Probabilistic framework for online identification of dynamic behavior of power systems with renewable generation
Papadopoulos, Panagiotis N. and Guo, Tingyan and Milanović, Jovica V. (2018) Probabilistic framework for online identification of dynamic behavior of power systems with renewable generation. IEEE Transactions on Power Systems, 33 (1). pp. 45-54. ISSN 0885-8950 (https://doi.org/10.1109/TPWRS.2017.2688446)
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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.
ORCID iDs
Papadopoulos, Panagiotis N. ORCID: https://orcid.org/0000-0001-7343-2590, Guo, Tingyan and Milanović, Jovica V.;-
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Item type: Article ID code: 63126 Dates: DateEvent31 January 2018Published28 March 2017Published Online23 March 2017AcceptedNotes: (c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 01 Feb 2018 10:01 Last modified: 04 Oct 2024 00:28 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/63126