Detection and Analysis of Electromechanical Oscillation in Power Systems with Low-Sampled Data Using Modal Analysis Methods

Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore, oscillation monitoring systems in real-time are of critical importance to detect the danger of poorly damped oscillations. For the detection and...

Full description

Saved in:
Bibliographic Details
Published inJournal of electrical engineering & technology Vol. 15; no. 5; pp. 1999 - 2006
Main Authors Baek, Jong-Oh, Kim, Soobae
Format Journal Article
LanguageEnglish
Published Singapore Springer Singapore 01.09.2020
대한전기학회
Subjects
Online AccessGet full text
ISSN1975-0102
2093-7423
DOI10.1007/s42835-020-00471-0

Cover

Abstract Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore, oscillation monitoring systems in real-time are of critical importance to detect the danger of poorly damped oscillations. For the detection and analysis of the oscillations, high-temporal-resolution measurements are required according to the Nyquist theorem. This paper proposes a novel algorithm for the identification of electromechanical oscillations using low-sampled data such as supervisory control and data acquisition (SCADA) measurements. Methods The lack of temporal resolution of the data is compensated by using low-sampled data sets at multiple different locations. At a target location, a high-sampled data-signal can be reconstructed using mode shape information obtained from model-based modal analysis. The variable projection method is then used to detect oscillations and estimate oscillation components including frequency and damping ratio. Results Case studies based on practical Korean power systems are presented to evaluate the performance of the proposed method. Simulation results show that the proposed method can detect and identify electromechanical oscillations with low-sampled data.
AbstractList Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore, oscillation monitoring systems in real-time are of critical importance to detect the danger of poorly damped oscillations. For the detection and analysis of the oscillations, high-temporal-resolution measurements are required according to the Nyquist theorem. This paper proposes a novel algorithm for the identification of electromechanical oscillations using low-sampled data such as supervisory control and data acquisition (SCADA) measurements. Methods The lack of temporal resolution of the data is compensated by using low-sampled data sets at multiple different locations. At a target location, a high-sampled data-signal can be reconstructed using mode shape information obtained from model-based modal analysis. The variable projection method is then used to detect oscillations and estimate oscillation components including frequency and damping ratio. Results Case studies based on practical Korean power systems are presented to evaluate the performance of the proposed method. Simulation results show that the proposed method can detect and identify electromechanical oscillations with low-sampled data.
Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore, oscillation monitoring systems in real-time are of critical importance to detect the danger of poorly damped oscillations. For the detection and analysis of the oscillations, high-temporal-resolution measurements are required according to the Nyquist theorem. This paper proposes a novel algorithm for the identifi cation of electromechanical oscillations using low-sampled data such as supervisory control and data acquisition (SCADA) measurements. Methods The lack of temporal resolution of the data is compensated by using low-sampled data sets at multiple diff erent locations. At a target location, a high-sampled data-signal can be reconstructed using mode shape information obtained from model-based modal analysis. The variable projection method is then used to detect oscillations and estimate oscillation components including frequency and damping ratio. Results Case studies based on practical Korean power systems are presented to evaluate the performance of the proposed method. Simulation results show that the proposed method can detect and identify electromechanical oscillations with lowsampled data. KCI Citation Count: 0
Author Kim, Soobae
Baek, Jong-Oh
Author_xml – sequence: 1
  givenname: Jong-Oh
  surname: Baek
  fullname: Baek, Jong-Oh
  organization: Department of Electrical Engineering, Kyungpook National University
– sequence: 2
  givenname: Soobae
  orcidid: 0000-0001-9945-1765
  surname: Kim
  fullname: Kim, Soobae
  email: soobae.kim@knu.ac.kr
  organization: Department of Electrical Engineering, Kyungpook National University
BackLink https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002622262$$DAccess content in National Research Foundation of Korea (NRF)
BookMark eNp9kMtOwzAQRS0EEuXxA6y8ZREY23GcLCveUhGIx9qaxHZrSG1kB1UVP09oEUtWs7jnXGnuAdkNMVhCThicMQB1nkteC1kAhwKgVKyAHTLh0IhClVzskglr1Bgz4PvkIOc3gIqBFBPydWkH2w0-BorB0GnAfp19ptHRq34MUlzaboHBd9jTh9z5vscN7QN9jCub6PM6D3aZ6coPCzqLq-IZlx-9NfQSB6Sv2Yc5vY9m1P_K7-2wiCYfkT2HfbbHv_eQvF5fvVzcFrOHm7uL6azouKqGgkOJtXNN7bAEJTtZV60xSmFjTCuxciWrBaKtROUsF3XrGmVkw1nb1qaplDgkp9vekJx-77yO6Dd3HvV70tOnlzvdyEpJIUeWb9kuxZyTdfoj-SWmtWagf6bW26n1OLXeTK1hlMRWyiMc5jbpt_iZxm_zf9Y3LmOExQ
Cites_doi 10.24251/HICSS.2017.384
10.1109/59.49089
10.1109/59.119229
10.1088/0266-5611/19/2/201
10.1109/TPWRS.2014.2336859
10.1109/TPWRS.2015.2404804
10.1109/TPWRS.2014.2309635
10.1137/0710036
10.1109/TPWRS.2015.2439811
10.1049/iet-gtd:20050243
10.1109/TPWRS.2017.2767105
10.1109/TPWRS.2011.2169284
10.1109/TPWRS.2010.2046503
10.1007/978-1-4615-4561-3
10.1109/TPWRS.2015.2441109
ContentType Journal Article
Copyright The Korean Institute of Electrical Engineers 2020
Copyright_xml – notice: The Korean Institute of Electrical Engineers 2020
DBID AAYXX
CITATION
ACYCR
DOI 10.1007/s42835-020-00471-0
DatabaseName CrossRef
Korean Citation Index
DatabaseTitle CrossRef
DatabaseTitleList

DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 2093-7423
EndPage 2006
ExternalDocumentID oai_kci_go_kr_ARTI_9567535
10_1007_s42835_020_00471_0
GrantInformation_xml – fundername: National Research Foundation of Korea (NRF) funded by the Ministry of Education
  grantid: 2018R1D1A1B07043818
  funderid: http://dx.doi.org/10.13039/501100002701
GroupedDBID -~X
.UV
0R~
2WC
406
9ZL
AACDK
AAHNG
AAJBT
AASML
AATNV
AAUYE
AAYYP
ABAKF
ABECU
ABFTV
ABJNI
ABKCH
ABMQK
ABTEG
ABTKH
ABTMW
ACAOD
ACDTI
ACHSB
ACOKC
ACPIV
ACZOJ
ADKNI
ADTPH
ADURQ
ADYFF
AEFQL
AEMSY
AENEX
AESKC
AFBBN
AFQWF
AGDGC
AGMZJ
AGQEE
AIGIU
AILAN
AITGF
AJZVZ
ALMA_UNASSIGNED_HOLDINGS
AMKLP
AMXSW
AMYLF
AXYYD
BGNMA
CSCUP
DBRKI
DPUIP
EBLON
EBS
EJD
FIGPU
FNLPD
FRJ
GGCAI
GW5
IKXTQ
IWAJR
JDI
JZLTJ
KOV
KVFHK
LLZTM
M4Y
NPVJJ
NQJWS
NU0
OK1
PT4
ROL
RSV
SJYHP
SNE
SNPRN
SOHCF
SOJ
SRMVM
SSLCW
TDB
UOJIU
UTJUX
VEKWB
VFIZW
ZMTXR
AAYXX
ABBRH
ABDBE
ABFSG
ACSTC
AEZWR
AFDZB
AFHIU
AFOHR
AHPBZ
AHWEU
AIXLP
ATHPR
AYFIA
CITATION
AAFGU
AAYFA
ABFGW
ABKAS
ACBMV
ACBRV
ACBYP
ACIGE
ACIPQ
ACTTH
ACVWB
ACWMK
ACYCR
ADMDM
ADOXG
AEFTE
AESTI
AEVTX
AFNRJ
AGGBP
AIMYW
AJDOV
AKQUC
Z7R
Z7S
Z7X
Z88
ID FETCH-LOGICAL-c276t-204a8ff98fa4075c586bdd77a9ddb5a6f4183aae636fe238bf97d5921bb8d9673
ISSN 1975-0102
IngestDate Tue Nov 21 21:20:32 EST 2023
Tue Jul 01 00:40:50 EDT 2025
Fri Feb 21 02:36:05 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 5
Keywords Electromechanical oscillations
Detection and analysis of oscillations
Korean power systems
Variable projection method
Low-sampled data
Model-based modal analysis
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c276t-204a8ff98fa4075c586bdd77a9ddb5a6f4183aae636fe238bf97d5921bb8d9673
ORCID 0000-0001-9945-1765
PageCount 8
ParticipantIDs nrf_kci_oai_kci_go_kr_ARTI_9567535
crossref_primary_10_1007_s42835_020_00471_0
springer_journals_10_1007_s42835_020_00471_0
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 20200900
2020-09-00
2020-09
PublicationDateYYYYMMDD 2020-09-01
PublicationDate_xml – month: 9
  year: 2020
  text: 20200900
PublicationDecade 2020
PublicationPlace Singapore
PublicationPlace_xml – name: Singapore
PublicationTitle Journal of electrical engineering & technology
PublicationTitleAbbrev J. Electr. Eng. Technol
PublicationYear 2020
Publisher Springer Singapore
대한전기학회
Publisher_xml – name: Springer Singapore
– name: 대한전기학회
References KundurPBaluNJLaubyMGPower system stability and control1994New YorkMcGraw-Hill
ZhouNA cross-coherence method for detecting oscillationsIEEE Trans Power Syst201631162363110.1109/TPWRS.2015.2404804
BezaMBongiornoMA modified RLS algorithm for online estimation of low-frequency oscillations in power systemsIEEE Trans Power Syst20163131703171410.1109/TPWRS.2015.2439811
Brien JGO, Wu T, Mani W, Zhang H (2017) Source location of forced oscillations using Synchrophasor and SCADA data. In: Proceedings of the 50th Hawaii international conference on system sciences, pp 3173–3182
POSOCO (2014) Report on power system oscillations experienced in Indian grid on 9th, 10th, 11th, and 12th August 2014, September 2014
GolubGHPereyraVThe differentiation of pseudo-inverses and nonlinear least squares problems whose variables separateSIAM J Numer Anal197310241343233698010.1137/0710036
ENTSOE (2017) Analysis of CE inter-area oscillations of 1st December 2016, July 2017
Powerworld corporation. [Online]. http://www.powerworld.com/. Accessed 18 June 2020
GolubGHPereyraVSeparable nonlinear least squares: the variable projection method and its applicationsInverse Probl2003192003R1R26199178610.1088/0266-5611/19/2/201
SetarehMParnianiMAminifarFAmbient data-based online electromechanical mode estimation by error-feedback lattice RLS filterIEEE Trans Power Syst20183343745375610.1109/TPWRS.2017.2767105
KorbaPReal-time monitoring of electromechanical oscillations in power systems: first findingsIET Gener Transm Distrib200711808810.1049/iet-gtd:20050243
KhalidHMPengJCImproved recursive electromechanical oscillations monitoring scheme: a novel distributed approachIEEE Trans Power Syst201530268068810.1109/TPWRS.2014.2336859
Korba P, Larsson M, Rehtanz C (2003) Detection of oscillations in power systems using Kalman filtering techniques. In: Proceedings of 2003 IEEE conference on control applications, 2003. CCA 2003, vol 1, pp 183–188
NERC (2002) Review of selected 1996 electric system disturbances in North America, August 2002
HauerJFVakiliFAn oscillation detector used in the BPA power system disturbance monitorIEEE Trans Power Syst199051747910.1109/59.49089
KhalidHMPengJCTracking electro-mechanical oscillations: an enhanced maximum-likelihood based approachIEEE Trans Power Syst20163131799180810.1109/TPWRS.2015.2441109
SauerPWPaiMAPower system dynamics and stability1998Upper Saddle RiverPrentice Hall
RogersGPower system oscillations2000BostonKluwer Academic10.1007/978-1-4615-4561-3
Mrinal MandalAAContinuous and discrete time signals and systems20071CambridgeCambridge University Press1129.93002
KamwaIPradhanAKJoosGRobust detection and analysis of power system oscillations using the Teager–Kaiser energy operatorIEEE Trans Power Syst201126132333310.1109/TPWRS.2010.2046503
BordenARLesieutreBCVariable projection method for power system modal identificationIEEE Trans Power Syst20142962613262010.1109/TPWRS.2014.2309635
SSAT User Manual, ver. 18, Powertech Labs, Inc
PengJCNairNCEnhancing Kalman filter for tracking ringdown electromechanical oscillationsIEEE Trans Power Syst20122721042105010.1109/TPWRS.2011.2169284
KleinMRogersGJKundurPA fundamental study of inter-area oscillations in power systemsIEEE Trans Power Syst19916391492110.1109/59.119229
P Kundur (471_CR7) 1994
AA Mrinal Mandal (471_CR17) 2007
PW Sauer (471_CR1) 1998
M Klein (471_CR6) 1991; 6
GH Golub (471_CR21) 1973; 10
GH Golub (471_CR22) 2003; 19
JC Peng (471_CR11) 2012; 27
471_CR4
471_CR24
471_CR23
471_CR18
471_CR3
471_CR2
M Beza (471_CR9) 2016; 31
I Kamwa (471_CR8) 2011; 26
N Zhou (471_CR10) 2016; 31
HM Khalid (471_CR14) 2016; 31
JF Hauer (471_CR15) 1990; 5
471_CR20
HM Khalid (471_CR16) 2015; 30
P Korba (471_CR12) 2007; 1
G Rogers (471_CR5) 2000
AR Borden (471_CR19) 2014; 29
M Setareh (471_CR13) 2018; 33
References_xml – reference: Korba P, Larsson M, Rehtanz C (2003) Detection of oscillations in power systems using Kalman filtering techniques. In: Proceedings of 2003 IEEE conference on control applications, 2003. CCA 2003, vol 1, pp 183–188
– reference: GolubGHPereyraVThe differentiation of pseudo-inverses and nonlinear least squares problems whose variables separateSIAM J Numer Anal197310241343233698010.1137/0710036
– reference: SSAT User Manual, ver. 18, Powertech Labs, Inc
– reference: SauerPWPaiMAPower system dynamics and stability1998Upper Saddle RiverPrentice Hall
– reference: Mrinal MandalAAContinuous and discrete time signals and systems20071CambridgeCambridge University Press1129.93002
– reference: NERC (2002) Review of selected 1996 electric system disturbances in North America, August 2002
– reference: SetarehMParnianiMAminifarFAmbient data-based online electromechanical mode estimation by error-feedback lattice RLS filterIEEE Trans Power Syst20183343745375610.1109/TPWRS.2017.2767105
– reference: GolubGHPereyraVSeparable nonlinear least squares: the variable projection method and its applicationsInverse Probl2003192003R1R26199178610.1088/0266-5611/19/2/201
– reference: KamwaIPradhanAKJoosGRobust detection and analysis of power system oscillations using the Teager–Kaiser energy operatorIEEE Trans Power Syst201126132333310.1109/TPWRS.2010.2046503
– reference: KleinMRogersGJKundurPA fundamental study of inter-area oscillations in power systemsIEEE Trans Power Syst19916391492110.1109/59.119229
– reference: BezaMBongiornoMA modified RLS algorithm for online estimation of low-frequency oscillations in power systemsIEEE Trans Power Syst20163131703171410.1109/TPWRS.2015.2439811
– reference: HauerJFVakiliFAn oscillation detector used in the BPA power system disturbance monitorIEEE Trans Power Syst199051747910.1109/59.49089
– reference: KorbaPReal-time monitoring of electromechanical oscillations in power systems: first findingsIET Gener Transm Distrib200711808810.1049/iet-gtd:20050243
– reference: Brien JGO, Wu T, Mani W, Zhang H (2017) Source location of forced oscillations using Synchrophasor and SCADA data. In: Proceedings of the 50th Hawaii international conference on system sciences, pp 3173–3182
– reference: PengJCNairNCEnhancing Kalman filter for tracking ringdown electromechanical oscillationsIEEE Trans Power Syst20122721042105010.1109/TPWRS.2011.2169284
– reference: BordenARLesieutreBCVariable projection method for power system modal identificationIEEE Trans Power Syst20142962613262010.1109/TPWRS.2014.2309635
– reference: KhalidHMPengJCImproved recursive electromechanical oscillations monitoring scheme: a novel distributed approachIEEE Trans Power Syst201530268068810.1109/TPWRS.2014.2336859
– reference: ENTSOE (2017) Analysis of CE inter-area oscillations of 1st December 2016, July 2017
– reference: Powerworld corporation. [Online]. http://www.powerworld.com/. Accessed 18 June 2020
– reference: POSOCO (2014) Report on power system oscillations experienced in Indian grid on 9th, 10th, 11th, and 12th August 2014, September 2014
– reference: KhalidHMPengJCTracking electro-mechanical oscillations: an enhanced maximum-likelihood based approachIEEE Trans Power Syst20163131799180810.1109/TPWRS.2015.2441109
– reference: KundurPBaluNJLaubyMGPower system stability and control1994New YorkMcGraw-Hill
– reference: ZhouNA cross-coherence method for detecting oscillationsIEEE Trans Power Syst201631162363110.1109/TPWRS.2015.2404804
– reference: RogersGPower system oscillations2000BostonKluwer Academic10.1007/978-1-4615-4561-3
– ident: 471_CR18
  doi: 10.24251/HICSS.2017.384
– volume: 5
  start-page: 74
  issue: 1
  year: 1990
  ident: 471_CR15
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/59.49089
– volume-title: Power system stability and control
  year: 1994
  ident: 471_CR7
– volume: 6
  start-page: 914
  issue: 3
  year: 1991
  ident: 471_CR6
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/59.119229
– volume: 19
  start-page: R1
  issue: 2003
  year: 2003
  ident: 471_CR22
  publication-title: Inverse Probl
  doi: 10.1088/0266-5611/19/2/201
– volume: 30
  start-page: 680
  issue: 2
  year: 2015
  ident: 471_CR16
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2014.2336859
– volume: 31
  start-page: 623
  issue: 1
  year: 2016
  ident: 471_CR10
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2015.2404804
– volume: 29
  start-page: 2613
  issue: 6
  year: 2014
  ident: 471_CR19
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2014.2309635
– volume-title: Power system dynamics and stability
  year: 1998
  ident: 471_CR1
– volume: 10
  start-page: 413
  issue: 2
  year: 1973
  ident: 471_CR21
  publication-title: SIAM J Numer Anal
  doi: 10.1137/0710036
– volume: 31
  start-page: 1703
  issue: 3
  year: 2016
  ident: 471_CR9
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2015.2439811
– volume-title: Continuous and discrete time signals and systems
  year: 2007
  ident: 471_CR17
– volume: 1
  start-page: 80
  issue: 1
  year: 2007
  ident: 471_CR12
  publication-title: IET Gener Transm Distrib
  doi: 10.1049/iet-gtd:20050243
– volume: 33
  start-page: 3745
  issue: 4
  year: 2018
  ident: 471_CR13
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2017.2767105
– ident: 471_CR23
– ident: 471_CR20
– volume: 27
  start-page: 1042
  issue: 2
  year: 2012
  ident: 471_CR11
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2011.2169284
– ident: 471_CR24
– ident: 471_CR2
– volume: 26
  start-page: 323
  issue: 1
  year: 2011
  ident: 471_CR8
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2010.2046503
– ident: 471_CR3
– ident: 471_CR4
– volume-title: Power system oscillations
  year: 2000
  ident: 471_CR5
  doi: 10.1007/978-1-4615-4561-3
– volume: 31
  start-page: 1799
  issue: 3
  year: 2016
  ident: 471_CR14
  publication-title: IEEE Trans Power Syst
  doi: 10.1109/TPWRS.2015.2441109
SSID ssj0061053
Score 2.1708012
Snippet Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore,...
Purpose Electromechanical oscillations between interconnected generators are considered a major threat to the secure operation of power systems. Therefore,...
SourceID nrf
crossref
springer
SourceType Open Website
Index Database
Publisher
StartPage 1999
SubjectTerms Electrical Engineering
Electrical Machines and Networks
Electronics and Microelectronics
Engineering
Instrumentation
Original Article
Power Electronics
전기공학
Title Detection and Analysis of Electromechanical Oscillation in Power Systems with Low-Sampled Data Using Modal Analysis Methods
URI https://link.springer.com/article/10.1007/s42835-020-00471-0
https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002622262
Volume 15
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
ispartofPNX Journal of Electrical Engineering & Technology, 2020, 15(5), , pp.1999-2006
journalDatabaseRights – providerCode: PRVLSH
  databaseName: SpringerLink Journals
  customDbUrl:
  mediaType: online
  eissn: 2093-7423
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0061053
  issn: 1975-0102
  databaseCode: AFBBN
  dateStart: 20190101
  isFulltext: true
  providerName: Library Specific Holdings
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwELa22wscEE-xvGQhfCpBaeL4cUy2WxXEFiRaqbfIjh1UFRK0mwoJfif_h7GT7GbZFhUulmU7k2Tmi2fsjGcQesWMiksa8YAaCgVXKgCjPgksp7AaAdTIwp1Gnh-zo1P67iw5G41-DbyWLhv9pvhx5bmS_5EqtIFc3SnZf5Dsiig0QB3kCyVIGMobyfjANrZL9V2Zjfgisza7zVfrDvZ6OXwAXfeldXxzexwfXXa0Pl55uxv7vv4efFIuWrABMDRqr3UnmNfGibEnPvcpp5fXGLVtVh1_Q7uOdOjx1Wxt4pNZRrKQZPtkNiVpRETiKlKQlK6HpCSTzh0DeoRwnd1F4XC_AhanvUNWizA3Skz9dQdEJkRO_T1CIqgnKRyNrkv6SgrjBzO05M7bMGyncOvbolDGgfvlPJiJXXiFgVZ3OydXaozWSWTp484F_nFD0NdBuNaPvU_AH2pzI0D3RXGef67zi0UOy5C3OSw6YRmY7KDdiDMWjdFuephlx72JACarD4-6epfuNJc_07n1JBsW0061KLd-2ntb6OQuutPJG6ctIu-hka3uo9uD0JYP0M8VNjFgE_fwwXWJt7CJB9jE5xX22MQdNrHDJh5gEztsYo9N7LG5Jt5h8yE6PZydTI-CLtFHUAB_GvimqRJlKUWpKJiwRSKYNoZzJY3RiWIlBcWjlGUxKy3YmLqU3CQy2tdaGMl4_AiNq7qyjxFmcZEUkobaaEU5LIap0lpFXCjGLBflBO31zMy_tfFc8lXkbs_6HFife9bn4QS9BH576V4v5Ql63Ysj7yaH5V9oPrkJzafo1vrbeYbGzeLSPgfrt9EvOiz9BmcromI
linkProvider Library Specific Holdings
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Detection+and+Analysis+of+Electromechanical+Oscillation+in+Power+Systems+with+Low-Sampled+Data+Using+Modal+Analysis+Methods&rft.jtitle=Journal+of+electrical+engineering+%26+technology&rft.au=%EB%B0%B1%EC%A2%85%EC%98%A4&rft.au=%EA%B9%80%EC%88%98%EB%B0%B0&rft.date=2020-09-01&rft.pub=%EB%8C%80%ED%95%9C%EC%A0%84%EA%B8%B0%ED%95%99%ED%9A%8C&rft.issn=1975-0102&rft.eissn=2093-7423&rft.spage=1999&rft.epage=2006&rft_id=info:doi/10.1007%2Fs42835-020-00471-0&rft.externalDBID=n%2Fa&rft.externalDocID=oai_kci_go_kr_ARTI_9567535
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1975-0102&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1975-0102&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1975-0102&client=summon