compute a set of switching angles with low THD from 3- to 31-level cascaded H-bridge MLI (CHBMLI). A PSIM simulation model has been developed to validate the switching angles and the corresponding THDs obtained from the MATLAB script. An experimental prototype has also been developed to validate the simulation results. The results obtained from the MATLAB script, the PSIM simulation, and the experimental measurement are in good agreement.
CNN based fault event classification and power quality enhancement in hybrid power system
Authors: Quawi Abdul , Shuaib Y. Mohamed , Manikandan M.
Published: July 2024

A resilient approach is presented in this study for detecting and classifying faults for power distribution systems integrating renewable energy sources (RES). Combining discrete wavelet transform (DWT) and convolutional neural network (CNN). The suggested framework addresses the challenges of RES intermittency and kinetic energy insufficiency. The recommended methodology is evaluated in a MATLAB platform, featuring a power distribution system with photovoltaic (PV) and wind energy conversion system (WECS), stabilized by a boost converter and cascaded fuzzy logic controller (CFLC) based maximum power point tracking (MPPT) for PV and a PI controller for WECS. Comparative analyses demonstrate the superior performance of the CNN classifier with an accuracy of 96.33%, outshining existing classifiers, including ANN. Furthermore, under various fault conditions, the CNN consistently achieves high accuracy, with 98% for Islanding, 95% for line-to-ground fault, and 96% for line-to-line fault. The proposed approach exhibits excellent computational efficiency, with a training time of 10.5 hours, inference speed of 5 milliseconds, and resource utilization of 85%, emphasizing its suitability for instantaneous fault identification in power systems.
New records, diagnostics and preliminary checklist of the superfamily Pentatomoidea (Hemiptera: Heteroptera) from the Comoro Islands
Authors: NICOLAS VINCENT , CARAPEZZA ATTILIO , RIDER DAVID A. , KMENT PETR
Published: July 2024

The following species are recorded from the Comoro Islands for the first time: 12 species of Pentatomidae: Pentatominae—Anoano pronotalis Cachan, 1952 (from Mayotte), Antestiopsis clymeneis cf. galtiei (Frappa, 1934) (Mayotte), Bagrada hilaris (Burmeister, 1835) (Mayotte), Bathycoelia rodhaini Schouteden, 1913 (Mayotte), Coquerelia ventralis Horváth, 1904 (Mayotte), Eurysaspis transversalis Signoret, 1851 (Anjouan, Grande Comore, Mayotte), Gadarscama ebenaui Reuter, 1887 (Anjouan, Grande Comore, Mohéli, Mayotte), Lerida annulicornis (Signoret, 1861) (Anjouan, Mayotte), Neoacrosternum validum (Horváth, 1904) (Grand Comore, Mayotte), Nezara viridula (Linnaeus, 1758) (Mayotte), Piezodorus hybneri (Gmelin, 1790) (Mayotte), and Stenozygum mirabile (Signoret, 1861) (Mayotte); two species of Plataspidae—Brachyplatys hemisphaerica (Westwood, 1837) (Mayotte) and Coptosoma maculatum Westwood, 1837 (Mayotte); and one species of Scutelleridae—Hotea denticulata Stål, 1865 (Mayotte). The endemic pentatomine species Bathycoelia cuneifera Bergroth, 1893, syn. nov., is recognized as a junior subjective synonym of the widely distributed African species Bathycoelia thalassina (Herrich-Schäffer, 1844). The lectotype of B. cuneifera is designated herein. The checklist of the Pentatomoidea of Comoro Islands includes six species of Cydnidae, 21 species of Pentatomidae, two species of Plataspidae, one species of Scutelleridae and 1 species of Tessaratomidae. Of these species, six are endemic to the archipelago, 14 species are subendemic (shared with Madagascar and/or Aldabra Atoll), and nine species are widespread, occurring also on the African mainland (including the cosmopolitan pest Nezara viridula and two species of Bathycoelia Amyot & Serville, 1843 from the Guinean area, all three possibly alien to the archipelago). We document an additional eight species (six species of Pentatomidae, one species of each Scutelleridae and Tessaratomidae) that are identified to generic level only (two recorded from Grand Comore, seven from Mayotte, one of them occuring in both islands). Mayotte is the best sampled island, with 28 recorded species, followed by Grande Comore (11 species), Anjouan (six species), and Mohéli (four species). In addition the following new records are provided: Bathycoelia rodhaini from Cameroon, Central African Republic, Gabon and Zambia, Bathycoelia thalassina from Central African Republic and Ethiopia, and Piezodorus hybneri from Angola (Cabinda) and Sierra Leone. The type locality of Eurysaspis transversalis Signoret, 1851, India: Puducherry, is considered an error as the species occurs only in Madagascar and Comoros. The following plant associations are recorded from Mayotte: Bagrada hilaris on Cleome viscosa (Cleomaceae), Eurysaspis transversalis on Senna singueana (Fabaceae), and Piezosternum sp. on Cucumis sativus (Cucurbitaceae) and Mikania capensis (Asteraceae).
Magnitude of emergence agitation, its interventions and associated factors among paediatric surgical patients
Authors: Aniley Habtamu Tilahun , Mekuria Samrawit Tassew , Kebede Mebratu Abraha , Gebreanania Alembrhan Hagos , Muleta Mahteme Bekele , Aniley Tafere Tilahun
Published: July 2024

Background

Emergence agitation is a transient confusional state of a child associated with consciousness from general anaesthesia, commonly occurs in the postoperative setting which delays their recovery and exposes them to traumas. The main objective of the current study was to investigate the magnitude of emergence agitation, its interventions and associated factors among paediatric surgical patients at Saint Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia.

Methods

Hospital based cross-sectional study with prospective follow-up framework was conducted on a paediatric surgical patients aged 2-14 years who underwent surgery under general anaesthesia between June 1 - October 30 2022. Stratified sampling method followed by simple random sampling technique was employed to reach study participants. Magnitude of emergence agitation and its interventions done at post-anaesthetic care units were recorded. Data analysis was carried out using a descriptive statistics method and the results were summarized using tables and diagrams. Bivariate analysis was done to identify causal relationship and multivariable analysis to assess the confounding effects of factors associated with emergence agitation. A p-value of less than 0.05 was considered statistically significant factor.

Results

A total of 150 participants were included in the current study, where 107 (71.3%) were male and 97 (64.7%) were preschool aged. About 81 (54%) of care givers were female and majority of them have completed primary school. The mean (standard deviation) age of the participants was 6.4 (3.57) years. Around 42.7% of them developed emergence agitation with an average duration of 8.39 ± 4.45 minutes. Factors such as propofol administration at the end of procedure (OR of 0.104 with 95% CI [0.035, 0305]), Ear, nose, throat surgery and oral maxillofacial surgery (OR of 2.341 with 95% CI [1.051, 5.211]) and arrival of patient to recovery awake (OR of 0.456 95% CI [0.209, 0.994]) showed statistically significant association with emergence agitation.

Conclusion

Almost half of the study participants experienced emergence agitation which is high magnitude. Ear, nose, throat surgery and oral maxillofacial surgeries were predictive factors of emergence agitation while propofol administration at the end of procedure and arrival of patient to recovery awake significantly decreased risk of emergence agitation. Therefore, anaesthesia personnel should have essential skills and knowledge to effectively care for children perioperatively including to minimize and treat emergence agitation.
A compartmental model for smoking dynamics in Italy: a pipeline for inference, validation, and forecasting under hypothetical scenarios
Authors: Lachi Alessio , Viscardi Cecilia , Cereda Giulia , Carreras Giulia , Baccini Michela
Published: July 2024

We propose a compartmental model for investigating smoking dynamics in an Italian region (Tuscany). Calibrating the model on local data from 1993 to 2019, we estimate the probabilities of starting and quitting smoking and the probability of smoking relapse. Then, we forecast the evolution of smoking prevalence until 2043 and assess the impact on mortality in terms of attributable deaths. We introduce elements of novelty with respect to previous studies in this field, including a formal definition of the equations governing the model dynamics and a flexible modelling of smoking probabilities based on cubic regression splines. We estimate model parameters by defining a two-step procedure and quantify the sampling variability via a parametric bootstrap. We propose the implementation of cross-validation on a rolling basis and variance-based Global Sensitivity Analysis to check the robustness of the results and support our findings. Our results suggest a decrease in smoking prevalence among males and stability among females, over the next two decades. We estimate that, in 2023, 18% of deaths among males and 8% among females are due to smoking. We test the use of the model in assessing the impact on smoking prevalence and mortality of different tobacco control policies, including the tobacco-free generation ban recently introduced in New Zealand.