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- W2348587640 abstract "In stability analysis,only particular areas need to be further detailed simulation and analyzed.It is espected that systems can be simplified and without employing great programming effort or extensive time-consuming computations.Dynamic Equivalent as a modeling method can reduce the huge workload when be used in analyzing the large interconnected power system.On the other hand,recurrent artificial neural netwoks(ANN) has good ability to deal with the complicated nonlinear problem and series parallel model(SPM) can assure the stability and astringency of the identified model.In this paper,dynamic equivalent for transmission networks in the interconnected power systems using the recurrent artificial neural netwoks(ANN) is introduced and series parallel model(SPM) structure is chosen to identify equivalent model.The approach depends on measurements of the boundary nodes,need not to postulate any fixed dynamic model in advance.The weighting parameters and structure of ANN will define the parameters and structure of the external areas.This new approach is used to simplify the 39 nodes network of IEEE,the results show that the proposed method can capture the dynamic character of the original system,and show the accuracy of the equivalent model and the validity of the proposed method." @default.
- W2348587640 created "2016-06-24" @default.
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- W2348587640 date "2008-01-01" @default.
- W2348587640 modified "2023-10-11" @default.
- W2348587640 title "Recurrent Neural Network-based Dynamic Equivalencing and Identification" @default.
- W2348587640 hasPublicationYear "2008" @default.
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