IEEE Canadian Journal of Electrical and Computer Engineering最新文献

IEEE Canadian Journal of Electrical and Computer Engineering 电气和电子工程师学会《加拿大电气和计算机工程学报

IF 2.1

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-09-16 DOI: 10.1109/ICJECE.2024.3446351

引用次数: 0

Green Electricity Share Enhancement Through Rooftop Solar PV System on Institutional Sheds 通过机构大棚屋顶太阳能光伏系统提高绿色电力份额

IF 2.1

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-09-02 DOI: 10.1109/ICJECE.2024.3439867

Kola Leleedhar Rao

{"title":"Green Electricity Share Enhancement Through Rooftop Solar PV System on Institutional Sheds","authors":"Kola Leleedhar Rao","doi":"10.1109/ICJECE.2024.3439867","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3439867","url":null,"abstract":"Different cases have been exercised to create real-time feasibility for erecting solar photovoltaic (PV) system on the roofs of the seven sheds being utilized as six workshops (WSs) and one central store (CS) within a higher educational institution. The obtained results are so intensive that for the WS and CS sheds, the average daily normalized production (ADNP) in kWh/kWp/Day is more on the south-facing roofs (4.20) followed by west- (4.06), east- (3.96), and north-facing roofs (3.78). The mean average additional energy (MAAE) of about 11.27% and 2.52% can be generated on south- and west-facing roofs compared to the north- and east-facing roofs, respectively. In comparison to the vertical installation (VI), the average specific production (ASP) in kWh/kWp/Annum is more with the horizontal installation (HI) of PV modules on either side of the exposed roofs for WS (1459.25) and less for CS (1454.5). The total maximum energy that can be generated on the roofs of total seven sheds is about 969 566 kWh/Annum, which may reduce about 824.12 ton of CO2 emissions per annum. It is an appreciable figure and could pave a path for establishing green electricity. The outcomes of the presented study address the energy sustainability challenges of a higher educational institution.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"158-167"},"PeriodicalIF":2.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165085","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

Enhanced Validation of Intelligent Control Algorithms in AC Microgrids 交流微电网中智能控制算法的强化验证

IF 2.1

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-08-20 DOI: 10.1109/ICJECE.2024.3417470

Goturu Sai Abhishek;Satish Kumar Injeti;Deepak Reddy Pullaguram

{"title":"Enhanced Validation of Intelligent Control Algorithms in AC Microgrids","authors":"Goturu Sai Abhishek;Satish Kumar Injeti;Deepak Reddy Pullaguram","doi":"10.1109/ICJECE.2024.3417470","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3417470","url":null,"abstract":"This article presents the development and application of a microgrid (MG) power system simulator, with an emphasis on AC MG systems. The simulator’s modeling intends to replicate the dynamic behavior MG and interactions of the MG’s various components, including generators, photovoltaic (PV) systems, energy storage units, and loads. The simulator is compatible with both reactive and active power set points from the controller, enabling a comprehensive analysis of the efficacy of the system. The simulation is correlated with direct field testing; this method offers numerous advantages. It provides a safe and cost-effective environment for conducting extensive simulations, thereby avoiding the potential risks and damages associated with conducting experiments in the real world. The flexibility and scalability of the simulator enable researchers to examine a wide variety of operating scenarios, test various control strategies, and assess the impact of system uncertainties. By utilizing the power system simulator’s capabilities, researchers can obtain valuable insights into the behavior of MGs. They are able to evaluate the efficacy of control algorithms in regulating voltage and frequency, managing power flows, and facilitating seamless transitions between grid-connected and isolated modes of operation. In addition, the simulator permits the identification of prospective obstacles and challenges, the evaluation of various control strategies, and the validation of system performance under a variety of operating conditions. The results of simulations run on the power system simulator provide valuable data for optimizing the design and operation of MGs. They contribute to improving the MG systems’ dependability, stability, and resilience. The power system simulator will continue to play a crucial role in the development and deployment of efficient and sustainable MG systems as modeling techniques and simulation capabilities advance.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"148-157"},"PeriodicalIF":2.1,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165107","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 Ensemble Machine Learning Algorithm for Predicting the Suitable Crop to Cultivate Based on Soil and Environment Characteristics 基于土壤和环境特征预测适宜种植作物的新型集合机器学习算法

IF 2.1

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-08-14 DOI: 10.1109/ICJECE.2024.3400048

G. Mariammal;A. Suruliandi;Z. Stamenkovic;S. P. Raja

引用次数: 0

Consensus and Clustering Approach for Dynamic Event-Triggered Distributed Optimization of Power System Networks With Saturation Constraint Approche de consensus et de regroupement pour 带饱和约束的电力系统网络动态事件触发分布式优化的共识与聚类方法 Approche de consensus et de regroupement pour

IF 2.1

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-07-11 DOI: 10.1109/ICJECE.2024.3402961

Ijaz Ahmed;Muhammad Rehan;Abdul Basit;Fahad Saleh Al-Ismail;Muhammad Khalid

{"title":"Consensus and Clustering Approach for Dynamic Event-Triggered Distributed Optimization of Power System Networks With Saturation Constraint Approche de consensus et de regroupement pour","authors":"Ijaz Ahmed;Muhammad Rehan;Abdul Basit;Fahad Saleh Al-Ismail;Muhammad Khalid","doi":"10.1109/ICJECE.2024.3402961","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3402961","url":null,"abstract":"This study presents a novel approach for solving the economic dispatch (ED) problem in groups of generating units communicating through a communication network. The suggested strategy is a consensus-based dynamic event-triggered (ET) distributed optimization method. Our methodology considers the sharing of the local information between generators and their convex cost functions to address the total cost function and offers a decentralized optimization solution over a network. The proposed distributed method addresses the ED problem by considering the criterion of optimal cost and by offering efficient communication. Generating units are grouped according to their generation operational limits, that is, total capacity and dynamic ET distributed protocols are developed to ensure the consensus of cost variables among generating units, operating under normal capacity conditions. The remaining generating agents work on their operating limits, which are segregated through the sharing of flag information through a switching mechanism. Consequently, in contrast to the existing methods, the recommended protocol allows nodes to function in groups, based on the power supply, for ED with geographical clustering and capacity restrictions, in addition to handling the system constraints. Furthermore, the proposed technique employs a dynamic triggering method to manage bandwidth and guarantee the elimination of Zeno behavior. The simulation results validate the efficacy of the proposed approach.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"136-147"},"PeriodicalIF":2.1,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013420","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

IEEE Canadian Journal of Electrical and Computer Engineering 电气和电子工程师学会《加拿大电气和计算机工程学报

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-06-14 DOI: 10.1109/ICJECE.2024.3379100

引用次数: 0

A Method for Abnormal Behavior Recognition in Aquaculture Fields Using Deep Learning 利用深度学习识别水产养殖领域异常行为的方法

IF 2.1

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-06-12 DOI: 10.1109/ICJECE.2024.3398653

Wu-Chih Hu;Liang-Bi Chen;Hong-Ming Lin

{"title":"A Method for Abnormal Behavior Recognition in Aquaculture Fields Using Deep Learning","authors":"Wu-Chih Hu;Liang-Bi Chen;Hong-Ming Lin","doi":"10.1109/ICJECE.2024.3398653","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3398653","url":null,"abstract":"The fish industry is an important source of income for island countries. Fish is a main source of animal-based protein. Marine fishing is gradually being replaced by marine farming (or aquaculture) due to declining wild fish populations and water pollution. However, fish farming is costly job with high requirements for labor, electricity, water, and feed. The use of deep learning to perform intelligent surveillance in aquaculture fields, reducing the need for human resources and implementing real-time monitoring, has been proposed. In this article, we propose a novel deep residual network (ResNeXt \u0000<inline-formula> <tex-math>$3 times 1 mathrm{D}$ </tex-math></inline-formula>\u0000) for abnormal behavior recognition in aquaculture fields. The proposed ResNeXt \u0000<inline-formula> <tex-math>$3 times 1 D$ </tex-math></inline-formula>\u0000 convolutional network is mainly based on an \u0000<inline-formula> <tex-math>$R(2+1) D$ </tex-math></inline-formula>\u0000 convolutional network and modified to obtain better performance. Experimental results showed that the proposed ResNeXt \u0000<inline-formula> <tex-math>$3 times 1 D$ </tex-math></inline-formula>\u0000 exhibited good performance for abnormal behavior recognition in aquaculture fields. Specifically, the accuracy obtained using the proposed ResNeXt \u0000<inline-formula> <tex-math>$3 times 1 mathrm{D}$ </tex-math></inline-formula>\u0000 for abnormal behavior recognition in aquaculture fields was approximately \u0000<inline-formula> <tex-math>$95.3 %$ </tex-math></inline-formula>\u0000.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"118-126"},"PeriodicalIF":2.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013197","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

Impacts of Laminating Core Materials on Permanent Magnet Synchronous Motor by Newton–Raphson Methodc 用牛顿-拉斐逊法研究层压铁芯材料对永磁同步电机的影响c

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-04-30 DOI: 10.1109/ICJECE.2024.3370973

Prabhu Sundaramoorthy;Arun Vijayakumar;Kuppapillai Rajkumar;Jamuna Ponnusamy;Gokul Chandrasekaran;Vijayakumar Madhaiyan

{"title":"Impacts of Laminating Core Materials on Permanent Magnet Synchronous Motor by Newton–Raphson Methodc","authors":"Prabhu Sundaramoorthy;Arun Vijayakumar;Kuppapillai Rajkumar;Jamuna Ponnusamy;Gokul Chandrasekaran;Vijayakumar Madhaiyan","doi":"10.1109/ICJECE.2024.3370973","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3370973","url":null,"abstract":"The permanent magnet synchronous motor (PMSM) has a more efficiency, high torque density, and high power density, but it suffers from torque ripple. This article describes the electromagnetic (EM) behavior of M19 29Ga material assists PMSM for 310 V, 5 A, and 1500 r/min. In addition, various materials as Losil 34050, Arnon 5, 50M290, M19 USS Transformer 72–29 gauge, and TR80 USS Transformer 80–29 gauge incorporated PMSM and which material has superiority, and with the superiority kept constant, changed the various magnet materials. The EEC 26-T350, MQP-14–12 835995, N45M, Recoma 22, Samarium Cobalt 20/30, Vacodym 890TP, and Vacomax 240 incorporated PMSM also investigated for EM finite-element analysis. The results of this study of the variable as torque ripple forecast the highest torque (\u0000<inline-formula> <tex-math>$T_{mathrm {max}})$ </tex-math></inline-formula>\u0000, lowest power output (\u0000<inline-formula> <tex-math>$T_{mathrm {min}})$ </tex-math></inline-formula>\u0000, and overall torque (\u0000<inline-formula> <tex-math>$T_{mathrm {avg}})$ </tex-math></inline-formula>\u0000. The superior motor among various materials unified PMSM by its ripple and field characteristics. The outcomings of the modeled motor are validated with numerical equations.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"105-110"},"PeriodicalIF":0.0,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140948906","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

Design of Novel Single-Frame Dual-Voltage (28-/270-V DC) Permanent Magnet Generator 新型单框架双电压（28-/270-V DC）永磁发电机的设计

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-04-24 DOI: 10.1109/ICJECE.2024.3370589

Jaishankar Chinnachamy;Hosimin Thilagar Srinivasan

引用次数: 0

Visual Geometry Group Network for Flexible Printed Circuit Board Surface Defect Classification 用于柔性印刷电路板表面缺陷分类的视觉几何群组网络

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-04-19 DOI: 10.1109/ICJECE.2024.3368454

Jiazheng Sheng;Siyi Guo;Hui Li;Shengnan Shen;Yikai Zhang;Yicang Huang;Bin Sun;Jian Wang

{"title":"Visual Geometry Group Network for Flexible Printed Circuit Board Surface Defect Classification","authors":"Jiazheng Sheng;Siyi Guo;Hui Li;Shengnan Shen;Yikai Zhang;Yicang Huang;Bin Sun;Jian Wang","doi":"10.1109/ICJECE.2024.3368454","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3368454","url":null,"abstract":"Convolutional neural networks (CNNs) have drawn huge interest in the field of surface defect classification. During the production of flexible printed circuit boards (FPCBs), only a limited number of images of surface defects can be obtained. FPCB surface defect datasets have small samples and severe imbalances, which can significantly affect defect classification accuracy. Hence, this article presented a lightweight visual geometry group (L-VGG), developed by modifying the classical VGG16 network structure. The L-VGG network was optimized using L2 regularization and sample weighting, which alleviated the over-fitting phenomenon caused by small samples and improved validation accuracy. In addition, the differences among the classification accuracies of different defect images caused by imbalanced datasets were significantly reduced. The training time of the proposed L-VGG network was equivalent to 83.84% and 91.94% compression of the traditional VGG16 and ResNet18 networks, respectively. The dataset augmentation with generated images further mitigates the overfitting phenomenon caused by the small sample problem to some extent, and finally achieves a validation accuracy of 94.20%.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"70-77"},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140651108","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