International Journal of Electrical and Electronics Research最新文献_第7页

Optimized Multi Agent System for Stability Enhancement of Inter Connected Power System 增强互联电力系统稳定性的优化多代理系统

International Journal of Electrical and Electronics Research Pub Date : 2023-12-02 DOI: 10.37391/ijeer.110431

Vijaya Kumar Begari, Dr. V.C. Veera Reddy, Dr. P. Sujatha

{"title":"Optimized Multi Agent System for Stability Enhancement of Inter Connected Power System","authors":"Vijaya Kumar Begari, Dr. V.C. Veera Reddy, Dr. P. Sujatha","doi":"10.37391/ijeer.110431","DOIUrl":"https://doi.org/10.37391/ijeer.110431","url":null,"abstract":"Due to the rising use of renewable energy sources and the use of contemporary power electronic equipment, power system stability has become a major challenge in current power systems. Controlling the power system characteristics can increase the stability of the power system. The traditional techniques for improving power system stability, such as the use of FACTS devices, are costly and may not be effective in handling the dynamic changes of the power system. As a result, by optimizing the power system parameters, an optimization-based multi-agent system can improve the stability of the power system. The Grey Wolf Optimizer based Multi Agent System (GWO-MAS) is proposed in this paper to improve power system stability. The control agents of Distributed Generations (DGs) are optimized using GWO algorithm based on the deviations in frequencies of DGs. Particle Swarm Optimization based Multi Agent System (PSO-MAS) and Conventional Multi Agent System performance are compared with the suggested technique's implementation on IEEE 30 bus system and testing in MATLAB/Simulink environment. The outcomes showed that the suggested approach is successfully improving the stability of an interconnected power system.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"119 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Control of Three-Phase Squirrel Cage Induction Motor by Field Acceleration Method (FAM) for E-Mobility 利用场加速法 (FAM) 控制用于电动汽车的三相鼠笼式感应电机

International Journal of Electrical and Electronics Research Pub Date : 2023-12-02 DOI: 10.37391/ijeer.110432

Elisha Undeti, Muktevi Chakravarthy

{"title":"Control of Three-Phase Squirrel Cage Induction Motor by Field Acceleration Method (FAM) for E-Mobility","authors":"Elisha Undeti, Muktevi Chakravarthy","doi":"10.37391/ijeer.110432","DOIUrl":"https://doi.org/10.37391/ijeer.110432","url":null,"abstract":"The rapid electrification of mobility systems has fuelled the demand for advanced control techniques that can enhance the performance and efficiency of electric vehicles (EVs). In this context, this paper introduces the Field Acceleration Method (FAM) as a control strategy for three-phase squirrel cage induction motors, specifically tailored for e-mobility applications. FAM has not been previously simulated or tested practically in the context of electric mobility, making this study a pioneering effort. Induction motors are widely employed in electric vehicles, and various control methods such as the Indirect Field-Oriented Control (IFOC) gained popularity for its effectiveness in achieving precise and efficient motor control. In this research, FAM is simulated using MATLAB, and the results demonstrate its suitability for electric vehicle control applications. FAM exhibits the potential to achieve rapid speed responses, making it a promising alternative to established control techniques. The outcomes of this study highlight the applicability of FAM in improving the dynamic performance of EVs, contributing to the ongoing efforts to enhance the efficiency and responsiveness of electric mobility solutions. This research paves the way for practical implementations of FAM in electric vehicles, potentially revolutionizing the field of EV motor control.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"118 51","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Cluster Head Selection in Wireless Sensor Network via Multi-constraint Basis using Hybrid Optimization Algorithm: NMJSOA 使用混合优化算法在无线传感器网络中基于多约束条件优化簇头选择NMJSOA

International Journal of Electrical and Electronics Research Pub Date : 2023-12-02 DOI: 10.37391/ijeer.110428

Vikhyath K B, Achyutha Prasad N

{"title":"Optimal Cluster Head Selection in Wireless Sensor Network via Multi-constraint Basis using Hybrid Optimization Algorithm: NMJSOA","authors":"Vikhyath K B, Achyutha Prasad N","doi":"10.37391/ijeer.110428","DOIUrl":"https://doi.org/10.37391/ijeer.110428","url":null,"abstract":"Due to its general use in various practical applications, number of innovations in Wireless Sensor Networks (WSN) is receiving a lot of consideration from researchers. It shows significant technological development with excessive capacity since it gives useful information to users in a particular field through real-time monitoring. Due to its characteristics, such as infrastructure-less adoption and resource limitations, wireless sensor networks bring several problems that could impair the system's operation. Cluster based routing in WSN is the major concern in this field that could conflicts with the effectiveness of energy, suitable Cluster Head (CH) selection, protected data transport as well as network lifetime augmentation, demand major consideration, etc. However, it remains challenging to make optimal clustering process of WSN that makes the routing process more effective. Thereby, this work proposes a new Namib Merged Jelly Search Optimization Algorithm (NMJSOA) approach for the optimal CH selection in WSN by the different constraints. Initially, the sensor nodes are grouped together to form the clusters by the k-means clustering techniques. Subsequently, allocating the CH for each cluster by computing the weight function for each cluster depends on the conditions such as energy, delay, distance and security. According to the NMJSOA method, the Namib Beetle Optimization (NBO) searching position and the Jellyfish swam old position are added together to get the best optimum position. Finally, the performance of the suggested model is investigated over the conventional methods in terms of different performance measures.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"49 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Optimized Neural Network Model for Ink Selection in Printed Electronics 用于印刷电子产品油墨选择的新型优化神经网络模型

International Journal of Electrical and Electronics Research Pub Date : 2023-12-02 DOI: 10.37391/ijeer.110430

Alagusundari Narayanan, Dr. Sivakumari Subramania Pillai

{"title":"A Novel Optimized Neural Network Model for Ink Selection in Printed Electronics","authors":"Alagusundari Narayanan, Dr. Sivakumari Subramania Pillai","doi":"10.37391/ijeer.110430","DOIUrl":"https://doi.org/10.37391/ijeer.110430","url":null,"abstract":"The field of Printed Electronics (PE) is experiencing significant growth in the industrial sector and generating considerable interest across various industries due to its ability to produce intricate components. The functionality of printed electronic products heavily relies on the utilization of conductive ink during the printing process, which plays a vital role in developing flexible electronic circuits and improving the communicative functionalities of objects. Selecting the right ink for printing is crucial to meet consumer requirements. However, the conventional approach to this process has been manual, labor-intensive, and time-consuming, relying on the expertise of designers. This paper presents an automated ink selection model for printed circuits. This novel method has been incorporated with Multilayer Perceptron Neural Network (MLPNN) and Particle Swarm Optimization (PSO), named PSO-MLPNN. A dataset containing material features is generated by gathering information from both literature and experimental observations. To ensure uniformity, the data undergoes preprocessing using the min-max method, which scales all features to a standardized range between 0 and 1. A four-layer MLPNN is constructed to choose the most suitable ink. The network is trained with the PSO algorithm. The bias and weight values of MLPNN are tuned using the PSO algorithm to attain high accuracy. The computed findings confirm that the ink selection is highly effective and more accurate when compared to both the standard MLPNN.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"12 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A New Dragonfly Optimized Fuzzy Logic-based MPPT Technique for Photovoltaic Systems 基于模糊逻辑的新型蜻蜓优化光伏系统 MPPT 技术

International Journal of Electrical and Electronics Research Pub Date : 2023-12-02 DOI: 10.37391/ijeer.110429

Pramod Singh, B. Mangu, Sukhdeo Saho

{"title":"A New Dragonfly Optimized Fuzzy Logic-based MPPT Technique for Photovoltaic Systems","authors":"Pramod Singh, B. Mangu, Sukhdeo Saho","doi":"10.37391/ijeer.110429","DOIUrl":"https://doi.org/10.37391/ijeer.110429","url":null,"abstract":"Photovoltaic (PV) power systems should be operated at the maximum power point (MPP) for best solar energy utilization, which can be achieved using maximum power point tracking (MPPT) techniques. Perturb & Observe (P&O) and Fuzzy logic MPPT approaches were two of the various strategies that were suggested as effective ways to achieve Maximum Power under Continuous Irradiation. When exposed to changes in environmental conditions, these approaches perform poorly dynamically and exhibit substantial steady-state oscillations around the MPP. To overcome this problem, this paper proposes the Dragonfly optimization-based fuzzy logic MPPT approach for maximum power extraction of photovoltaic (PV) systems. The approaches for implementing FL-based MPPTs that are currently available are not adaptable to the operating point, which varies widely in real-world PV systems with operational irradiance and ambient temperature. The proposed MPPT (DAFLC-MPPT) is straightforward, accurate, and offers quicker convergence to the optimal operating point. With consideration of various operating situations at slow and fast changes in solar radiation, the efficacy and viability verifications of the proposed AFL-MPPT approach are validated. The proposed strategy outperforms the standard P&O and fuzzy logic methods.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"122 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Analysis of Multi-Hop Hybrid FSO/mm Wave Communication System for Next-Generation Wireless Networks 面向下一代无线网络的多跳混合 FSO/ 毫米波通信系统性能分析

International Journal of Electrical and Electronics Research Pub Date : 2023-11-30 DOI: 10.37391/ijeer.110424

Mogadala Vinod Kumar, Vinodh Kumar Minchula, M. Hemanth Kumar, M. V. Krishna, S. Gottapu

引用次数: 0

Skin Cancer Detection and Classification using Deep learning methods 使用深度学习方法进行皮肤癌检测和分类

International Journal of Electrical and Electronics Research Pub Date : 2023-11-30 DOI: 10.37391/ijeer.110427

Anchal Kumari, Dr. Punam Rattan

引用次数: 0

High-frequency Differential Mode Modeling of Universal Motor's Windings 万能电机绕组的高频差模建模

International Journal of Electrical and Electronics Research Pub Date : 2023-11-30 DOI: 10.37391/ijeer.110425

Dr. Mohammed Hamza Bermaki, Dr. Houcine Miloudi, Dr. Mohamed Miloudi, Dr. Abdelkader Gourbi, Prof. Dr. Abdelber Bendaoud

{"title":"High-frequency Differential Mode Modeling of Universal Motor's Windings","authors":"Dr. Mohammed Hamza Bermaki, Dr. Houcine Miloudi, Dr. Mohamed Miloudi, Dr. Abdelkader Gourbi, Prof. Dr. Abdelber Bendaoud","doi":"10.37391/ijeer.110425","DOIUrl":"https://doi.org/10.37391/ijeer.110425","url":null,"abstract":"The universal motor is a rotating electrical machine that can operate on either direct current or single-phase alternating current, similar to a DC motor. It has been widely used in various small and inexpensive drives for a long time, mostly in home appliances and hand tools. The noise generated by a universal motor is believed to be closely associated with the electromagnetic torque fluctuations of the machine, which are caused by variations in the current supplied to the motor. The power electronics utilized for controlling the motor's speed are responsible for these current changes. Accurate high-frequency motor models are crucial for reliable electromagnetic interference simulations in motor drive power electronic systems. Research efforts have expanded to explore different realistic configurations that can be used to investigate the electromagnetic compatibility behavior of electrical machines. This study describes a method for predicting the differential mode impedance of universal motor. The behavior of each motor winding has been individually studied through impedance measurements, starting with the armature, followed by the series winding, and finally the inductive compensating winding. The prediction results over a wide frequency range up to 1 MHz are in good agreement with the measurements and enabled us to propose a model circuit for each motor winding.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"85 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139206664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Location of Electric Vehicle Charging Station in Reconfigured Radial Distribution Network 重构径向配电网络中电动汽车充电站的最佳位置

International Journal of Electrical and Electronics Research Pub Date : 2023-11-30 DOI: 10.37391/ijeer.110426

D. Srinivas, Dr.M. Ramasekhara Reddy

{"title":"Optimal Location of Electric Vehicle Charging Station in Reconfigured Radial Distribution Network","authors":"D. Srinivas, Dr.M. Ramasekhara Reddy","doi":"10.37391/ijeer.110426","DOIUrl":"https://doi.org/10.37391/ijeer.110426","url":null,"abstract":"Electric vehicles are becoming increasingly popular because they are cleaner-burning and more efficient than combustion-engine automobiles. Due to the diminishing availability of fossil fuels and the carbon emissions produced by cars, electric vehicles (EV) have become a need for mobility in the near future. Electric car charging stations were established as a consequence of the increase in EVs. Electric car charging lowers voltage and increases real power loss in the radial distribution network. In order to mitigate real power loss and provide a stable voltage profile, the charging station has to be placed as efficiently as possible. The current research examines and elucidates the influence of electric vehicle charging stations (EVCS) on the balanced radial distribution network (BRDN) using particle swarm optimization (PSO). There are two steps involved in the planning process. The optimal placement for EVCS [1] in BRDN is identified in the first stage using PSO. The second stage uses reconfiguration to ensure higher EVCS stability. This two-step technique's main goal is to decrease the real power loss due to the placement of charging stations in the radial distribution network (RDN). The correctness of the suggested approach is expounded upon in four different cases. The second, third, and fourth cases use a two-step procedure, which is then compared to the base case. In the base case EVCS is ideally located in BRDN using PSO. The fourth case employs a concurrent two-step optimization approach and demonstrates superior performance compared to other cases. The suggested approach is implemented and evaluated on the IEEE 69 bus BRDN using the MATLAB software.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"168 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139203606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Brain Tumor Classification and Identification using PSO and ANFIs 使用 PSO 和 ANFIs 进行脑肿瘤分类和识别

International Journal of Electrical and Electronics Research Pub Date : 2023-11-20 DOI: 10.37391/ijeer.110422

J. S. Awati, Mahesh Kumbhar

引用次数: 0