{"title":"面向智能输电网的智能故障定位算法的开发、测试与比较","authors":"Neelesh Ramseebaluck, K. Awodele","doi":"10.1109/ROBOMECH.2019.8704852","DOIUrl":null,"url":null,"abstract":"This paper presents the design and implementation of three different algorithms used to estimate the location of electrical faults along a transmission line. Firstly, an impedance-based algorithm, which is dependent on the sequence components of the fault voltages and currents, is presented. Secondly, a travelling wave-based fault location algorithm (FLA) is investigated, and it relies on intensive signal processing techniques such as the Discrete Wavelet Transform to estimate the fault location. Lastly, the third algorithm integrates the wavelet transform with artificial intelligence to achieve the same objective. The transmission line is modelled for each algorithm using MATLAB/Simulink to get the required post-fault line parameters. Simulations are carried out under different fault conditions and the results are analysed. It is concluded that all three algorithms are effective for single phase-to-ground and line-to-line faults. The algorithm based on artificial intelligence provided the most conclusive results.","PeriodicalId":344332,"journal":{"name":"2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Development, Testing and Comparison of Smart Fault Location Algorithms for Smart Transmission Grids\",\"authors\":\"Neelesh Ramseebaluck, K. Awodele\",\"doi\":\"10.1109/ROBOMECH.2019.8704852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the design and implementation of three different algorithms used to estimate the location of electrical faults along a transmission line. Firstly, an impedance-based algorithm, which is dependent on the sequence components of the fault voltages and currents, is presented. Secondly, a travelling wave-based fault location algorithm (FLA) is investigated, and it relies on intensive signal processing techniques such as the Discrete Wavelet Transform to estimate the fault location. Lastly, the third algorithm integrates the wavelet transform with artificial intelligence to achieve the same objective. The transmission line is modelled for each algorithm using MATLAB/Simulink to get the required post-fault line parameters. Simulations are carried out under different fault conditions and the results are analysed. It is concluded that all three algorithms are effective for single phase-to-ground and line-to-line faults. The algorithm based on artificial intelligence provided the most conclusive results.\",\"PeriodicalId\":344332,\"journal\":{\"name\":\"2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA)\",\"volume\":\"150 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROBOMECH.2019.8704852\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOMECH.2019.8704852","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development, Testing and Comparison of Smart Fault Location Algorithms for Smart Transmission Grids
This paper presents the design and implementation of three different algorithms used to estimate the location of electrical faults along a transmission line. Firstly, an impedance-based algorithm, which is dependent on the sequence components of the fault voltages and currents, is presented. Secondly, a travelling wave-based fault location algorithm (FLA) is investigated, and it relies on intensive signal processing techniques such as the Discrete Wavelet Transform to estimate the fault location. Lastly, the third algorithm integrates the wavelet transform with artificial intelligence to achieve the same objective. The transmission line is modelled for each algorithm using MATLAB/Simulink to get the required post-fault line parameters. Simulations are carried out under different fault conditions and the results are analysed. It is concluded that all three algorithms are effective for single phase-to-ground and line-to-line faults. The algorithm based on artificial intelligence provided the most conclusive results.