bluuebunny/crossref_metadata_2025 huggingface dataset:
Distance in Information and Statistical Physics III
Authors: Yamano Takuya
Published: January 2023

This Special Issue is a subsequent edition of a previous collection that focused on the notion of distance in two major fields: Distance in Information and Statistical Physics Volume 2 [...]
Investigating the Impact of Digital Transformation on the Labor Market in the Era of Changing Digital Transformation Dynamics in Saudi Arabia
Authors: Sarabdeen Masahina , Alofaysan Hind
Published: January 2023

In Saudi Arabia, limited studies have developed models related to measuring the impact of the digital economy on the labor market. This model concerns the agricultural, service, and industrial sectors in Saudi Arabia. This study further investigates the relationship between digitalization, labor productivity, and unemployment using the ARDL error correction method for time-series data obtained from the World Bank database for the period of 2001–2019. The findings of this study illustrate, digital variables such as fixed broadband subscriptions (LNFBS), mobile cellular subscriptions (LNMCS), and computer, communications, and other services (LNCCO) do not significantly affect the labor market in the agricultural sector. LNMCS and LNCCO do not influence the service sector. However, they are negatively influencing the industrial sector and labor productivity. In contrast, LNFBS has a positive impact on both the service and industrial sectors. Interestingly, all three digital variables significantly reduce unemployment in the long run in Saudi Arabia. However, in the short run, digitalization does not have a positive impact on the economy. This study hopes to benefit policymakers in considering how to reorganize the socioeconomic infrastructure to balance economic growth through greater technology and the utilization of the country’s human resources.
The Impact of Digital Financial Inclusion and Bank Competition on Bank Stability in Sub-Saharan Africa
Authors: Chinoda Tough , Kapingura Forget Mingiri
Published: January 2023

The last few years have witnessed a rapid development in digital finance that may threaten the manner in which traditional financial services are being used. It opens up new opportunities for low-income groups and small businesses that have limited or no access to formal financial services. Thus, digital financial inclusion plays a vital role in boosting a country’s financial inclusion, fulfilling some sustainable development goals and achieving higher economic growth. This study builds on a new measure of digital financial inclusion to examine the impact of digital financial inclusion and bank competition on bank stability in Sub-Saharan Africa for the period 2014 to 2020 using the two-step System Generalised Method of Moments. An index of digital financial inclusion, z-score, Herfindahl–Hirschman Index (HHI), and non-performing loans were used as data variables. The study findings reveal that digital financial inclusion has a significant positive relationship with bank stability (z-score) and a negative relationship with non-performing loans. The study also found a significant negative effect of bank competition (HHI) on bank stability in line with the competition-fragility view. Policymakers should ensure digital financial literacy for all since it feeds into bank stability and also reduces bank insolvency. They should also find ways of enhancing bank competition which reduces non-performing loans and bank insolvency. On practical implications, the study calls for strategic measures to preserve bank stability, such as complementing digital financial inclusion with financial literacy and enhancing bank competition.
Characteristics of Parental Digital Mediation: Predictors, Strategies, and Differences among Children Experiencing Various Parental Mediation Strategies
Authors: Rudnova Natalia , Kornienko Dmitry , Semenov Yuri , Egorov Vladimir
Published: January 2023

The process of digitalization has become an integral part of the social situation of a child’s growth in the modern world. Child development in the digital environment demands the involvement of adults as mediators. This practice is called parental digital mediation. Previous studies have identified the significant parental and environmental aspects of parental mediation, but there has been little information about the relationships between the children’s characteristics and parental digital mediation. The current study aims to fill this gap by identifying the behavioral (social network and screen time) and emotional (social network addiction and happiness) predictors of the two dimensions of digital mediation: parental support and parental control. The study also examines the differences among children influenced by various parental mediation strategies. A total of 4011 students (42% male and 58% female) ranging in age from 13 to 15 years (M = 14.07; SD = 0.76) took part in the study. The parental mediation of their children’s internet use, social media addiction, social network time, screen time, and happiness were measured. According to the results, both the behavioral and emotional characteristics of the children served as predictors of parental mediation. A small amount of time spent on social networks or screens and low social media addiction and happiness were identified as the predictors of parental support, whereas a large amount of time spent on social networks and screens and low social media addiction were identified as the predictors of parental control. Three groups of children experiencing different parental mediation strategies were determined. The children with parents who enabled mediation were happier than the others. Children under instructive mediation demonstrated the highest tendency to social media addiction. Children under selective mediation spent the most time (of all groups) on gadgets, but they showed a low tendency towards social media addiction.
Lecture Attendance among Undergraduate Business Students in Egypt: An Exploratory Study
Authors: Iparraguirre José-Louis , Antón-Sancho Álvaro , Vergara Diego
Published: January 2023

In Egypt’s higher education system, there are differences among universities about the compulsory nature of class attendance. In addition, the COVID-19 pandemic, which saw a transition of higher education activities to online environments, has led, after the return to face-to-face learning, to an update on the usefulness of face-to-face learning for higher education students. This work provides quantitative exploratory research on the assessment of university students in the areas of economics and business in Egypt about attendance to face-to-face lectures, its advantages and disadvantages, and the usefulness of implementing new learning methodologies within the lectures. As a result, it has been obtained that the participating students valued attendance as an important element of their learning, although they identified disadvantages in this regard. In addition, they supported the development of active and collaborative methodologies in lectures. It is proposed that this research should be extended to compare the results with those of other geographical areas, and it is suggested that universities increase the adoption of new learning methodologies through the adoption of measures, such as teacher training, in this regard.
Impact of Output Conductance on Current-Gain Cut-Off Frequency in InxGa1-xAs/In0.52Al0.48As Quantum-Well High-Electron-Mobility Transistors on InP Substrate
Authors: Kim Hyo-Jin , Lee In-Geun , Jo Hyeon-Bhin , Rho Tae-Beom , Tsutsumi Takuya , Sugiyama Hiroki , Matsuzaki Hideaki , Lee Jae-Hak , Kim Tae-Woo , Kim Dae-Hyun
Published: January 2023

In this study, we investigated the impact of intrinsic output conductance (goi) on the short-circuit current-gain cut-off frequency (fT) in InxGa1-xAs/In0.52Al0.48As quantum-well (QW) high-electron-mobility transistors. At its core, we attempted to extract values of fT using a simplified small-signal model (SSM) of the HEMTs and to derive an analytical formula for fT in terms of extrinsic model parameters that are related with intrinsic model parameters of a general SSM. We projected how fT was influenced by goi in HEMTs, emphasizing that the improvement in electrostatic integrity would also be of critical importance to fully benefit from scaling down Lg.
A Detailed Survey on Federated Learning Attacks and Defenses
Authors: Sikandar Hira Shahzadi , Waheed Huda , Tahir Sibgha , Malik Saif U. R. , Rafique Waqas
Published: January 2023

A traditional centralized method of training AI models has been put to the test by the emergence of data stores and public privacy concerns. To overcome these issues, the federated learning (FL) approach was introduced. FL employs a privacy-by-design architecture to train deep neural networks utilizing decentralized data, in which numerous devices collectively build any machine learning system that does not reveal users’ personal information under the supervision of a centralized server. While federated learning (FL), as a machine learning (ML) strategy, may be effective for safeguarding the confidentiality of local data, it is also vulnerable to attacks. Increased interest in the FL domain inspired us to write this paper, which informs readers of the numerous threats to and flaws in the federated learning strategy, and introduces a multiple-defense mechanism that can be employed to fend off threats.
Human Activity Recognition for the Identification of Bullying and Cyberbullying Using Smartphone Sensors
Authors: Gattulli Vincenzo , Impedovo Donato , Pirlo Giuseppe , Sarcinella Lucia
Published: January 2023

The smartphone is an excellent source of data; it is possible to extrapolate smartphone sensor values and, through Machine Learning approaches, perform anomaly detection analysis characterized by human behavior. This work exploits Human Activity Recognition (HAR) models and techniques to identify human activity performed while filling out a questionnaire via a smartphone application, which aims to classify users as Bullying, Cyberbullying, Victims of Bullying, and Victims of Cyberbullying. The purpose of the work is to discuss a new smartphone methodology that combines the final label elicited from the cyberbullying/bullying questionnaire (Bully, Cyberbully, Bullying Victim, and Cyberbullying Victim) and the human activity performed (Human Activity Recognition) while the individual fills out the questionnaire. The paper starts with a state-of-the-art analysis of HAR to arrive at the design of a model that could recognize everyday life actions and discriminate them from actions resulting from alleged bullying activities. Five activities were considered for recognition: Walking, Jumping, Sitting, Running and Falling. The best HAR activity identification model then is applied to the Dataset derived from the “Smartphone Questionnaire Application” experiment to perform the analysis previously described.
1/f Additive Phase Noise Analysis for One-Port Injection-Locked Oscillators
Authors: Suh Inwon , Roblin Patrick , Ko Youngseo
Published: January 2023

The 1/f additive phase noise of one-port injection-locked oscillators is experimentally characterized and analyzed using a simple analytic model based on the generalized 1/f Kurokawa theory. To experimentally verify the prediction of the simple analytic model proposed, two negative-conductance transmission line pHEMT oscillators operating at 2.4828 GHz and 2.485 GHz were designed and fabricated. A new configuration for integrating an additive phase noise measurement system with a large signal network analyzer (LSNA) is introduced to jointly acquire both the noise and RF waveforms of the one-port injection-locked oscillator. The Kurokawa derivatives needed for the analytic expression were experimentally obtained using the LSNA measurements and optimized to accurately model the corner frequency. A good agreement between the predicted and experimental results was obtained for both the injection-locked and free-running oscillators. In contrast to phase noise measurements of the free-running oscillator, which can only characterize the oscillator-upconverted 1/f3 noise, the additive phase noise characterization of the injection-locked oscillator is shown to provide the means to directly observe and characterize the input-referred intrinsic 1/f noise source of the oscillator negative resistance.
A Method for Calculating the Derivative of Activation Functions Based on Piecewise Linear Approximation
Authors: Liao Xuan , Zhou Tong , Zhang Longlong , Hu Xiang , Peng Yuanxi
Published: January 2023

Nonlinear functions are widely used as activation functions in artificial neural networks, which have a great impact on the fitting ability of artificial neural networks. Due to the complexity of the activation function, the computation of the activation function and its derivative requires a lot of computing resources and time during training. In order to improve the computational efficiency of the derivatives of the activation function in the back-propagation of artificial neural networks, this paper proposes a method based on piecewise linear approximation method to calculate the derivative of the activation function. This method is hardware-friendly and universal, it can efficiently compute various nonlinear activation functions in the field of neural network hardware accelerators. In this paper, we use least squares to improve a piecewise linear approximation calculation method that can control the absolute error and get less number of segments or smaller average error, which means fewer hardware resources are required. We use this method to perform a segmented linear approximation to the original or derivative function of the activation function. Both types of activation functions are substituted into a multilayer perceptron for binary classification experiments to verify the effectiveness of the proposed method. Experimental results show that the same or even slightly higher classification accuracy can be achieved by using this method, and the computation time of the back-propagation is reduced by 4–6% compared to the direct calculation of the derivative directly from the function expression using the operator encapsulated in PyTorch. This shows that the proposed method provides an efficient solution of nonlinear activation functions for hardware acceleration of neural networks.
D.O.T. PAQUITOP, an Autonomous Mobile Manipulator for Hospital Assistance
Authors: Tagliavini Luigi , Baglieri Lorenzo , Colucci Giovanni , Botta Andrea , Visconte Carmen , Quaglia Giuseppe
Published: January 2023

The use of robotic technologies for caregiving and assistance has become a very interesting research topic in the field of robotics. Towards this goal, the researchers at Politecnico di Torino are developing robotic solutions for indoor assistance. This paper presents the D.O.T. PAQUITOP project, which aims at developing a mobile robotic assistant for the hospital environment. The mobile robot is composed of a custom omnidirectional platform, named PAQUITOP, a commercial 6 dof robotic arm, sensors for monitoring vital signs in patients, and a tablet to interact with the patient. To prove the effectiveness of this solution, preliminary tests were conducted with success in the laboratories of Politecnico di Torino and, thanks to the collaboration with the Onlus Fondazione D.O.T. and the medical staff of Molinette Hospital in Turin (Italy), at the hematology ward of Molinette Hospital.
A Trust-Based Secure Neuro Fuzzy Clustering Technique for Mobile Ad Hoc Networks
Authors: Rajeswari Alagan Ramasamy , Lai Wen-Cheng , Kavitha C. , Balasubramanian Prabhu Kavin , Srividhya S. R.
Published: January 2023

A MANET consists of a group of mobile nodes. In a MANET, scalability and mobility have a greater influence on routing performance. The clustering technique plays a vital role in enhancing the routing mechanism and improving the network lifetime of a large-scale network like a MANET. The clustering process will degrade network performance if the malicious node is chosen as the Cluster Leader (CL). Thus, the secure clustering process in a MANET is a very challenging task. To overcome this problem, the following key factors like Trust Value (TV), Residual Energy Level (REL), and Mobility (M) of the node are used as decision-making parameters to elect a Cluster Leader (CL). In this work, we have proposed a soft computing-based neuro-fuzzy model, ANFIS-based Energy-Efficient Secure Clustering Model (ANFIS-EESC), with a primary objective of forming energy-aware stable trust-based clustering in a MANET. Moreover, we have proposed two working novel algorithms: Weight-Based Trust Estimation (WBTE) algorithm and the Fuzzy-Based Clustering (FBC) algorithm. The primary objective of the WBTE algorithm is to measure the trustworthiness of the nodes and to mitigate the malicious nodes. Fuzzy-Based Clustering (FBC) algorithm is a fuzzy logic-based cluster formation algorithm. In our proposed work, each non-CL in the system applies the cluster density of CL and mobility for each CL node using the Mamdani Fuzzy Inference system, and makes the decision to join as a member with a CL that holds maximum value. Simulation results show that the proposed work enhances the network performance by electing a more stable trust-aware and energy-aware node as Cluster leader (CL). We compare the performance parameters of the proposed work, such as packet delivery rate, energy consumption, detection rate, and reaffiliation, with the existing work, Weighted Clustering Algorithm (WCA). The network lifetime is 39% greater in the proposed ANFIS-EESC model than in the other existing work, WCA. Moreover, ANFIS-EESC shows an enhancement of 22% to 32% in packet delivery ratio and 32% and 39% in throughput. From the above analysis, it has been proved that the proposed work gives a better performance in terms of reliability and stability when compared to the existing work, WCA.
Research on High-Throughput Crop Root Phenotype 3D Reconstruction Using X-ray CT in 5G Era
Authors: Wang Jinpeng , Liu Haotian , Yao Qingxue , Gillbanks Jeremy , Zhao Xin
Published: January 2023

Currently, the three-dimensional detection of plant root structure is one of the core issues in studies on plant root phenotype. Manual measurement methods are not only cumbersome but also have poor reliability and damage the root. Among many solutions, X-ray computed tomography (X-ray CT) can help us observe the plant root structure in a three-dimensional and non-destructive form under the condition of underground soil in situ. Therefore, this paper proposes a high-throughput method and process for plant three-dimensional root phenotype and reconstruction based on X-ray CT technology. Firstly, this paper proposes a high-throughput transmission for the root phenotyping and utilizing the imaging technique to extract the root characteristics; then, the study adopts a moving cube algorithm to reconstruct the 3D (three-dimensional) root. Finally, this research simulates the proposed algorithm, and the simulation results show that the presented method in this paper works well.
Fermatean Fuzzy Programming with New Score Function: A New Methodology to Multi-Objective Transportation Problems
Authors: Sharma M. K. , Kamini  , Dhaka Arvind , Nandal Amita , Rosales Hamurabi Gamboa , Monteagudo Francisco Eneldo López , Hernández Alejandra García , Hoang Vinh Truong
Published: January 2023

The aim of this work is to establish a new methodology to tackle the multi-objective transportation problems [MOTP] in a Fermatean fuzzy environment that can deal with all the parameters that possess a conflicting nature. In our research work, we developed a new score function in the context of a fermatean nature for converting fuzzy data into crisp data with the help of the Fermatean fuzzy technique. Then, we introduced an algorithm-based methodology, i.e., the Fermatean Fuzzy Programming approach to tackle transportation problems with multi-objectives. The main purpose of this research work is to give an alternate fuzzy programming approach to handle the MOTP. To justify the potential and validity of our work, numerical computations have been carried out using our proposed methodology.
Does Banking Accessibility Matter in Assuring the Economic Growth in the Digitization Context? Evidence from Central and Eastern European Countries
Authors: Manta Alina Georgiana , Badareu Gabriela , Bădîrcea Roxana Maria , Doran Nicoleta Mihaela
Published: January 2023

The purpose of this paper is to investigate the nexus between financial (banking) accessibility and economic growth in the context of the digitization process. Thus, we built a panel model to evaluate the correlations between the banking accessibility and economic growth during 2010–2021 period for the Central and Eastern European Countries (CEEC). Furthermore, we applied the Fully Modified Ordinary Least Squares (FMOLS) method with eight independent variables measuring the degree of banking accessibility and the dependent variable for economic growth. The results show that improving financial accessibility positively influences economic growth and greater access to banking services does not necessarily stimulate economic growth. In the digitization context, the results are relevant for the policymakers outlining that investing more in digitization is important, but this does not necessarily help people to have more access to banking services because there is also a lack of will and financial education that restrain them from embracing the digital changes.
Multiple Microgrids: A Review of Architectures and Operation and Control Strategies
Authors: Saha Diptish , Bazmohammadi Najmeh , Vasquez Juan C. , Guerrero Josep M.
Published: January 2023

Several issues of individual microgrids (MGs) such as voltage and frequency fluctuations mainly due to the intermittent nature of renewable energy sources’ (RESs) power production can be mitigated by interconnecting multiple MGs and forming a multi-microgrid (MMG) system. MMG systems improve the reliability and resiliency of power systems, increase RESs’ utilization, and provide cost-efficient power to the consumers. This paper provides a comprehensive review of the conducted studies in the MMG area summarizing different operational goals and constraints proposed in the literature for efficient operation of MMGs. Besides, different MMG architectures in which the MGs can be interconnected to form an MMG system and their characteristics are discussed. This paper also provides a state-of-the-art review on different control strategies and operation management methodologies for the operation and control of MMGs in centralized, decentralized, distributed, and hierarchical structures. A classification of different sources of uncertainties in an MMG system and proposed uncertainty handling strategies are also presented. Finally, the paper is complemented with a discussion of the main open issues and future research directions of MMG systems.
Hybrid Weighted Least Square Multi-Verse Optimizer (WLS–MVO) Framework for Real-Time Estimation of Harmonics in Non-Linear Loads
Authors: Haseeb Abdul , Waleed Umar , Ashraf Muhammad Mansoor , Siddiq Faisal , Rafiq Muhammad , Shafique Muhammad
Published: January 2023

The electric power quality has become a serious concern for electric utilities and end users owing to its undesirable effects on system capabilities and performance. Harmonic levels on power systems have been pronounced to a greater extent with the continuous growth in the application of solid-state and reactive power compensatory devices. Harmonics are the key constituents that are mainly responsible for power quality deterioration. Power system harmonics need to be correctly estimated and filtered to increase power quality. This research work focuses on accurate estimation of power system harmonics with the proposed hybrid weighted least-square multi-verse optimizer (WLS–MVO) based framework. Multi-verse optimizer replicates the phenomenon of the formation of new universes as described by multi-verse theory to solve complex real-world optimization problems. The proposed WLS–MVO framework is tested and validated by estimating the harmonics present in multiple test signals with different noise levels. Amplitudes and phases of harmonics present in the polluted signal were estimated, and the framework computational time was compared with the previously developed technique’s results which are reported in the literature. There was 80% reduction in computational time and 82% improvement in terms of accuracy in estimating harmonics using WLS–MVO as compared to previously developed techniques. The performance of the developed framework is further validated by estimating the harmonics present in the real-time voltage and current waveforms obtained from axial flux permanent magnet generator (AFPMSG), uninterruptible power supply (UPS), and light-emitting diode (LED). The purposed technique technique outperforms the already-developed techniques, in terms of accuracy and computational time.
Energy Poverty and Low Carbon Energy Transition
Authors: Streimikiene Dalia , Kyriakopoulos Grigorios L.
Published: January 2023

In the recent two decades of recorded literature, energy poverty is increasingly understood as a multi-dimensional issue caused by the low-carbon energy transition. In this study, a literature review was performed, the outcome of which confirmed the contentious nature of energy poverty at the regional and international levels of analysis. Furthermore, the collected literature enabled the identification of those domains under which energy poverty is prevailing. The impacts of the current COVID-19 pandemic and the Russian-Ukrainian war on energy prices and energy poverty were also considered key issues of interest in recently published studies (published within the last five years). While all the collected studies in the literature review covered a wide geographical context worldwide, a comprehensive analysis of nurturing energy poverty sources and their consequences was primarily and foremost understood in the household sector, which was the research focus of this study, accordingly. Moreover, future research guidelines that should be drawn regarding energy poverty alleviation were also proposed.
A Survey on Hybrid SCADA/WAMS State Estimation Methodologies in Electric Power Transmission Systems
Authors: Darmis Orestis , Korres George
Published: January 2023

State estimation (SE) is an essential tool of energy management systems (EMS), providing power system operators with an overall grasp of the actual power system operating conditions and aiding them in sustaining reliable and secure operation of the grid. In modern transmission sectors, two main measurement systems are deployed, namely the supervisory control and data acquisition (SCADA) and the wide area monitoring systems (WAMS). The multiple advantages of augmenting conventional SCADA-based SE algorithms with synchrophasor measurements from WAMS are already well-established; thus, an abundance of different methodologies has been reported in the field of hybrid SE (HSE). Under this premise, this paper provides a thorough literature review of novel HSE methods in transmission systems and proposes a classification based on the scope and mathematical modeling of each method. Following a brief introduction to the concept of SE based on WAMS and SCADA measurements, an insight into the main challenges emerging in HSE implementations is provided. Various HSE methods which overcome these challenges are reviewed, for both static and dynamic SE implementations. In conclusion, the research trends in the area of HSE are summarized, and the main findings of this literature review are discussed.
Discussion on the Suitability of SCADA-Based Condition Monitoring for Wind Turbine Fault Diagnosis through Temperature Data Analysis
Authors: Murgia Alessandro , Verbeke Robbert , Tsiporkova Elena , Terzi Ludovico , Astolfi Davide
Published: January 2023

Wind turbines are expected to provide on the order of 50% of the electricity worldwide in the near future, and it is therefore fundamental to reduce the costs associated with this form of energy conversion, which regard maintenance as the first item of expenditure. SCADA-based condition monitoring for anomaly detection is commonly presented as a convenient solution for fault diagnosis on turbine components. However, its suitability is generally proven by empirical analyses which are limited in time and based on a circumscribed number of turbines. To cope with this lack of validation, this paper performs a controlled experiment to evaluate the suitability of SCADA-based condition monitoring for fault diagnosis in a fleet of eight turbines monitored for over 11 years. For the controlled experiment, a weakly supervised method was used to model the normal behavior of the turbine component. Such a model is instantiated as a convolutional neural network. The method, instantiated as a threshold-based method, proved to be suitable for diagnosis, i.e. the identification of all drivetrain failures with a considerable advance time. On the other hand, the wide variability between the time the alarm is raised and the fault is observed suggests its limited suitability for prognosis.
A Resilient Prosumer Model for Microgrid Communities with High PV Penetration
Authors: Mumbere Kihembo Samuel , Sasaki Yutaka , Yorino Naoto , Zoka Yoshifumi , Tanioka Yoshiki , Bedawy Ahmed
Published: January 2023

Worldwide energy shortages and the green energy revolution have triggered an increase in the penetration of standalone microgrids. However, they have limited generation capacity and are wasteful when excess generated energy is curtailed. This presents an opportunity for the coordinated operation of multiple prosumer microgrids that absorb this waste to enhance their resiliency and reliability. This paper proposes a reliable prosumer model with an inbuilt energy management system (EMS) simulator that considers the mentioned deficiencies for constructing resilient interconnected prosumer microgrids. The EMS simulator operates in a real-time dynamic environment to coordinate the prosumer components and performs flexible switching for (1) prioritizing critical load by shedding the non-critical load and (2) meeting load demand locally or from other interconnected prosumers. The EMS simulator maintains energy balance by setting limits for the battery energy storage system (BESS) to preserve energy during low generation and performs real-time monitoring. The novelty of this model lies in its simplicity and flexibility, which allows interconnected prosumer microgrids to operate in cooperation without the need for communication. The proposed model is evaluated in a post-disaster off-grid scenario using a single-phase average value model that considers reasonable computation time. The simulation results of the proposed system indicate the preservation of stored energy while maintaining critical resources beyond three days of poor weather conditions.
A Reconfiguration Circuit to Boost the Output Power of a Partially Shaded PV String
Authors: Murtaza Ali Faisal , Sher Hadeed Ahmed
Published: January 2023

An optical isolator circuit is developed to detect and dynamically relocate the photovoltaic (PV) module under partial shading. The suggested system control structure operates in two modes. Mode 1 governs the system at global maxima (GM) by tracing the power-voltage (PV) curve. Mode 2 detects and separates all the bypassed modules from a PV string/array by means of a decentralized control and stores its power in the battery. Simulations are performed on different shading patterns to verify the efficacy of the suggested system. The results showcase that the averaged harnessed power using the proposed circuit is 25.26% more than the total cross-tied (TCT) and series-parallel (SP) array configurations. The proposed circuit does not require complex gate driver circuits and large switch counts. The circuit is scalable and can be implemented on an “N × N” array.
Age Estimation of a Hybrid Energy Storage System for Vehicular Start–Stop
Authors: Manla Emad , Nasiri Adel
Published: January 2023

Ultracapacitors are energy storage devices that have shown outstanding capability in a vast spectrum of applications, mainly in energy storage systems required to deliver short bursts of electrical energy. Ultracapacitors possess high power density while batteries possess high energy density. In this paper, a hybrid energy storage device comprising a lithium-ion ultracapacitor module and a lead acid battery was modeled, built, and tested for vehicular start–stop application, which requires a much larger number of engine cranking events than conventional vehicles. The combination of a lead acid battery with Li-ion ultracapacitors was chosen due to the fact that the vast majority of vehicles utilize lead acid batteries to crank the internal combustion engine. This allows retrofitting this hybrid setup in conventional vehicles along with the start–stop feature without inflicting damage to the already installed lead acid battery. The start–stop feature puts high stress on the lead acid battery, contributing to its faster aging. This feature is commonly found in hybrid vehicles to save the unnecessarily burned fuel during idling. This paper discusses aging of the lead acid battery as a result of being used in hybrid vehicles equipped with start–stop when used alone versus when used in the hybrid setup. The paper shows cranking tests performed on a number of cars to obtain voltage, current, power, and energy requirements for combustion engine cranking. Mathematical derivation, analysis, and an energy storage age estimation method are also presented. A set of cranking events followed by capacity checks performed on two automobile energy storage systems, one being a lead acid battery alone and the other being the proposed hybrid module, show the advantage of integrating the ultracapacitor module with the lead acid battery to extend its life span almost fivefold in a hybrid automobile.
Voltage Sag Mitigation Effect Considering Failure Probability According to the Types of SFCL
Authors: Shin Joong-Woo , Youn Young-Woo , Kim Jin-Seok
Published: January 2023

The development of industrial technology is based on electronic devices that are sensitive to power quality. Thus, the demand for high-quality and reliable power supplies is increasing. Voltage sag results in severe problems in the manufacturing process of power quality-sensitive industrial loads. When a fault occurs in a multi-ground power distribution system, the magnitudes of the fault current and voltage sag in the faulted and nonfaulted feeders become high. Hence, installing a superconducting fault current limiter (SFCL) is an effective method of compensating for fault current limitation and voltage sag. This study evaluates the effects of improving the magnitude, duration, and frequency of the voltage sag according to the type of SFCL used. First, a fault in the power distribution system is analyzed using PSCAD/EMTDC, a power system simulation software, according to the fault current-limiting element (CLE) and the type of SFCL. Second, the expected voltage sag frequency caused by a feeder fault in the power distribution system is assessed. Finally, the voltage sag improvement effect according to the CLE and the type of SFCL are compared. The trigger-type SFCL with a resistor as a CLE has been evaluated and found to be effective in improving voltage sag.
Poly(ether ether ketone)-Induced Surface Modification of Polyethylene Separators for Li-Ion Batteries
Authors: Kim Yunjung , Jang Yong-Jin , Seo Hyungeun , Lee Je-Nam , Woo Sang-Gil , Kim Jae-Hun
Published: January 2023

With the global effort to reduce fossil fuels and to use eco-friendly energy, interest in Li-ion batteries (LIBs) is rapidly increasing. In the LIB system, the separator is an important component for determining the rate performance and safety of cells. Although polyolefin separators are commercially used in LIBs, they still suffer from inferior electrolyte wettability and low thermal stability issues. Here, we introduce a chemical surface modification for polyethylene (PE) separators using a poly(ether ether ketone) (PEEK) coating. The separators were pretreated in a tannic acid solution to enforce the adhesion of the coated layers. Then, PEEK was coated onto the PE surface by a doctor blading method. The separators were examined by infrared spectroscopy, and the surface properties were characterized by electrolyte uptake and contact angle measurements. The treated surface was hydrophilic, and the ionic conductivity of the cell with the modified separator was significantly improved. As a result, the corresponding rate performance was significantly improved. The surface modification strategy proposed here can be applied to polyolefin-based separators as well.
A Comprehensive Review of Electric Vehicles in Energy Systems: Integration with Renewable Energy Sources, Charging Levels, Different Types, and Standards
Authors: Taghizad-Tavana Kamran , Alizadeh As’ad , Ghanbari-Ghalehjoughi Mohsen , Nojavan Sayyad
Published: January 2023

Due to the rapid expansion of electric vehicles (EVs), they are expected to be one of the main contributors to transportation. The increasing use of fossil fuels as one of the most available energy sources has led to the emission of greenhouse gases, which will play a vital role in achieving a sustainable transportation system. Developed and developing countries have long-term plans and policies to use EVs instead of internal combustion vehicles and to use renewable energy to generate electricity, which increases the number of charging stations. Recently, to meet the charging demand for EVs, the main focus of researchers has been on smart charging solutions. In addition, maintaining power quality and peak demand for grids has become very difficult due to the widespread deployment of EVs as personal and commercial vehicles. This paper provides information on EV charging control that can be used to improve the design and implementation of charging station infrastructure. An in-depth analysis of EV types, global charging standards, and the architectures of AC-DC and DC-DC converters are covered in this review article. In addition, investigating the role of EV collectors, as well as EV penetration, in electric energy systems to facilitate the integration of electric energy systems with renewable energy sources is one of the main goals of this paper.
A Review of Denial of Service Attack and Mitigation in the Smart Grid Using Reinforcement Learning
Authors: Ortega-Fernandez Ines , Liberati Francesco
Published: January 2023

The smart grid merges cyber-physical systems (CPS) infrastructure with information and communication technologies (ICT) to ensure efficient power generation, smart energy distribution in real-time, and optimisation, and it is rapidly becoming the current standard for energy generation and distribution. However, the use of ICT has increased the attack surface against the electricity grid, which is vulnerable to a wider range of cyberattacks. In particular, Denial-of-Service (DoS) attacks might impact both the communication network and the cyber-physical layer. DoS attacks have become critical threats against the smart grid due to their ability to impact the normal operation of legitimate smart-grid devices and their ability to target different smart grid systems and applications. This paper presents a comprehensive and methodical discussion of DoS attacks in the smart grid, analysing the most common attack vectors and their effect on the smart grid. The paper also presents a survey of detection and mitigation techniques against DoS attacks in the smart grid using reinforcement learning (RL) algorithms, analysing the strengths and limitations of the current approaches and identifying the prospects for future research.
Maceral Control on the Hydrocarbon Generation Potential of Lacustrine Shales: A Case Study of the Chang 7 Member of the Triassic Yanchang Formation, Ordos Basin, North China
Authors: Liu Bei , Teng Juan , Mastalerz Maria
Published: January 2023

Organic matter (OM) type critically controls the hydrocarbon generation potential and organic pore development in black shales. However, maceral variation in lacustrine shales and its control on hydrocarbon generation potential and organic pore development are not yet well understood. In this study, 15 Chang 7 Member shale samples of the Yanchang Formation, Ordos Basin, were investigated with organic petrography, Rock-Eval pyrolysis, and a scanning electron microscope to study the maceral composition, hydrocarbon generation potential, and organic pores in this black shale succession. The results show that the studied shales are in the oil window (Ro~0.70%). OM belongs to Type I and Type III kerogen, as demonstrated by Rock-Eval pyrolysis. Macerals in the Chang 7 Member shales are composed of amorphous OM, alginite, sporinite, liptodetrinite, vitrinite, inertinite, and solid bitumen. Amorphous OM and alginite are major hydrocarbon-generating macerals, and their content determines the hydrocarbon potential of shales. Secondary organic pores were not observed in the studied Chang 7 Member shales due to either a low thermal maturity or a dominance of terrigenous OM. Maceral variation can affect the reliability of using Rock-Eval Tmax as a thermal maturity indicator. This study provides important insights into maceral control on hydrocarbon generation and organic pore development in black shales, calling for a critical evaluation of OM in black shale successions with organic petrography.
High-Order Compensation Topology Integration for High-Tolerant Wireless Power Transfer
Authors: Yuan Zhaoyang , Yang Qingxin , Zhang Xian , Ma Xianjie , Chen Zhixin , Xue Ming , Zhang Pengcheng
Published: January 2023

Wireless power transfer (WPT) has been a promising way to transfer power wirelessly over certain distances through the mutual inductance (MI) of the magnetically coupled transmitter and receiver coils, providing significant benefits of convenience, safety, and feasibility to special occasions. The stable output and efficiency cannot be maintained due to the load variation and the inevitable misalignment between the magnetic couplers. High-order compensation topologies that are highly flexible in design due to more compensation elements are essential for the WPT to suppress the load variation and misalignment effects. However, due to core loss and thermal management, high-power-level and high-frequency inductor design have always been challenging for WPT systems. Space occupation and cost are other aspects to be considered for inductor design. Thus integrating these additional bulky inductors into the main coils has been a critical trial. As a result, the compensation topologies’ original input and output profiles will change or even disappear. This paper reviews the existing high-order compensation topologies and their integration principles and implementation for the WPT to obtain high misalignment tolerance. The design objectives and challenges of the integrated compensation topology in terms of misalignment tolerance capability are discussed. The relevant control systems to cope with coil misalignment and load variations are investigated. Challenges and future development of the high-tolerant WPT are discussed.
A Comprehensive Review on Techno-Economic Analysis and Optimal Sizing of Hybrid Renewable Energy Sources with Energy Storage Systems
Authors: Agajie Takele Ferede , Ali Ahmed , Fopah-Lele Armand , Amoussou Isaac , Khan Baseem , Velasco Carmen Lilí Rodríguez , Tanyi Emmanuel
Published: January 2023

Renewable energy solutions are appropriate for on-grid and off-grid applications, acting as a supporter for the utility network or rural locations without the need to develop or extend costly and difficult grid infrastructure. As a result, hybrid renewable energy sources have become a popular option for grid-connected or standalone systems. This paper examines hybrid renewable energy power production systems with a focus on energy sustainability, reliability due to irregularities, techno-economic feasibility, and being environmentally friendly. In attaining a reliable, clean, and cost-effective system, sizing optimal hybrid renewable energy sources (HRES) is a crucial challenge. The presenters went further to outline the best sizing approach that can be used in HRES, taking into consideration the key components, parameters, methods, and data. Moreover, the goal functions, constraints from design, system components, optimization software tools, and meta-heuristic algorithm methodologies were highlighted for the available studies in this timely synopsis of the state of the art. Additionally, current issues resulting from scaling HRES were also identified and discussed. The latest trends and advances in planning problems were thoroughly addressed. Finally, this paper provides suggestions for further research into the appropriate component sizing in HRES.
Advancements of Biochar-Based Catalyst for Improved Production of Biodiesel: A Comprehensive Review
Authors: Kumar Sooraj , Soomro Suhail Ahmed , Harijan Khanji , Uqaili Mohammad Aslam , Kumar Laveet
Published: January 2023

Despite being a limited and scarce resource, the necessity and exploitation of fossil fuels are unstoppable in serving human demands. In order to supply energy demand without causing environmental damage, it is crucial to utilize a variety of renewable feedstock resources. Biochar, made up mostly of carbon, oxygen, and hydrogen, is the product of the thermochemical processes of pyrolysis, hydrothermal carbonization, torrefaction, and hydrothermal liquefaction. Biochar, once activated, has the potential to act as a catalyst in a variety of energy generation processes, including transesterification and fermentation. Transesterification is the process that is used to produce biodiesel from a variety of oils, both edible and non-edible, as well as animal fats in the presence of either a homogeneous or a heterogeneous catalyst. When selecting a catalyst, the amount of free fatty acid (FFA) content in the oil is considered. Homogeneous catalysts are superior to heterogeneous catalysts because they are unaffected by the concentration of free fatty acids in the oil. Homogeneous catalysts are extremely hazardous, as they are poisonous, combustible, and corrosive. In addition, the production of soaps as a byproduct and a large volume of wastewater from the use of homogeneous catalysts necessitates additional pretreatment procedures and costs for adequate disposal. This article examines the biochar-based fuel-generation catalyst in detail. At first, a wide variety of thermochemical methods were provided for manufacturing biochar and its production. Biochar’s chemical nature was analyzed, and the case for using it as a catalyst in the production of biofuels was also scrutinized. An explanation of how the biochar catalyst can improve fuel synthesis is provided for readers. Biodiesel’s transesterification and esterification processes, biomass hydrolysis, and biohydrogen generation with the help of a biochar catalyst are all reviewed in detail.