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Probabilistic Framework for Online Identification of Dynamic Behavior of Power Systems With Renewable Generation.
- Source :
- IEEE Transactions on Power Systems; Jan2018, Vol. 33 Issue 1, p45-54, 10p
- Publication Year :
- 2018
-
Abstract
- The paper introduces a probabilistic framework for online identification of post fault dynamic behavior of power systems with renewable generation. The framework is based on decision trees and hierarchical clustering and incorporates uncertainties associated with network operating conditions, topology changes, faults, and renewable generation. In addition to identifying unstable generator groups, the developed clustering methodology also facilitates identification of the sequence in which the groups lose synchronism. The framework is illustrated on a modified version of the IEEE 68 bus test network incorporating significant portion of renewable generation. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 08858950
- Volume :
- 33
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Power Systems
- Publication Type :
- Academic Journal
- Accession number :
- 126964046
- Full Text :
- https://doi.org/10.1109/TPWRS.2017.2688446