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

Panagiotis N. Papadopoulos; Jovica V. Milanović; Pratyasa Bhui; Nilanjan Senroy

doi:10.1109/ISGTEurope.2016.7856236

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

Panagiotis N. Papadopoulos, Jovica V. Milanović, Pratyasa Bhui, Nilanjan Senroy

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

5 Citations (Scopus)

38 Downloads (Pure)

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.

Original language	English
Title of host publication	IEEE PES Innovative Smart Grid Technologies, Europe
Subtitle of host publication	October, 9-12, 2016, Ljubljana
Place of Publication	Piscataway, NJ
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9781509033584
DOIs	https://doi.org/10.1109/ISGTEurope.2016.7856236
Publication status	Published - 16 Feb 2017
Event	2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016 - Ljubljana, Slovenia Duration: 9 Oct 2016 → 12 Oct 2016

Conference

Conference	2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016
Country/Territory	Slovenia
City	Ljubljana
Period	9/10/16 → 12/10/16

Keywords

clustering
k-means
recurrence quantification analysis
renewable energy resources

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10.1109/ISGTEurope.2016.7856236

Papadopoulos-etal-ISGT2016-Feasibility-study-of-applicability-of-recurrence-quantification-analysisAccepted author manuscript, 1.27 MB

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title = "Feasibility study of applicability of recurrence quantification analysis for clustering of power system dynamic responses",

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.",

keywords = "clustering, k-means, recurrence quantification analysis, renewable energy resources",

author = "Papadopoulos, {Panagiotis N.} and Milanovi{\'c}, {Jovica V.} and Pratyasa Bhui and Nilanjan Senroy",

note = "{\textcopyright} 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.; 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016 ; Conference date: 09-10-2016 Through 12-10-2016",

year = "2017",

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day = "16",

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language = "English",

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Papadopoulos, PN, Milanović, JV, Bhui, P & Senroy, N 2017, Feasibility study of applicability of recurrence quantification analysis for clustering of power system dynamic responses. in IEEE PES Innovative Smart Grid Technologies, Europe: October, 9-12, 2016, Ljubljana., 7856236, IEEE, Piscataway, NJ, 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2016, Ljubljana, Slovenia, 9/10/16. https://doi.org/10.1109/ISGTEurope.2016.7856236

Feasibility study of applicability of recurrence quantification analysis for clustering of power system dynamic responses. / Papadopoulos, Panagiotis N.; Milanović, Jovica V.; Bhui, Pratyasa et al.
IEEE PES Innovative Smart Grid Technologies, Europe: October, 9-12, 2016, Ljubljana. Piscataway, NJ: IEEE, 2017. 7856236.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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AU - Papadopoulos, Panagiotis N.

AU - Milanović, Jovica V.

AU - Bhui, Pratyasa

AU - Senroy, Nilanjan

N1 - © 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.

PY - 2017/2/16

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N2 - 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.

AB - 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.

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KW - k-means

KW - recurrence quantification analysis

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ER -

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

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