AEEE. 2024, vol. 22

Permanent URI for this collectionhttp://hdl.handle.net/10084/152515

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Now showing 1 - 20 out of 34 results

A Rewiew of Plasma Antenna Technology for Satelite Communication
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Alharbi, Khalid Hame; Alharbi, Mohammed S.
In wireless communication systems, the an- tenna is the most crucial component. An antenna is a device that converts electrical impulses into radio waves and vice versa. Antennas come in a variety of shapes and sizes, with varying properties depending on the ne- cessity for signal transmission and reception. In this study, we give a comparative analysis of the promise and limitations of plasma antennas in the field of satel- lite communication systems giving an in-depth inves- tigation of their fundamental principles, technological breakthroughs, applications, and the obstacles that fol- low their integration.
Physical Layer Security in wireless sensors networks with friendly jammer: Secrecy Outage Probability Analysis
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Minh, Bui Vu; Nhan, N.H.K.; Pham, Thu-Ha Thi; Tran, Minh
In this paper, we addressed improving the physical layer security (PLS) of an energy harvest- ing (EH)-based wireless network composed of a source node, which is operated by the harvested energy from the power beacon and sends secure information to a destination in the presence of an eavesdropper and a cooperative jammer (CJ). In particular, we provided an explicit transmit design for minimizing the secrecy outage probability (SOP), subject to a minimum secrecy rate constraint. The results show that support from a friendly jammer can significantly improve the reliabil- ity and security performance of the system. Addition- ally, we described the effects of particular factors on the optimal possible temporal distribution between informa- tion transmission and energy harvesting. As a result, when considering the SOP, we concluded that there ex- ists an optimal value of the time switching factor for the system to function well. The analytical formulas were verified by Monte Carlo simulation.
Investigation of Transients in Grounding Grids
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Samy, Basma M.; Mansy, Ibrahim I. I.; Badran, Ebrahim A.
he grounding grid of a power system is very important for absorbing the harmful overvoltages and/or overcurrents during transients. The lightning surges frequently causes overvoltages and/or overcur- rents via the grounding grid. This may have dangerous effects on persons and/or equipment. Therefore, this paper reviews in detail the transient in grounding grids due to lightning surges. The grounding grid configura- tions and mathematical modeling are explained. Many configurations are used in the analysis such as one, four, sixteen meshes grounding configurations. Also, two injection points are analyzed: at the terminal and the middle of the grid. The analysis is carried out using ATP/EMTP. Many transient responses of voltages and currents at different points of the grounding grid for different configurations are calculated and compared. The peak voltage and current values are compared to be the basis of safety design of the grounding system.
Largest Roi Segmentation for Breast Cancer Classification Using a VGG16 Deep Learning Network
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Nguyen, Thanh-Tam; Nguyen, Thanh-Hai; Ngo, Ba-Viet; Nguyen, Thanh-Nghia
The exact evaluation of breast cancer im- ages for patients is very important, because they can be early treated for lasting their life. This article pro- poses a classification system for finding breast cancer images, in which each breast lesion image is segmented to produce a largest Region of Interest (ROI) and a VGG16 deep learning network is applied for classifi- cation. An Otsu threshold is utilized on two datasets from two sources of CBIS-DDSM and MIAS to create largest ROI with main features. For the classification with high performance, two datasets of the breast le- sions were augmented by rotating, flipping, and bright- ness variation. This article was proposed an algorithm with processing images sets before classification using VGG16. In particular, the results of the largest ROI datasets for four types of breast lesions were repre- sented through segmentation, normalization and en- hancement. In addition, the results of classifying four types of breast lesions (BC, BM, MC, MM) were eval- uated using confusion matrix, with the high accuracy of around 95%. Another evaluation was that these im- age sets without ROI/with ROI parts/With the largest ROI only using the Otsu segmentation were compared and the highest accuracy was of the image sets with the largest ROI. The results with the high accuracy demon- strated to illustrate the effectiveness of the proposed method. It means that this method can be developed to classify many stages of breast cancers during diagnosis and treatment.
Simplified Methodology of Economic Evaluation of Household PV Instalations in Czech Republic Using Monte Ccarlo Method
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Vinš, Martin; Gangur, Mikuláš
his paper deals with the design of a suit- able, transparent, and reasonably accurate methodology for the economic evaluation of household photovoltaic (PV) installations in the Czech Republic. The basis of economic evaluations of household photovoltaic instal- lations is a time model of energy balance from which cash flows result. Therefore, a specific methodology of the energy balance calculation is proposed to increase accuracy, while at the same time, reasonably increas- ing the energy balance model complexity by using the Monte Carlo method (probability model). Following the detailed analysis of the affecting factors and the compi- lation of the methodology for the energy balance calcu- lation, the main stochastic parameters were specified. These specified stochastic parameters are estimated by the Monte Carlo method in multiple scenarios. The presented methodology of the energy balance calculation is also used for direct calculation where the mean val- ues of the same specified stochastic parameters (without assumption of their probability) serve as the reference values for one scenario. Pros and cons of the designed methodology are demonstrated in a case study of an existing household photovoltaic installation. The mean values of the output parameters from the Monte Carlo method scenarios are then calculated for subsequent re- sults comparison of both methods and also with the real (measured) values of the case study installation. Then a cash flows for each year of the installation’s lifetime are stated, and the internal rate of return (IRR) as an economic evaluation criterion is calculated. The results show that IRR differs between methods by about 2.5% which may be crucial in such long-term projects on the verge of profitability. The accuracy of the application of the Monte Carlo method to the output parameters is then discussed in the conclusion where some possible recommendations for further work and project evalua- tors are indicated as well.
Outage Performance of Energy Harvesting Assisted Multi-Hop M2M Networks with Partial Relay Selection Methods
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) An, Ngo Hoang; Huan, Nguyen Trong; Nguyen, Ngoc-Lan; Tung, Nguyen Tien
his paper evaluates outage performance of wireless energy harvesting-assisted multi-hop mobile- to-mobile schemes. In our scheme, a mobile source sends its data to a mobile destination via a pre- established route, utilizing multiple intermediate mo- bile relays. The source and relay nodes harvest energy from a power beacon station deployed in the network, and they use this energy to transmit the data. To en- hance reliability of data transmission, cooperative com- munication is employed at each hop, with assistance of outer mobile nodes (they are not on the source-to- destination route). An incremental cooperation tech- nique is applied at each hop, i.e., cooperative commu- nication is only performed when the direct link is out- age. Moreover, two partial relay selection algorithms are also considered at each hop. This paper calculates end-to-end outage probability of the proposed schemes over double-Rayleigh fading channels. The obtained re- sults show that our schemes can achieve better outage performance, as compared with the conventional multi- hop relay scheme and a corresponding scheme that uses random relay selection at each hop.
Advances in Solar Radiation Estimation Techniques: A Comprehensive Rewiew
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Yeşil, Feyza Nur; Serttaş, Tuba Nur
Solar energy is a favored renewable energy source in the energy sector due to its zero emissions, environmental friendliness, low cost, and sustainability. However, meteorological factors such as weather conditions and cloud movements can interrupt solar radiation, potentially leading to undesirable outcomes in the energy sector. Solar irradiance forecasting is crucial for mitigating these adverse effects and supporting the development of renewable energy projects. In this study, the methods employed in the literature for various prediction intervals are classified, and the evaluation results of these predictions are summarized in a table. Also, an example model created with ANFIS for estimating solar radiation is presented. Imagebased and NWP models is perform well for short-term forecast horizons. To predict various time horizons, artificial intelligence-based models such as time series models, deep learning, and machine learning are prefer. Hybrid models that combine multiple methods to achieve higher accuracy are also proposed, although this increases the complexity and cost of the model. There are potential limitations in the field of solar forecasting that arise from model and data characteristics. Therefore, This study aims to guide other researchers in this field by discussing the features, limitations, and results of the models used for solar forecasting. Also, the example of daily solar radiation forecasting provided in this study offers a practical application opportunity for researchers new to this field.
Performance Enhancing of Single-Phase Voltage Source Inverter Through Average-Based Pulse Delay Time Compensation
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Franklin, J.; Pongiannan, R.K.; Narayanamoorthi, R.
The effectiveness of a Voltage Source Inverter (VSI) operating in a single-phase configuration controlled using Pulse Width Modulation (PWM) depends on multiple factors, particularly a special attention given to the Delay Time (DT) linked to the switching of power devices within the same arm. The ramifications of DT in a single-phase VSI have notable effects on output quality, harmonic content, and transient responsiveness. In this paper, a DT compensator is implemented for a single-phase VSI using the Average Based Pulse Compensation (ABPC) method. This technique adjusts switching instant to counteract the effects of DT and mitigate voltage distortions, reduce harmonic content, and enhance waveform quality. Simulations and validations are performed using MATLAB/Simulink to evaluate compensator performance under different operating conditions. The compensator design is implemented in hardware through the utilization of an FPGA SPARTAN 6 XC6SLX9 controller, tasked with generating a PWM pulse. The quality of ouput voltage and current has been improved by ABP compensation and the THD is reduced by 20%. Additionally, a laboratory testing phase is conducted to assess the performance of the proposed method, involving the validation of a prototype for a single-phase PWM inverter.
Sensorless DTC Based on Artificial Neural Network for Independent Control of Dual 5-Phase Induction Machine Fed by a Three-Level NPC Inverter
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Benzaoui, Khaled Mohammed Said; Benyoussef, Elakhdar; Guedida, Sifelislam; Tabbache, Bekheira; Kouache, Ahmed Zouhir
This paper deals with an independent control of two parallel-connected five-phase induction machines (FPIM) fed by NPC three-level inverter. In effect a direct torque control (DTC) of two parallelconnected FPIMs has been developed to ensure a simple and fast decoupled control over the stator flux and electromagnetic torque and high performance in event of machine parameters disturbances. However, DTC suffer from the torque and flux ripples due the hysteresis controllers. In this context, an intelligent DTC based on Artificial Neural Network (ANN) has been proposed to minimize the stator flux and electromagnetic torque ripples in a steady and transient states and therefore reduction of the stator current harmonic THD. hence, Intelligent ANN hysteresis controllers and switching table of the DTC have been incorporated to select the optimum voltage vector of the NPC-VSI to be applied in the control of two parallel-connected FPIM. Moreover, a virtual current sensor (VCS) approach is proposed to configure a fault-tolerant control scheme (FTC). The effectiveness of the proposed (DTC-ANN) and the FTC have been checked by an intensive simulation in different operating conditions.
Modelling And Control of Cable Driven Robotic Arm Using Maplesim
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Alkamachi, Ahmed; Abboosh, Yahya Ghufran Khidhir
Cable-driven robotic arms (CDRA) are robots with novel structures, wherein flexible cables are used to drive rigid links identified to move the end effector according to a desired trajectory. Due to the complex and nonlinear characteristics of this type of robotic arm, it is challenging to derive the model, which requires critical analysis to be conducted. This paper presents the design, modeling, and Model Predictive Control (MPC) of a special 2D CDRA with four rigid links. Maplesim is employed as a tool to design and simulate the proposed robotic arm. First, the prototype model is constructed in Maplesim and simulated using random input signals, and the input and output data sets are collected. A data-driven scheme based on neural networks is used to learn the unknown kinematics of the CDRA and to solve the kinematic control issue. The Matlab-Simulink platform is used for this purpose, and the black box model is obtained using the neural network fitting tool. MPC is then used for the end effector trajectory tracking control and to validate the modeling processes. Furthermore, comparative simulations using two scenarios are applied to the controlled system to verify the effectiveness of the proposed modeling and control method with the aid of Mean Squared Error (MSE) as an optimality index. The result verified that CDRA is capable of following reference trajectories accurately with MSE of 10e-5 and 4.99e-5 for rhombus and circular trajectories respectively.
Outage Performance Analysis of STAR-RIS-NOMA Networks under Imperfect CSI
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Nguyen, Sang Quang; Le, Anh-Tu; Phan, Van-Duc; Thien, Huynh Thanh; Kharel, Rupak
In this paper, we investigate the performance of simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs)-assisted non-orthogonal multiple access (NOMA) networks under imperfect channel state information (CSI). Furthermore, we derive the exact analytical equations for the OP of two users. To obtain insight into the high power domain, the asymptotic analysis outage probability (OP) is studied. Further, the Monte-Carlo methods verified the tightness of all derivations. Finally, the results indicate that when increasing the number of elements of STAR-RIS, the STAR-RIS-NOMA networks can achieve improved outage performance.
Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Woon, Sze Sin; Kho, Lee Chin; Ngu, Sze Song; Joseph, Annie; Kipli, Kuryati
The rapid expansion of power transmission infrastructure necessitates the development of efficient and accurate inspection methods. This paper proposes an autonomous positioning model for Unmanned Aerial Vehicles (UAVs) that can detect power line insulators on transmission lines to address this need. The proposed model leverages machine learning algorithms for autonomous detection of insulators. To determine the optimal stopping point and safety distance between the UAV and the insulator, a mathematical model is presented that utilises the captured images and the machine learning algorithm. A simulation model is utilised to verify the proposed model, ensuring that the UAV moves to the best-predicted position. The machine learning algorithms are utilised to identify and calculate the length of power line insulators. A set of labelled insulator images is trained in the selected machine learning algorithm, enabling it to accurately determine the length of insulators in new images. The mathematical model considers the size of the insulator in the image to calculate the safety distance between the UAV and the power line insulator, while also determining the optimal image shooting coordinate. MATLAB’s Simulink software is utilised to leverage the UAV’s navigation and control systems, enabling it to move to the best position for capturing high-quality photos of the power transmission lines. The model also considers environmental conditions and operational constraints for optimisation. The proposed autonomous positioning model has undergone extensive simulation to demonstrate its effectiveness. Furthermore, the autonomous positioning of the UAV reduces human intervention, minimises inspection time, and increases efficiency and cost-effectiveness.
Hosting Capacity In Smart Distribution Network – Definitions, Calculation, Constraints And Improvement
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Mašić, Fatima; Šarić, Mirza; Džemić, Zijad
Renewable sources offer benefits including more efficient power system operation and management and reduction of CO2. Recent increases in distributed generation cause operational and technical challenges such as voltage rise. Hosting capacity aims to estimate how much additional generation can be integrated into the existing network without breaching prescribed technical and operational constraints. The aim of this paper is to explore in the recent literature answers to questions: how HC can be calculated, what factors influence it and how it can be improved. The most common HC improvement methods are photovoltaic inverter reactive power control, voltage control, network reconfiguration and soft open points usage, conductor reinforcement and classical reconstruction of the network, active operational strategies based on control of the active and reactive power, active power curtailment, battery energy storage systems, power quality improvement and electrical vehicles. To achieve advantages like reducing calculation time and improving accuracy, state-of-the-art research enhancements are built on a unique combination of techniques from earlier studies. They take into account both technological and economical constraints, in comparison to earlier approaches where only technological constraints were considered. It also aims to present what are the major contributions in the field, what are the existing research gaps, opportunities and possible future directions. This paper contributes as it presents the state of art in this field and gathers information that can be used as a foundation for future research. It can be concluded that this remains an important area of research with numerous research opportunities.
Multi-Objective Design of An Induction Motor Using A New Method For Finding The Optimal Solution By The Pareto Front Based On Harmony Search
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Laouar, Idris; Boukadoum, Ahcene
This article introduces a novel method for choosing the optimal solution from the Pareto front generated by the multi-objective harmony search (MOHS) algorithm, specifically aimed at optimizing an induction motor. We formulate both single- and multi-objective optimization problems that minimize active mass while maximizing efficiency and rated torque. To effectively identify and manage the Pareto-optimal front, we utilize non-dominated elitist fast sorting and crowding distance. Comprehensive simulations using MATLAB software were conducted on a 18.5 kW, 4- pole, 50 Hz squirrel-cage induction motor serving as our test system. Furthermore, in-depth comparisons were made between our proposed method and established approaches like the fuzzy membership approach and the geometric mean, all vying to select the best solution from the Pareto set generated by the Harmony search algorithm. This rigorous evaluation highlighted the superior efficiency and robustness of our method, demonstrating significant improvements compared to the motor’s initial values: 0.4377% for rated torque, 0.1766% for efficiency, and a remarkable 7.1048% for active mass.
Digital Space Vector Approach to Eliminate Overcharging of DC-link Capacitor in Asymmetrical VSI Fed Open End Winding Induction Motor Drive
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Reddy, M. Harshavardhan; Gowri, K. Sri; Kishor, G.; Reddy, T. Bramhananda
Dual inverter topology with asymmetrical input voltage (2:1) is the simple and most economical solution to fabricate four-level output voltage. Due to the lack of switching status selections, the asymmetric configuration of the dual inverter suffers from overload of the DC link capacitor. The present work compares few exiting decoupled and coupled PWM techniques with implementation using multilevel carrier comparison approach and digital space vector approach. It is proved that proposed coupled PWM with the digital space vector approach provide easy path for switching state selection to eliminate the problem “overcharging of DC link capacitor”. The other decoupled PWM techniques may eliminate the problem, but generate poor quality of output voltage. In addition, the proposed digital space vector approach provides freedom in the choice of different voltage vectors to achieve good output voltage quality.
Multi-Layer Networks and Routing Protocols for Aquatic Robotic Swarm Management
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Mannone, Maria; Fazio, Peppino; Marman, Norbert; Giacometti, Achille
The paradigm of multi-layer networks can help devise a set of robotic swarms interacting with mo- bile computing centrals. We present here a distributed hierarchical network model and a related routing pro- tocol (based on static routing and/or AODV protocol for peer nodes) for swarm robotics in aquatic environ- ment, defining also which packets need to be exchanged to guarantee the mission accomplishment. Joining con- cepts and techniques from different disciplines allows us building a robust system with potential practical ap- plications in scenarios such as environmental care. We discuss our results and further developments of the pro- posed approach.
Design of A Real-Time Solar Power Monitoring and Controlling System Using Internet of Things
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Trang, Tran Thanh; Toi, Le Thanh; Khoa, Tran Huu
In this research, the system is designed to monitor parameters of residential solar power sources such as voltage, current, power capacity, power factor and energy consumption. These parameters are mea- sured by a highly accurate PZEM circuit and the specifi- cations are suitable for residential solar power sources. Measurement results will be sent to the main control circuit (ARM controller) via the UART communica- tion standard to analyze and filter the necessary data. The data of that parameter will then be displayed at the system installation site using the TFT screen. Af- ter an installation period, the control circuit will send measurement parameters to the dedicated WiFi mod- ule (ESP32), the WiFi module will continue to send parameters to the cloud server for storage and mon- itoring. The system also builds applications that run on many operating systems, can access data, and dis- play data in real time using IoT technology. It should be noted that the system can still operate in the event of loss or absence of WiFi signal by using Bluetooth signal. In addition, the designed system also has the function of remotely controlling on/off the solar power supply to the loads when an incident occurs, ensuring safety for the electrical system.
Performance Comparison Of A Six Phase Surface-Mounded Pmsm With Inner And Outer Rotor Types For High Torque Applications
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Quoc, Vuong Dang; Truong, Trinh Cong; Vu, Thanh Nguyen; Thanh, Ha Vo
Permanent magnet synchronous motors (PMSMs) have been widely applied in the fields of elec- tric cars/strucks and industries due to their high torque and efficiency, reliable performance, simple structure and various shapes and sizes. Recently, multi-phase PMSMs with inner and outer configurations have been applied to the above applications. However, the inves- tigation, evaluation and comparison performences of multi-phase PMSM with inner and outer rotor types in previous studies have not been fully presented in both the analytical model and finite element technique. The previous researches mainly have focussed on do- ing experiments without presenting the detail of de- sign of these machines. In this context, electromag- netic parameters (such as electromagnetic torque, cog- ging torque, torque ripple, back electromagnetic force, linkage flux) of a six-phase surface mounted PMSM (SPMSM) with inner and outer rotor configurations is proposed via an association of analytic model and fi- nite element method (FEM). The development of the proposed methods is focussed on a 145kW six-phase SPMSM with two distinct rotor structures (inner and outer rotors)
Comparison Of Mppt Algorithms For Dc-Dc Boost Converter In Grid-Tied Photovoltaic Systems
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Shehata, Nabila; Hussien, Ahmed E. A.; Abdellatif, Walid S. E.; Ramamurthy, Praveen C.; Emad-Eldeen, Ahmed
n unpredictable weather circumstances, a maximum power point tracking (MPPT) approach is critical for ensuring maximum photovoltaic (PV) out- put power is extracted. In this paper, we will com- pare the incremental conductance algorithm (IC), per- turb and observe (p&o), and fuzzy logic controller (FLC) as maximum power point tracking (MPPT) techniques. The three algorithms were used on a pho- tovoltaic energy conversion system that was linked to a grid. The suggested methodologies investigate the pho- tovoltaic (PV) system’s solar energy conversion perfor- mance under various irradiance and temperature cir- cumstances. Lastly, a performance comparison between IC, P O, and FLC has been performed, demonstrating the superiority of the fuzzy controller over the other ap- proaches. FLC converts photovoltaic electricity readily, reducing fluctuations, and it responds quickly to vari- ations in solar irradiation (the shading effect). The simulation results demonstrate that the controller us- ing fuzzy logic performs well, allowing the inverter to convert the electricity provided by the solar panels.
The future of sustainable agriculture: A review of IOT and autonomous control in vertical hydroponic farming
(Vysoká škola báňská - Technická univerzita Ostrava, 2024) Mohd Azmi, Kaiyisah Hanis; Mohamed Radzi, Nurul Asyikin; Ahmad, Ayuniza
By 2050, the global population is ex- pected to exceed 9.7 billion, increasing the demand for food production. Vertical hydroponic (VHF) systems, which enable hydroponically growing plants in space- constrained situations emerge as a promising solution to these difficulties. To address the limitations of tra- ditional farming methods and the challenges faced in VHF, such as manual monitoring and inefficient re- source utilization, this survey paper examines how IoT and ACS are integrated into VHF to enhance crop management. It discusses the advantages of this in- tegration, including real-time monitoring, automation, and improved environmental control. Examples of IoT- ACS implementations in VHF, such as automated nu- trient dosing systems and real-time root monitoring, are provided to illustrate the diverse applications of these technologies. This paper also presents the chal- lenges such as connectivity issues and sensor calibra- tion must be addressed for successful implementation. Finally, this article demonstrates how IoT and ACS have the potential to change agriculture and handle the growing demand for food production in a sustainable manner.

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