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}
G. Mariammal;A. Suruliandi;Z. Stamenkovic;S. P. Raja
{"title":"A Novel Ensemble Machine Learning Algorithm for Predicting the Suitable Crop to Cultivate Based on Soil and Environment Characteristics","authors":"G. Mariammal;A. Suruliandi;Z. Stamenkovic;S. P. Raja","doi":"10.1109/ICJECE.2024.3400048","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3400048","url":null,"abstract":"Research in agriculture is a promising field, and crop prediction for particular land areas is especially critical to agriculture. Such prediction depends on the soil, minerals, and environment, the last of which has been short-changed by changing climatic conditions. Consequently, crop prediction for a particular zone presents difficulties for farmers. This is where machine learning (ML) steps in with techniques that are widely applied in agriculture. This work proposes a weighted stacked ensemble (WSE) method for the crop prediction process. It combines two base learners or classifiers to construct the WSE, which is a single predictive ensemble model, using weighted instances. The experimental outcomes show that the proposed WSE outperforms other classification and ensemble techniques in terms of improved crop prediction accuracy.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"127-135"},"PeriodicalIF":2.1,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013341","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}
{"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}
{"title":"IEEE Canadian Journal of Electrical and Computer Engineering","authors":"","doi":"10.1109/ICJECE.2024.3379100","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3379100","url":null,"abstract":"","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10557783","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141326286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"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}
{"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}
{"title":"Design of Novel Single-Frame Dual-Voltage (28-/270-V DC) Permanent Magnet Generator","authors":"Jaishankar Chinnachamy;Hosimin Thilagar Srinivasan","doi":"10.1109/ICJECE.2024.3370589","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3370589","url":null,"abstract":"Armored fighting vehicles (AFVs) of the future will be equipped with electrical drives and many electronic systems, such as computers, sensors, displays, actuators, and other sensitive electronics. Electric drive systems have the potential to substantially increase the efficiency of combat vehicles. The demand for electrical power in AFV has grown beyond the limits of that can be managed by the existing 28-V dc system. There is a necessity to switch from the single electrical bus configuration to a dual bus voltage configuration. This article describes the design procedure of a novel permanent magnet (PM) dual voltage generator for simultaneously providing power at two different voltages. Test results are presented and discussed.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"95-104"},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140948991","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}
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}
{"title":"Fault Restoration Strategy for Multienergy Distribution Systems With Consideration of Resilience Enhancement","authors":"Tianchi Tong;Yuwei Yan;Yuan Xia","doi":"10.1109/ICJECE.2024.3380062","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3380062","url":null,"abstract":"The traditional methods of improving the resilience of the distribution network have certain limitations, while the integrated energy system makes the grid tightly coupled with other energy systems, providing a new way to improve the resilience of the distribution network. Aiming at the problem of large-scale power outages caused by frequent extreme weather events in recent years, this article proposes a fault recovery strategy for multienergy distribution systems considering enhanced resilience. For the first time, this article considers the load conversion of multienergy forms on the demand side in the process of distribution network restoration. During the period from the occurrence of multiline faults in the distribution network to the fault repaired, this article adopts reconstruction and island division, and cooperates with the multienergy form load conversion on the demand side to reduce the loss of electrical loads. In this article, the calculation example of the modified 69 bus system shows the method adopted in this article reduces the load loss rate by about 30% compared with the traditional scheme, which verifies that load conversion of multienergy forms on the demand side can effectively alleviate the problem of insufficient energy supply when the traditional distributed generation (DG) is used to construct island.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"87-94"},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140651127","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}
Bashar Abbas Fadheel;Noor Izzri Abdul Wahab;Ali Jafer Mahdi;Mohd Amran Bin Mohd Radzi;Azura Binti Che Soh;Hussein Mohammed Ridha;Veerapandiyan Veerasamy
{"title":"Optimal Tuning of Virtual Inertia Control for Frequency Regulation of Microgrid","authors":"Bashar Abbas Fadheel;Noor Izzri Abdul Wahab;Ali Jafer Mahdi;Mohd Amran Bin Mohd Radzi;Azura Binti Che Soh;Hussein Mohammed Ridha;Veerapandiyan Veerasamy","doi":"10.1109/ICJECE.2024.3351152","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3351152","url":null,"abstract":"The integration of renewable energy sources in modern microgrid power systems has a significant impact on frequency stability due to reducing inertia and damping coefficient. This article employs a virtual inertia control (VIC) based on frequency deviation derivatives to emulate the system inertia and damping coefficient characteristics of traditional synchronous generators. Coordination between the global controller (load frequency control) and the VIC is implemented. The parameters of both the secondary and virtual control are tuned using a novel hybrid sparrow search algorithm with mountain gazelle optimizer algorithm. The simulation results demonstrate a substantial improvement in mitigating the low inertia of the power system when exposed to consecutive rapid load changes, utilizing the suggested algorithm on comparing with the hybrid sparrow search algorithm based on grey wolf optimizer.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"60-69"},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140651132","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}