Robust RLS Methods for Online Estimation of Power System Electromechanical Modes
This paper proposes a robust recursive least square (RRLS) algorithm for online identification of power system modes based on measurement data. The measurement data can be either ambient or ringdown. Also, the mode estimation is provided in real-time. The validity of the proposed RRLS algorithm is d...
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Veröffentlicht in: | IEEE transactions on power systems 2007-08, Vol.22 (3), p.1240-1249 |
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creator | Ning Zhou Pierre, J.W. Trudnowski, D.J. Guttromson, R.T. |
description | This paper proposes a robust recursive least square (RRLS) algorithm for online identification of power system modes based on measurement data. The measurement data can be either ambient or ringdown. Also, the mode estimation is provided in real-time. The validity of the proposed RRLS algorithm is demonstrated with both simulation data from a 17-machine model and field measurement data from a wide area measurement system (WAMS). Comparison with the conventional recursive least square (RLS) and least mean square (LMS) algorithms shows that the proposed RRLS algorithm can identify the modes from the combined ringdown and ambient signals with outliers and missing data in real-time without noticeable performance degradation. An adaptive detrend algorithm is also proposed to remove the signal trend based on the RRLS algorithm. It is shown that the algorithm can keep up with the measurement data flow and work online to provide real-time mode estimation. |
doi_str_mv | 10.1109/TPWRS.2007.901104 |
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The measurement data can be either ambient or ringdown. Also, the mode estimation is provided in real-time. The validity of the proposed RRLS algorithm is demonstrated with both simulation data from a 17-machine model and field measurement data from a wide area measurement system (WAMS). Comparison with the conventional recursive least square (RLS) and least mean square (LMS) algorithms shows that the proposed RRLS algorithm can identify the modes from the combined ringdown and ambient signals with outliers and missing data in real-time without noticeable performance degradation. An adaptive detrend algorithm is also proposed to remove the signal trend based on the RRLS algorithm. It is shown that the algorithm can keep up with the measurement data flow and work online to provide real-time mode estimation.</description><identifier>ISSN: 0885-8950</identifier><identifier>EISSN: 1558-0679</identifier><identifier>DOI: 10.1109/TPWRS.2007.901104</identifier><identifier>CODEN: ITPSEG</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive algorithms ; Algorithms ; Area measurement ; Autoregressive ; electromechanical mode ; identification ; Least mean squares ; Least squares method ; Least squares methods ; On-line systems ; Online ; Power measurement ; Power system measurements ; Power system modeling ; power system parameter estimation ; Power system simulation ; power system small signal stability ; Power systems ; Real time ; Recursive ; Resonance light scattering ; robust recursive least square (RRLS) ; Robustness ; Wide area measurements</subject><ispartof>IEEE transactions on power systems, 2007-08, Vol.22 (3), p.1240-1249</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2007</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c453t-5cd6a679a8b4446d2035da0c834487955b188c3c08749993d29926c74b5340f93</citedby><cites>FETCH-LOGICAL-c453t-5cd6a679a8b4446d2035da0c834487955b188c3c08749993d29926c74b5340f93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4282064$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27922,27923,54756</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4282064$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ning Zhou</creatorcontrib><creatorcontrib>Pierre, J.W.</creatorcontrib><creatorcontrib>Trudnowski, D.J.</creatorcontrib><creatorcontrib>Guttromson, R.T.</creatorcontrib><title>Robust RLS Methods for Online Estimation of Power System Electromechanical Modes</title><title>IEEE transactions on power systems</title><addtitle>TPWRS</addtitle><description>This paper proposes a robust recursive least square (RRLS) algorithm for online identification of power system modes based on measurement data. The measurement data can be either ambient or ringdown. Also, the mode estimation is provided in real-time. The validity of the proposed RRLS algorithm is demonstrated with both simulation data from a 17-machine model and field measurement data from a wide area measurement system (WAMS). Comparison with the conventional recursive least square (RLS) and least mean square (LMS) algorithms shows that the proposed RRLS algorithm can identify the modes from the combined ringdown and ambient signals with outliers and missing data in real-time without noticeable performance degradation. An adaptive detrend algorithm is also proposed to remove the signal trend based on the RRLS algorithm. It is shown that the algorithm can keep up with the measurement data flow and work online to provide real-time mode estimation.</description><subject>Adaptive algorithms</subject><subject>Algorithms</subject><subject>Area measurement</subject><subject>Autoregressive</subject><subject>electromechanical mode</subject><subject>identification</subject><subject>Least mean squares</subject><subject>Least squares method</subject><subject>Least squares methods</subject><subject>On-line systems</subject><subject>Online</subject><subject>Power measurement</subject><subject>Power system measurements</subject><subject>Power system modeling</subject><subject>power system parameter estimation</subject><subject>Power system simulation</subject><subject>power system small signal stability</subject><subject>Power systems</subject><subject>Real time</subject><subject>Recursive</subject><subject>Resonance light scattering</subject><subject>robust recursive least square (RRLS)</subject><subject>Robustness</subject><subject>Wide area measurements</subject><issn>0885-8950</issn><issn>1558-0679</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqFkU1LAzEQhoMoWD9-gHgJHvS0dbKZZJOjSP2AiqWteAzbbBZXthtNtkj_vakVDx70NDDzvMPM-xJywmDIGOjL-eR5OhvmAMVQQ-rgDhkwIVQGstC7ZABKiUxpAfvkIMZXAJBpMCCTqV-sYk-n4xl9cP2LryKtfaCPXdt0jo5i3yzLvvEd9TWd-A8X6Gwde7eko9bZPvilsy9l19iypQ--cvGI7NVlG93xdz0kTzej-fVdNn68vb--GmcWBe8zYStZpgtKtUBEWeXARVWCVRxRFVqIBVPKcguqQK01r3Ktc2kLXAiOUGt-SC62e9-Cf1-52JtlE61r27JzfhWNBi4RBBT_kkoljwClSuT5n2S6TTJWYALPfoGvfhW69K9REnMmULAEsS1kg48xuNq8hWRmWBsGZhOa-QrNbEIz29CS5nSraZxzPzzmKgeJ_BMPj5BV</recordid><startdate>20070801</startdate><enddate>20070801</enddate><creator>Ning Zhou</creator><creator>Pierre, J.W.</creator><creator>Trudnowski, D.J.</creator><creator>Guttromson, R.T.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>F28</scope></search><sort><creationdate>20070801</creationdate><title>Robust RLS Methods for Online Estimation of Power System Electromechanical Modes</title><author>Ning Zhou ; Pierre, J.W. ; Trudnowski, D.J. ; Guttromson, R.T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c453t-5cd6a679a8b4446d2035da0c834487955b188c3c08749993d29926c74b5340f93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Adaptive algorithms</topic><topic>Algorithms</topic><topic>Area measurement</topic><topic>Autoregressive</topic><topic>electromechanical mode</topic><topic>identification</topic><topic>Least mean squares</topic><topic>Least squares method</topic><topic>Least squares methods</topic><topic>On-line systems</topic><topic>Online</topic><topic>Power measurement</topic><topic>Power system measurements</topic><topic>Power system modeling</topic><topic>power system parameter estimation</topic><topic>Power system simulation</topic><topic>power system small signal stability</topic><topic>Power systems</topic><topic>Real time</topic><topic>Recursive</topic><topic>Resonance light scattering</topic><topic>robust recursive least square (RRLS)</topic><topic>Robustness</topic><topic>Wide area measurements</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ning Zhou</creatorcontrib><creatorcontrib>Pierre, J.W.</creatorcontrib><creatorcontrib>Trudnowski, D.J.</creatorcontrib><creatorcontrib>Guttromson, R.T.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on power systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ning Zhou</au><au>Pierre, J.W.</au><au>Trudnowski, D.J.</au><au>Guttromson, R.T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Robust RLS Methods for Online Estimation of Power System Electromechanical Modes</atitle><jtitle>IEEE transactions on power systems</jtitle><stitle>TPWRS</stitle><date>2007-08-01</date><risdate>2007</risdate><volume>22</volume><issue>3</issue><spage>1240</spage><epage>1249</epage><pages>1240-1249</pages><issn>0885-8950</issn><eissn>1558-0679</eissn><coden>ITPSEG</coden><abstract>This paper proposes a robust recursive least square (RRLS) algorithm for online identification of power system modes based on measurement data. The measurement data can be either ambient or ringdown. Also, the mode estimation is provided in real-time. The validity of the proposed RRLS algorithm is demonstrated with both simulation data from a 17-machine model and field measurement data from a wide area measurement system (WAMS). Comparison with the conventional recursive least square (RLS) and least mean square (LMS) algorithms shows that the proposed RRLS algorithm can identify the modes from the combined ringdown and ambient signals with outliers and missing data in real-time without noticeable performance degradation. An adaptive detrend algorithm is also proposed to remove the signal trend based on the RRLS algorithm. It is shown that the algorithm can keep up with the measurement data flow and work online to provide real-time mode estimation.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TPWRS.2007.901104</doi><tpages>10</tpages></addata></record> |
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subjects | Adaptive algorithms Algorithms Area measurement Autoregressive electromechanical mode identification Least mean squares Least squares method Least squares methods On-line systems Online Power measurement Power system measurements Power system modeling power system parameter estimation Power system simulation power system small signal stability Power systems Real time Recursive Resonance light scattering robust recursive least square (RRLS) Robustness Wide area measurements |
title | Robust RLS Methods for Online Estimation of Power System Electromechanical Modes |
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