{"title":"奇异摄动与大规模电力系统稳定性","authors":"M. Pai, P. Sauer, K. Khorasani","doi":"10.1109/CDC.1984.272294","DOIUrl":null,"url":null,"abstract":"Stability of large scale power systems using direct methods has been investigated either through reduced order models (e.g. one machine-infinite bus equivalent) or by decomposition. The latter method employs artificial mathematical methods for decomposition. In either method the physical picture gets lost and the analysis has to be repated for every disturbance. In this paper we propose a new approach based on singular perturbation and time scale decomposition. The system Lyapunov function gets split into a \"slow\" Lyapunov function and a number of \"fast\" Lyapunov functions each for a slowly coherent area. The weighted sum of these Lyapunov functions gets improved in quality as higher order corrections are taken into account. The decomposition is invariant with respect to the disturbance and thus offers a new approach to stability analysis of large scale power systems.","PeriodicalId":269680,"journal":{"name":"The 23rd IEEE Conference on Decision and Control","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1984-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Singular perturbations and large scale power system stability\",\"authors\":\"M. Pai, P. Sauer, K. Khorasani\",\"doi\":\"10.1109/CDC.1984.272294\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stability of large scale power systems using direct methods has been investigated either through reduced order models (e.g. one machine-infinite bus equivalent) or by decomposition. The latter method employs artificial mathematical methods for decomposition. In either method the physical picture gets lost and the analysis has to be repated for every disturbance. In this paper we propose a new approach based on singular perturbation and time scale decomposition. The system Lyapunov function gets split into a \\\"slow\\\" Lyapunov function and a number of \\\"fast\\\" Lyapunov functions each for a slowly coherent area. The weighted sum of these Lyapunov functions gets improved in quality as higher order corrections are taken into account. The decomposition is invariant with respect to the disturbance and thus offers a new approach to stability analysis of large scale power systems.\",\"PeriodicalId\":269680,\"journal\":{\"name\":\"The 23rd IEEE Conference on Decision and Control\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1984-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 23rd IEEE Conference on Decision and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1984.272294\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 23rd IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1984.272294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Singular perturbations and large scale power system stability
Stability of large scale power systems using direct methods has been investigated either through reduced order models (e.g. one machine-infinite bus equivalent) or by decomposition. The latter method employs artificial mathematical methods for decomposition. In either method the physical picture gets lost and the analysis has to be repated for every disturbance. In this paper we propose a new approach based on singular perturbation and time scale decomposition. The system Lyapunov function gets split into a "slow" Lyapunov function and a number of "fast" Lyapunov functions each for a slowly coherent area. The weighted sum of these Lyapunov functions gets improved in quality as higher order corrections are taken into account. The decomposition is invariant with respect to the disturbance and thus offers a new approach to stability analysis of large scale power systems.