Electrical Circuit Research Articles

Predicting power and solar energy using neural networks and PCA with meteorological parameters from Diass and Taïba Ndiaye

The excessive reliance on conventional fossil fuel-based resources poses a significant threat to our environment. To mitigate this impact, it has become increasingly crucial to increase the integration of intermittent and non-polluting energy sources into our electrical grids. However, while this higher penetration rate brings benefits such as improved producer satisfaction and reduced fossil fuel consumption, it also presents challenges for traditional non-smart electrical networks. To promote intermittent energy sources effectively and maintain a balance between consumption and production, accurate forecasting of these energy outputs plays a vital role. This research paper focuses on studying the application of artificial neural networks for predicting the power and energy output of the Diass solar power plant in the short and medium term. The proposed approach utilizes not only the meteorological data from the city where the power plant is located but also data from a nearby city with a data acquisition station. Principal component analysis (PCA) is employed to select the relevant variables for the prediction model. Furthermore, the results obtained from our approach are compared to existing literature that solely uses meteorological data from the power plant's location. The comparison shows that our method achieves more satisfactory results, with mean absolute errors and root mean square errors of 0.0223 KWh and 0.003 KWh, respectively, and a prediction accuracy of 94.57% in terms of energy and power. It is worth noting that the computational resource requirements for our approach are higher, with simulation times ranging between 1788 seconds and 2201 seconds. By utilizing a broader range of data sources and employing advanced techniques like artificial neural networks, this research contributes to improving the accuracy of solar power generation forecasts. The findings highlight the potential of incorporating additional data inputs and advanced modeling techniques to enhance the performance of renewable energy systems, paving the way for a more sustainable and efficient energy future.

Robust Design of Electrical System for Nuclear Plants to Prevent a Nuclear Accident During an Emergency Situation

The Chernobyl accident taught us an important lesson regarding the significance of the emergency diesel generator (EDG), which is crucial for supplying a nuclear facility with emergency alternating-current power. A worst-case scenario would occur if the EDG failed to start functioning. In response to this problem, this research addresses the issue and suggests an optimal design for another alternative electrical source using solar energy. Until now, employing this technology presented a challenge as a solar energy system generates electrical harmonics that are transmitted from the photovoltaic (PV) grid to the electrical network. These harmonics can negatively impact the performance and operation of nuclear facilities. Consequently, this study proposes a comprehensive investigation that tackles this issue by implementing a LCL filter to mitigate the harmonics in the PV network. This paper not only provides an alternative solution in the event of a diesel generator breakdown, but also studies the effect of this solution on the station’s performance and how to improve it. A mathematical model based on the MATLAB program is developed to simulate the application of the LCL filter strategy. The proposed technique is tested through simulation with an actual case, demonstrating its reliability and high-quality outcomes.

Sustaining Situational Assessment in Electrical Network Power Control

Objective The aim of this study was to examine contributions to sustained situational assessment over an extended period in the context of electricity transmission control. Background The electricity industry is engaged in a period of unprecedented change in the transition to renewable sources of energy. Changes in the nature and function of electricity transmission risks a reduction in situational assessment as network controllers place increased reliance on advanced technology to identify and diagnose changes in the system state. Method Transmission network controllers from three organisations completed an assessment of their situational assessment on two occasions, one year apart. Results Multiple regression revealed a statistically significant model in which the variance in Year 2 was predicted by a combination of performance in Year 1, the recency of formal training, and the extent to which controllers perceived their job as exciting. No relationship was evident for years of experience as a network controller. Conclusion The results suggest that a combination of recent formal training and perceptions of job excitement may have implications in maintaining the capacity for situational assessment over an extended period in the context of electricity network control. Application The outcomes of the present study suggest that changes in situational assessment can be monitored and that strategies, including formal training and job design, may sustain situational assessment over an extended period in advanced technology settings.

Optimizing Network Insights: AI-Driven Approaches to Circulant Graph Based on Laplacian Spectra

Abstract Exploring the applications of Laplacian and signless Laplacian spectra extends beyond theoretical chemistry, computer science, electrical networks, and complex networks. These spectra, with their relevance, provide valuable insights into the structures of real-world networks and facilitate the prediction of their structural properties. The focal point of the study lies in the spectrum-based analysis of circulant graphs. From these analyses, crucial network measures such as mean-first passage time, average path length, spanning trees, and spectral radius are derived. This research enriches our comprehension of the interplay between graph spectra and network characteristics, offering a holistic understanding of complex networks. Consequently, it contributes to the ability to make predictions and conduct analyses across diverse scientific disciplines.

Virtual Reality in the Classroom: Transforming the Teaching of Electrical Circuits in the Digital Age

In response to the digital transformation in education, this study explores the efficacy of virtual reality (VR) video games in teaching direct current electrical circuits at a public university in Colombia. Using a mixed-method action research approach, this study aimed to design, implement, and evaluate a VR-based educational strategy to enhance undergraduate learning experiences. The methodology integrated VR into the curriculum, facilitating a comparison of this innovative approach with traditional teaching methods. The results indicate that the VR strategy significantly improved students’ comprehension of electrical circuits and increased engagement, demonstrating the utility of immersive technologies in educational settings. Challenges such as the need for technological integration and curriculum adaptation were also identified. This study concludes that VR video games can effectively augment electrical engineering education, offering a model for incorporating advanced digital tools into higher education curricula. This approach aligns with ongoing trends in digital transformation, suggesting significant potential for broad applications across various educational contexts.

Thermal-electrical analogy for simulations of superconducting power cables

Due the integration of superconducting technologies into electrical networks around the world, its precise simulations in power grids are increasingly becoming a desirable outcome. Over the years, sophisticated methods have been used to model superconducting power cables and, in this way, predict its behavior under different conditions. Most of the available models, however, are not advisable to be used and embedded in power system simulators. In this manuscript, we focus on the development of a method specifically for modeling superconducting cables in traditional power grid simulators. We start developing the model through a case example, within the basic concepts are introduced and later expanded to general cases. The model also incorporates the transient behavior of the cooling media, which is mandatory for such cables. It has been observed that the proposed model requires less computational effort and is able to deliver accurate results when compared to more advanced methods.

Earthquake Precursors: The Physics, Identification, and Application

The paper presents the author’s vision of the problem of earthquake hazards from the physical point of view. The first part is concerned with the processes of precursor’s generation. These processes are a part of the complex system of the lithosphere–atmosphere–ionosphere–magnetosphere coupling, which is characteristic of many other natural phenomena, where air ionization, atmospheric thermodynamic instability, and the Global Electric Circuit are involved in the processes of the geosphere’s interaction. The second part of the paper is concentrated on the reliable precursor’s identification. The specific features helping to identify precursors are separated into two groups: the absolute signatures such as the precursor’s locality or equatorial anomaly crests generation in conditions of absence of natural east-directed electric field and the conditional signatures due to the physical uniqueness mechanism of their generation, or necessity of the presence of additional precursors as multiple consequences of air ionization demonstrating the precursor’s synergy. The last part of the paper is devoted to the possible practical applications of the described precursors for purposes of the short-term earthquake forecast. A change in the paradigm of the earthquake forecast is proposed. The problem should be placed into the same category as weather forecasting or space weather forecasting.

Assessment and Level Modelling in Fundamentals of Electrical Engineering

This paper focuses on the module “Fundamentals of Electrical Engineering,” in which students from different engineering disciplines often face difficulties. Despite efforts to enhance the course through digital media, the formation of study groups, and adjusted lecture and exercise materials, there is still a high failure rate in the subject, leading to potential student dropouts. The primary goal is to analyze students’ challenges in solving electrical engineering problems to evaluate their grasp of the fundamentals of electrical engineering and identify varying levels of competence. The findings are based on a cross-sectional study conducted at the conclusion of a university course in Germany, involving 196 students. Through item response theory (IRT) analyses, it was determined that the assessment items demonstrated satisfactory fit values. The proficiency model delineates four levels, with only 8.2% of students achieving the highest level. At this stage, students can tackle more intricate problems using circuit analysis techniques. However, a notable portion of students (40.3%) lack a basic understanding of electrical circuits, placing them at the lowest level.

Impact of Fraxinus snag fall on electric distribution and infrastructure stability: An empirical analysis

With increasing climate variability and the movement of exotic pests and diseases, the rate of forest mortality has become an issue of global concern. Emerald Ash Borer (EAB), as one such pest, is causing the mass mortality of ash trees, Fraxinus spp., thus leading to an ongoing surge in the number of snags across North America. Snags are dead-standing trees that pose an extant threat to nearby infrastructure and buildings. In this article, we evaluate the impacts which snags pose to electrical distribution infrastructure. New Jersey, a state with a high degree of urbanization, has an extensive electric grid located in forested areas. New Jersey is currently in the process of upgrading the electric distribution network, which will increase the height of electric distribution lines to increase resiliency and potential capacity. This article demonstrates a yearly risk assessment methodology for Fraxinus snags using an integrated GIS, differential equation, and applied regression model framework under two distribution network parameterizations. The framework is applied to three northern New Jersey counties (Warren, Sussex, and Morris), which are managed by one utility, New Jersey Central Power and Light, and which are home to most of New Jersey’s Fraxinus trees.

Towards Automated Model Selection for Wind Speed and Solar Irradiance Forecasting

Given the recent increase in demand for electricity, it is necessary for renewable energy sources (RESs) to be widely integrated into power networks, with the two most commonly adopted alternatives being solar and wind power. Nonetheless, there is a significant amount of variation in wind speed and solar irradiance, on both a seasonal and a daily basis, an issue that, in turn, causes a large degree of variation in the amount of solar and wind energy produced. Therefore, RES technology integration into electricity networks is challenging. Accurate forecasting of solar irradiance and wind speed is crucial for the efficient operation of renewable energy power plants, guaranteeing the electricity supply at the most competitive price and preserving the dependability and security of electrical networks. In this research, a variety of different models were evaluated to predict medium-term (24 h ahead) wind speed and solar irradiance based on real-time measurement data relevant to the island of Crete, Greece. Illustrating several preprocessing steps and exploring a collection of “classical” and deep learning algorithms, this analysis highlights their conceptual design and rationale as time series predictors. Concluding the analysis, it discusses the importance of the “features” (intended as “time steps”), showing how it is possible to pinpoint the specific time of the day that most influences the forecast. Aside from producing the most accurate model for the case under examination, the necessity of performing extensive model searches in similar studies is highlighted by the current work.

The superiority of innovative spiral-interdigital microelectrode pattern in increasing the sensitivity of tracing synchronization via serum starvation in cellular metabolism

In order to investigate the changes in the properties of the cell culture solution in the effect of cell synchronization via cell starvation (for 12, 24, and 36 h), a new spiral-interdigital pattern of microelectrode as a biosensor has been proposed. Then, to test its superiority, the results of this spiral-interdigital pattern with the results of the commercial pattern have been compared. The cells were selected from breast cancer standard lines (MDA-MB-231). Changes in CV peaks of the secretions were recorded by the spiral-interdigital pattern, in which increasing the interactive surface with homogenous electric paths had been considered by simulation before fabrication. The results of the simulation and experimental procedures showed a meaningful correlation. The occurrence of CV oxidative peaks at about 0.1–0.4 V and reductive peaks at approximately 0 V in the spiral-interdigital biosensor in the starved MDA-MB-231 cell line has been observed. The starvation situation resembles one that does not cause meaningful cell apoptosis or necrosis, and this method is only used to make the cells synchronized. Also, no peak is observed in normal cell growth conditions. In addition, by using the commercial design of the electrodes, no peak is observed in any of the conditions of normal and synchronized growth of the cells. Therefore, it seems that the observed peaks are caused by the agents that are secreted in the cell culture solution in a synchronized situation. Moreover, the design of the new spiral-interdigital electrode can significantly increase the sensitivity of the sensor to receive these peaks due to more space and a uniform electric field.

Causes of accidents in electrical distribution networks (using the example of the branch of PJSC Rossetti Volga – Saratov Distribution Networks)

The article is a continuation of a series of studies dedicated to the analysis of power transmission through distribution electric networks of PJSC ROSSETI. The presented material analyzes the functioning of the electrical networks of the branch of PJSC Rosseti Volga – Saratov Distribution Networks. An analytical assessment of the electric energy transport through distribution electric networks was carried out for the period 2018–2022. The structure of the company is considered, the structural characteristics of the main elements of the studied electrical networks are given, and the number of emergencies that occurred during the study period is estimated. A quantitative assessment of the magnitude of the electric energy undersupply caused by power supply interruptions is given. The classification of failures according to the degree of the intensity of undersupply was carried out and a quantitative assessment of each group of failures according to their intensity was made. The influence of the seasonal component on the number of emergencies during the study period is considered. Based on the data from 2022–2023, the analysis of the main causes of damage to the elements of electrical networks was carried out. The classification of failures by groups of failure causes is made, their main characteristics for this period are considered. The percentage ratio of the number of failures number for the most characteristic reasons to the total number of outages during the study period has been established. The information published in the open press was used as the source data. General scientific methods as well as numerical methods of analysis were used in the research. MATLAB graphics editor technologies were used to visualize the obtained analysis results. The results obtained may be of interest to the managers of power grid companies, as well as researchers and engineers engaged in research in the field of reliability of power supply.

Leveraging Virtual Reality for the Visualization of Non-Observable Electrical Circuit Principles in Engineering Education

Leveraging Virtual Reality for the Visualization of Non-Observable Electrical Circuit Principles in Engineering Education

Beam coupling impedance of the main extraction kickers in the CERN PS

In view of the High Luminosity (HL) upgrade of the LHC, the beam intensity must be doubled in the injector chain. To perform reliable beam dynamics simulations, the beam coupling impedance in the injectors, such as the Proton Synchrotron (PS), must be followed closely by including all contributing elements into the impedance model. The existing kicker magnets of the PS had been optimized for large kick strength and short rise/fall times, but not necessarily to minimise beam coupling impedance. Hence, unwanted beam induced voltage can build up in their electrical circuits, with an impact on the beam. The beam coupling impedances of the two main kicker magnets used for the fast extraction from PS, the KFA71 and KFA79, are extensively characterized in this study. In particular, electromagnetic simulation results for the longitudinal and transverse coupling impedance are shown. The critical impedance contributions are identified, and their effect on beam stability with a possible mitigation solution is discussed. Moreover, the impact of the cable terminations on the electromagnetic field pattern and possible mitigation techniques are presented, providing a complete impedance evaluation of the entire kicker installation.

Trends of Asset Management Techniques for Electric Power Network Equipment

Trends of Asset Management Techniques for Electric Power Network Equipment

Linear Algebraic Nodal Analysis: An Applied Project for a First Course in Linear Algebra

Many students who enroll in a first course in linear algebra major in STEM disciplines other than mathematics. Teachers who serve such students may find it difficult to provide authentic problems from these broader areas that ignite students' interest in linear algebra. In this paper, we highlight an interdisciplinary learning activity that engages students in using linear systems of equations to model the behavior of practical electric circuits. This exercise fits nicely into standard introductory linear algebra curricula and is designed to excite students majoring in engineering, physics, or applied mathematics. We also include references to a collection of open-access resources to support instructors who want to use this material in project-based, flipped-learning, inquiry-oriented, or independent-study environments.

Automated gas-controlled cooker system design and implementation

Cooking from ancient times has evolved from using open fires to wood, gas cookers, using liquefied petroleum gas (LPG). This has also come with various adverse effects ranging from gas leakages to burnt food due to absent-mindedness, thereby creating a significant disaster that could lead to loss of life and property damage. The study aimed to reduce the rate of liquefied petroleum gas related accidents in domestic usage and improve the safety of domestic gas users. An automated method to enforce safety was proposed to avoid unwanted cooking gas flow consequences, especially in homes. The paper presents a control system using an Arduino Uno with a control design interfaced with a utensil sensor, solenoid valve, and a timer circuit to allow gas flow to commence and ignite a flame automatically. The automatic ignition apparatus, which has a high-voltage electric circuit, begins to function once the utensil detector comes in contact with silverware. The system is designed to function in different modes to ensure safety and prevent gas flow. The prototype serves as a means of curbing gas wastage and increasing the safety of people who use LPG as a source of fuel for cooking.

Advanced control of double stage grid-tied three phase photovoltaic systems with shunt active power filter

This paper explores the challenges associated with the control of a two-stage three-phase electrical grid connected to a photovoltaic (PV) system. The objectives encompass: i) maximizing the available PV power, ii) controlling the DC-link voltage to a predetermined setpoint, and iii) considering that power quality has become an important measure in a distribution electrical network where different loads are connected, the third objective will mainly focus on ensuring power factor correction (PFC). To achieve these objectives, two loops of nonlinear controller are developed. In the outer loop, the duty cycle of a boost converter is controlled using a hybrid technique of backstepping technique and the perturb & observe (P&O) algorithm. In addition, the inner loop employs a hybrid automaton approach to tackle the challenges of a three-phase shunt active power filter (SAPF). The results have been verified through numerical simulation using MATLAB/Simulink power systems environment.

High Frequency Electrochemical Transmission Spectroscopy Application to Bulk Conducting Analytes in Aqueous Solution

This work illustrates a novel technique, high-frequency transmission spectroscopy (HFTS), for the characterization of analyte in aqueous solution. The application of this technique to material characterization is similar traditional impedance spectroscopy (IS) but differs primarily in that HFTS is a measure of transmitted potential through the material (voltage out versus voltage in) rather than its impedance (current out versus voltage in). The material properties explored by HFTS are not limited to effects occurring at the electrode/analyte interface which dominate IS measurements. Additionally, electric network analyzers (ENA), used for the characterization of frequency response, provide spectrum measurement capability over a much higher frequency range than typical impedance instrumentation. In this work, the capability of HFTS is demonstrated using three test cases: electrolyte solutions, carbon nanoparticles in solution, and sulfate latex microparticles in aqueous suspension. The experimental setup consists of a 3D printed liquid test cell, custom design patch antennae, and an off-the shelf ENA with a frequency range of 300 kHz to 500 MHz. The magnitude response of these analytes at various concentrations demonstrated a sensitivity of the measurement on the order of 10 µM. Furthermore, the system shows the ability to distinguish between monovalent and divalent ions and detect changes in radii on the order of 10 pm to 1 µm. Techniques demonstrated in this work have a wide range of potential applications including environmental monitoring, detection of polluting substances (e.g. PFAS) in water, and disease/infection screening.

Controllability and Observability of Non-homogeneous Granular Descriptor Fractional Dynamical Systems Applied in Electrical Circuit

Controllability and Observability of Non-homogeneous Granular Descriptor Fractional Dynamical Systems Applied in Electrical Circuit