Feasibility study of applicability of recurrence quantification analysis for clustering of power system dynamic responses

Papadopoulos, Panagiotis N. and Milanović, Jovica V. and Bhui, Pratyasa and Senroy, Nilanjan; (2017) Feasibility study of applicability of recurrence quantification analysis for clustering of power system dynamic responses. In: IEEE PES Innovative Smart Grid Technologies, Europe. IEEE, SVN. ISBN 9781509033584 (https://doi.org/10.1109/ISGTEurope.2016.7856236)

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Abstract

A methodology based on Recurrence Quantification Analysis (RQA) for the clustering of generator dynamic behavior is presented. RQA is a nonlinear data analysis method, which is used in this paper to extract features from measured generator rotor angle responses that can be used to cluster generators in groups with similar oscillatory behavior. The possibility of extracting features relevant to damping and frequency of oscillations present in power systems is studied. The k-Means clustering algorithm is further used to cluster the generator responses in groups exhibiting well or poorly damped oscillations, based on the extracted features from RQA. The effectiveness of RQA is investigated using simulated responses from a modified version of the IEEE 68 bus network, including renewable energy resources.

  • Item type:Book Section
    ID code:62466
    Dates:
    Date
    Event
    16 February 2017
    Published
    Notes:© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component 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:29 Nov 2017 14:10
    Last modified:08 Apr 2024 13:43
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/62466
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