{"title":"基于ART2的电力系统节点电压概率诊断","authors":"H. Mori, N. Kanda","doi":"10.1109/ANN.1993.264294","DOIUrl":null,"url":null,"abstract":"This paper proposes a new method for nodal voltage diagnosis in power systems using a self-organization artificial neural network. ART2 is utilized to classify power system conditions. A probability voltage security index is evaluated by the resulting classification. The proposed method is used for tracking the voltage profile continuously.<<ETX>>","PeriodicalId":121897,"journal":{"name":"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Probabilistic diagnosis of power system nodal voltages with ART2\",\"authors\":\"H. Mori, N. Kanda\",\"doi\":\"10.1109/ANN.1993.264294\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a new method for nodal voltage diagnosis in power systems using a self-organization artificial neural network. ART2 is utilized to classify power system conditions. A probability voltage security index is evaluated by the resulting classification. The proposed method is used for tracking the voltage profile continuously.<<ETX>>\",\"PeriodicalId\":121897,\"journal\":{\"name\":\"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANN.1993.264294\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANN.1993.264294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Probabilistic diagnosis of power system nodal voltages with ART2
This paper proposes a new method for nodal voltage diagnosis in power systems using a self-organization artificial neural network. ART2 is utilized to classify power system conditions. A probability voltage security index is evaluated by the resulting classification. The proposed method is used for tracking the voltage profile continuously.<>