Measurement Based Method for Online Characterization of Generator Dynamic Behaviour in Systems With Renewable Generation

This paper introduces a two-step methodology for online identification of the participation of generators in power system oscillatory modes, based on measured responses. The dominant modes in generator measured responses are initially identified using a mode identification technique and then introdu...

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Bibliographic Details
Published inIEEE transactions on power systems Vol. 33; no. 6; pp. 6466 - 6475
Main Authors Papadopoulos, Panagiotis N., Papadopoulos, Theofilos A., Chrysochos, Andreas I., Milanovic, Jovica V.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Clustering
Clustering algorithms
Feature extraction
Generators
online dynamic security assessment
Power system dynamics
Power system stability
Renewable energy sources
renewable generation
uncertainties
Unsupervised learning
unsupervised machine learning
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Summary:This paper introduces a two-step methodology for online identification of the participation of generators in power system oscillatory modes, based on measured responses. The dominant modes in generator measured responses are initially identified using a mode identification technique and then introduced, in the next step, as input into a clustering algorithm. Critical groups of generators that exhibit poorly or negatively damped oscillations are identified, in order to enable corrective control actions and stabilize the system. The uncertainties associated with the operation of modern power systems with renewable energy sources (RESs) are investigated as well as the impact of the dynamic behavior of power electronic interfaced RESs.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2018.2830817