{"title":"面向大规模并行动态状态估计的同步发电机详细建模","authors":"H. Karimipour, V. Dinavahi","doi":"10.1109/NAPS.2014.6965417","DOIUrl":null,"url":null,"abstract":"Synchronous generators are normally represented in a simplified fashion to reduce computational complexity in dynamic state estimation (DSE). In this paper a dynamic state estimator for a sixth-order synchronous generator model was developed on the massively parallel graphic processing units (GPU) to provide detailed and accurate Extended Kalman Filter (EKF) based estimation of the generator states. The estimation results are compared with the time domain simulation results on the CPU to demonstrate the accuracy of the proposed method. Also a speed-up of 10.02 for a 5120 generator system is reported.","PeriodicalId":421766,"journal":{"name":"2014 North American Power Symposium (NAPS)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"On detailed synchronous generator modeling for massively parallel dynamic state estimation\",\"authors\":\"H. Karimipour, V. Dinavahi\",\"doi\":\"10.1109/NAPS.2014.6965417\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Synchronous generators are normally represented in a simplified fashion to reduce computational complexity in dynamic state estimation (DSE). In this paper a dynamic state estimator for a sixth-order synchronous generator model was developed on the massively parallel graphic processing units (GPU) to provide detailed and accurate Extended Kalman Filter (EKF) based estimation of the generator states. The estimation results are compared with the time domain simulation results on the CPU to demonstrate the accuracy of the proposed method. Also a speed-up of 10.02 for a 5120 generator system is reported.\",\"PeriodicalId\":421766,\"journal\":{\"name\":\"2014 North American Power Symposium (NAPS)\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 North American Power Symposium (NAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAPS.2014.6965417\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS.2014.6965417","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On detailed synchronous generator modeling for massively parallel dynamic state estimation
Synchronous generators are normally represented in a simplified fashion to reduce computational complexity in dynamic state estimation (DSE). In this paper a dynamic state estimator for a sixth-order synchronous generator model was developed on the massively parallel graphic processing units (GPU) to provide detailed and accurate Extended Kalman Filter (EKF) based estimation of the generator states. The estimation results are compared with the time domain simulation results on the CPU to demonstrate the accuracy of the proposed method. Also a speed-up of 10.02 for a 5120 generator system is reported.
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