{"title":"A review of intelligent verification system distributiontautomationtterminalinal based on artificial intelligealgorithmsthms","authors":"Hongwei Li, Qiyuan Xu, Qilin Wang, Bin Tang","doi":"10.1186/s13677-023-00527-2","DOIUrl":null,"url":null,"abstract":"Abstract Artificial intelligence (AI) plays a key role in the distribution automation system (DAS). By using artificial intelligence technology, it is possible to intelligently verify and monitor distribution automation terminals, improve their safety and reliability, and reduce power system operating and maintenance costs. At present, researchers are exploring a variety of application methods and algorithms of the distribution automation terminal intelligent acceptance system based on artificial intelligence, such as machine learning, deep learning and expert systems, and have made significant progress. This paper comprehensively reviews the existing research on the application of artificial intelligence technology in distribution automation systems, including fault detection, network reconfiguration, load forecasting, and network security. It undertakes a thorough examination and summarization of the major research achievements in the field of distribution automation systems over the past few years, while also analyzing the challenges that this field confronts. Moreover, this study elaborates extensively on the diverse applications of AI technology within distribution automation systems, providing a detailed comparative analysis of various algorithms and methodologies from multiple classification perspectives. The primary aim of this endeavor is to furnish valuable insights for researchers and practitioners in this domain, thereby fostering the advancement and innovation of distribution automation systems.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"76 1","pages":"0"},"PeriodicalIF":3.7000,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cloud Computing-Advances Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s13677-023-00527-2","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Artificial intelligence (AI) plays a key role in the distribution automation system (DAS). By using artificial intelligence technology, it is possible to intelligently verify and monitor distribution automation terminals, improve their safety and reliability, and reduce power system operating and maintenance costs. At present, researchers are exploring a variety of application methods and algorithms of the distribution automation terminal intelligent acceptance system based on artificial intelligence, such as machine learning, deep learning and expert systems, and have made significant progress. This paper comprehensively reviews the existing research on the application of artificial intelligence technology in distribution automation systems, including fault detection, network reconfiguration, load forecasting, and network security. It undertakes a thorough examination and summarization of the major research achievements in the field of distribution automation systems over the past few years, while also analyzing the challenges that this field confronts. Moreover, this study elaborates extensively on the diverse applications of AI technology within distribution automation systems, providing a detailed comparative analysis of various algorithms and methodologies from multiple classification perspectives. The primary aim of this endeavor is to furnish valuable insights for researchers and practitioners in this domain, thereby fostering the advancement and innovation of distribution automation systems.
期刊介绍:
The Journal of Cloud Computing: Advances, Systems and Applications (JoCCASA) will publish research articles on all aspects of Cloud Computing. Principally, articles will address topics that are core to Cloud Computing, focusing on the Cloud applications, the Cloud systems, and the advances that will lead to the Clouds of the future. Comprehensive review and survey articles that offer up new insights, and lay the foundations for further exploratory and experimental work, are also relevant.