Shankar B B, Harshitha Bhat, S. Poornima, R. Bharanidharan, M. Sridharan, Ayan Banik
{"title":"Conventional Protection of Power Transformers at Distribution Grid Side using Artificial Neural Network","authors":"Shankar B B, Harshitha Bhat, S. Poornima, R. Bharanidharan, M. Sridharan, Ayan Banik","doi":"10.1109/ICEARS56392.2023.10085631","DOIUrl":null,"url":null,"abstract":"A smart grid has a complex topology which includes multiple diversity of components. Power interruption due to faulty components has become a major issue in smart grid. It is difficult to obtain warning for faults that occur in each component. Also, the security of smart grid is under threat due to these unnoticeable faults. To improve the security of smart grid, it is essential to develop an efficient fault detection technique. Hence, an attempt is made to determine the transmission line faults that occur in smart grids using Artificial Neural Networks. The proposal is simulated using MATLAB SIMULINK and the results confirm the supremacy of the proposal over other approaches.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEARS56392.2023.10085631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A smart grid has a complex topology which includes multiple diversity of components. Power interruption due to faulty components has become a major issue in smart grid. It is difficult to obtain warning for faults that occur in each component. Also, the security of smart grid is under threat due to these unnoticeable faults. To improve the security of smart grid, it is essential to develop an efficient fault detection technique. Hence, an attempt is made to determine the transmission line faults that occur in smart grids using Artificial Neural Networks. The proposal is simulated using MATLAB SIMULINK and the results confirm the supremacy of the proposal over other approaches.
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