Loading…
Performance of Controller Designs in Small-Disturbance Angle Stability of Power Systems with Parametric Uncertainties
The electric power system is a complicated dynamic system with a range of operating states and parametric uncertainties, especially due to change of the network topology, load increment and generation scheduling. Under this circumstance, traditional power system transient stability analysis methods...
Saved in:
Published in: | Revista IEEE América Latina 2021-12, Vol.19 (12), p.2054-2061 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | eng ; por |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c291t-1f9397d78e0934225073448e4d7006014690b070ab60ceadae67cb68fc2b14d43 |
---|---|
cites | |
container_end_page | 2061 |
container_issue | 12 |
container_start_page | 2054 |
container_title | Revista IEEE América Latina |
container_volume | 19 |
creator | Santos, Moises Calvaittis Santana, Gabriel De Campos, Mauricio Sperandio, Mauricio Sausen, Paulo S. |
description | The electric power system is a complicated dynamic system with a range of operating states and parametric uncertainties, especially due to change of the network topology, load increment and generation scheduling. Under this circumstance, traditional power system transient stability analysis methods may not always be appropriate. This paper presents the development of a computational methodology for evaluating the effect of parametric uncertainties on the small-signal stability analysis of power systems. A probabilistic approach is applied as a metric for the dynamic performance of the damping ratio of critical eigenvalues. The method is based on a Monte Carlo simulation for the analysis of automatic control of generation. The methodology is used for the performance evaluation of three classical controller tuning techniques: Frequency Response, Approximate Method and Ziegler-Nichols. The results show that the methodology is valid and potentially useful for quantifying the effect of parametric uncertainties in power systems dynamics simulations. |
doi_str_mv | 10.1109/TLA.2021.9480147 |
format | article |
fullrecord | <record><control><sourceid>proquest_ieee_</sourceid><recordid>TN_cdi_ieee_primary_9480147</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9480147</ieee_id><sourcerecordid>2551370143</sourcerecordid><originalsourceid>FETCH-LOGICAL-c291t-1f9397d78e0934225073448e4d7006014690b070ab60ceadae67cb68fc2b14d43</originalsourceid><addsrcrecordid>eNpNkMtrAjEQh0Npodb2Xugl0PPayWMfOYr2BUIF9bxkd2dtZB82iYj_fWO1pacZmO-bYX6E3DMYMQbqaTkbjzhwNlIyAybTCzJgscwiUIpf_uuvyY1zGwCRJZkYkN0cbd3bVncl0r6mk77ztm8atHSKzqw7R01HF61ummhqnN_Z4gcdd-sG6cLrwjTGH47qvN8Ha3FwHltH98Z_0rm2ukVvTUlXwbJem84bdLfkqtaNw7tzHZLVy_Ny8hbNPl7fJ-NZVHLFfMRqJVRapRmCEpLzGFIhZYaySgGS8GWioIAUdJFAibrSmKRlkWR1yQsmKymG5PG0d2v7rx06n2_6ne3CyZzHMRNp2CECBSeqtL1zFut8a02r7SFnkB_DzUO4-THc_BxuUB5OikHEP_x3-g01-nY0</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2551370143</pqid></control><display><type>article</type><title>Performance of Controller Designs in Small-Disturbance Angle Stability of Power Systems with Parametric Uncertainties</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Santos, Moises ; Calvaittis Santana, Gabriel ; De Campos, Mauricio ; Sperandio, Mauricio ; Sausen, Paulo S.</creator><creatorcontrib>Santos, Moises ; Calvaittis Santana, Gabriel ; De Campos, Mauricio ; Sperandio, Mauricio ; Sausen, Paulo S.</creatorcontrib><description>The electric power system is a complicated dynamic system with a range of operating states and parametric uncertainties, especially due to change of the network topology, load increment and generation scheduling. Under this circumstance, traditional power system transient stability analysis methods may not always be appropriate. This paper presents the development of a computational methodology for evaluating the effect of parametric uncertainties on the small-signal stability analysis of power systems. A probabilistic approach is applied as a metric for the dynamic performance of the damping ratio of critical eigenvalues. The method is based on a Monte Carlo simulation for the analysis of automatic control of generation. The methodology is used for the performance evaluation of three classical controller tuning techniques: Frequency Response, Approximate Method and Ziegler-Nichols. The results show that the methodology is valid and potentially useful for quantifying the effect of parametric uncertainties in power systems dynamics simulations.</description><identifier>ISSN: 1548-0992</identifier><identifier>EISSN: 1548-0992</identifier><identifier>DOI: 10.1109/TLA.2021.9480147</identifier><language>eng ; por</language><publisher>Los Alamitos: IEEE</publisher><subject>angle stability ; Approximation ; Automatic control ; automatic generation control ; Control stability ; Control systems design ; controller design ; Controllers ; Damping ratio ; Dynamic scheduling ; Eigenvalues ; Electric power systems ; Frequency response ; IEEE transactions ; Jacobian matrices ; Methodology ; Monte Carlo methods ; Monte Carlo simulation ; Network topologies ; parametric uncertainties ; Performance evaluation ; Power system dynamics ; Power system stability ; Stability analysis ; Transient stability ; Uncertainty</subject><ispartof>Revista IEEE América Latina, 2021-12, Vol.19 (12), p.2054-2061</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-1f9397d78e0934225073448e4d7006014690b070ab60ceadae67cb68fc2b14d43</citedby><orcidid>0000-0001-8691-2913 ; 0000-0001-9863-8800 ; 0000-0003-1681-1425 ; 0000-0003-4507-8437</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9480147$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids></links><search><creatorcontrib>Santos, Moises</creatorcontrib><creatorcontrib>Calvaittis Santana, Gabriel</creatorcontrib><creatorcontrib>De Campos, Mauricio</creatorcontrib><creatorcontrib>Sperandio, Mauricio</creatorcontrib><creatorcontrib>Sausen, Paulo S.</creatorcontrib><title>Performance of Controller Designs in Small-Disturbance Angle Stability of Power Systems with Parametric Uncertainties</title><title>Revista IEEE América Latina</title><addtitle>T-LA</addtitle><description>The electric power system is a complicated dynamic system with a range of operating states and parametric uncertainties, especially due to change of the network topology, load increment and generation scheduling. Under this circumstance, traditional power system transient stability analysis methods may not always be appropriate. This paper presents the development of a computational methodology for evaluating the effect of parametric uncertainties on the small-signal stability analysis of power systems. A probabilistic approach is applied as a metric for the dynamic performance of the damping ratio of critical eigenvalues. The method is based on a Monte Carlo simulation for the analysis of automatic control of generation. The methodology is used for the performance evaluation of three classical controller tuning techniques: Frequency Response, Approximate Method and Ziegler-Nichols. The results show that the methodology is valid and potentially useful for quantifying the effect of parametric uncertainties in power systems dynamics simulations.</description><subject>angle stability</subject><subject>Approximation</subject><subject>Automatic control</subject><subject>automatic generation control</subject><subject>Control stability</subject><subject>Control systems design</subject><subject>controller design</subject><subject>Controllers</subject><subject>Damping ratio</subject><subject>Dynamic scheduling</subject><subject>Eigenvalues</subject><subject>Electric power systems</subject><subject>Frequency response</subject><subject>IEEE transactions</subject><subject>Jacobian matrices</subject><subject>Methodology</subject><subject>Monte Carlo methods</subject><subject>Monte Carlo simulation</subject><subject>Network topologies</subject><subject>parametric uncertainties</subject><subject>Performance evaluation</subject><subject>Power system dynamics</subject><subject>Power system stability</subject><subject>Stability analysis</subject><subject>Transient stability</subject><subject>Uncertainty</subject><issn>1548-0992</issn><issn>1548-0992</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNpNkMtrAjEQh0Npodb2Xugl0PPayWMfOYr2BUIF9bxkd2dtZB82iYj_fWO1pacZmO-bYX6E3DMYMQbqaTkbjzhwNlIyAybTCzJgscwiUIpf_uuvyY1zGwCRJZkYkN0cbd3bVncl0r6mk77ztm8atHSKzqw7R01HF61ummhqnN_Z4gcdd-sG6cLrwjTGH47qvN8Ha3FwHltH98Z_0rm2ukVvTUlXwbJem84bdLfkqtaNw7tzHZLVy_Ny8hbNPl7fJ-NZVHLFfMRqJVRapRmCEpLzGFIhZYaySgGS8GWioIAUdJFAibrSmKRlkWR1yQsmKymG5PG0d2v7rx06n2_6ne3CyZzHMRNp2CECBSeqtL1zFut8a02r7SFnkB_DzUO4-THc_BxuUB5OikHEP_x3-g01-nY0</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Santos, Moises</creator><creator>Calvaittis Santana, Gabriel</creator><creator>De Campos, Mauricio</creator><creator>Sperandio, Mauricio</creator><creator>Sausen, Paulo S.</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>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-8691-2913</orcidid><orcidid>https://orcid.org/0000-0001-9863-8800</orcidid><orcidid>https://orcid.org/0000-0003-1681-1425</orcidid><orcidid>https://orcid.org/0000-0003-4507-8437</orcidid></search><sort><creationdate>20211201</creationdate><title>Performance of Controller Designs in Small-Disturbance Angle Stability of Power Systems with Parametric Uncertainties</title><author>Santos, Moises ; Calvaittis Santana, Gabriel ; De Campos, Mauricio ; Sperandio, Mauricio ; Sausen, Paulo S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-1f9397d78e0934225073448e4d7006014690b070ab60ceadae67cb68fc2b14d43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng ; por</language><creationdate>2021</creationdate><topic>angle stability</topic><topic>Approximation</topic><topic>Automatic control</topic><topic>automatic generation control</topic><topic>Control stability</topic><topic>Control systems design</topic><topic>controller design</topic><topic>Controllers</topic><topic>Damping ratio</topic><topic>Dynamic scheduling</topic><topic>Eigenvalues</topic><topic>Electric power systems</topic><topic>Frequency response</topic><topic>IEEE transactions</topic><topic>Jacobian matrices</topic><topic>Methodology</topic><topic>Monte Carlo methods</topic><topic>Monte Carlo simulation</topic><topic>Network topologies</topic><topic>parametric uncertainties</topic><topic>Performance evaluation</topic><topic>Power system dynamics</topic><topic>Power system stability</topic><topic>Stability analysis</topic><topic>Transient stability</topic><topic>Uncertainty</topic><toplevel>online_resources</toplevel><creatorcontrib>Santos, Moises</creatorcontrib><creatorcontrib>Calvaittis Santana, Gabriel</creatorcontrib><creatorcontrib>De Campos, Mauricio</creatorcontrib><creatorcontrib>Sperandio, Mauricio</creatorcontrib><creatorcontrib>Sausen, Paulo S.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Revista IEEE América Latina</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Santos, Moises</au><au>Calvaittis Santana, Gabriel</au><au>De Campos, Mauricio</au><au>Sperandio, Mauricio</au><au>Sausen, Paulo S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Performance of Controller Designs in Small-Disturbance Angle Stability of Power Systems with Parametric Uncertainties</atitle><jtitle>Revista IEEE América Latina</jtitle><stitle>T-LA</stitle><date>2021-12-01</date><risdate>2021</risdate><volume>19</volume><issue>12</issue><spage>2054</spage><epage>2061</epage><pages>2054-2061</pages><issn>1548-0992</issn><eissn>1548-0992</eissn><abstract>The electric power system is a complicated dynamic system with a range of operating states and parametric uncertainties, especially due to change of the network topology, load increment and generation scheduling. Under this circumstance, traditional power system transient stability analysis methods may not always be appropriate. This paper presents the development of a computational methodology for evaluating the effect of parametric uncertainties on the small-signal stability analysis of power systems. A probabilistic approach is applied as a metric for the dynamic performance of the damping ratio of critical eigenvalues. The method is based on a Monte Carlo simulation for the analysis of automatic control of generation. The methodology is used for the performance evaluation of three classical controller tuning techniques: Frequency Response, Approximate Method and Ziegler-Nichols. The results show that the methodology is valid and potentially useful for quantifying the effect of parametric uncertainties in power systems dynamics simulations.</abstract><cop>Los Alamitos</cop><pub>IEEE</pub><doi>10.1109/TLA.2021.9480147</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-8691-2913</orcidid><orcidid>https://orcid.org/0000-0001-9863-8800</orcidid><orcidid>https://orcid.org/0000-0003-1681-1425</orcidid><orcidid>https://orcid.org/0000-0003-4507-8437</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1548-0992 |
ispartof | Revista IEEE América Latina, 2021-12, Vol.19 (12), p.2054-2061 |
issn | 1548-0992 1548-0992 |
language | eng ; por |
recordid | cdi_ieee_primary_9480147 |
source | IEEE Electronic Library (IEL) Journals |
subjects | angle stability Approximation Automatic control automatic generation control Control stability Control systems design controller design Controllers Damping ratio Dynamic scheduling Eigenvalues Electric power systems Frequency response IEEE transactions Jacobian matrices Methodology Monte Carlo methods Monte Carlo simulation Network topologies parametric uncertainties Performance evaluation Power system dynamics Power system stability Stability analysis Transient stability Uncertainty |
title | Performance of Controller Designs in Small-Disturbance Angle Stability of Power Systems with Parametric Uncertainties |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T01%3A49%3A29IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Performance%20of%20Controller%20Designs%20in%20Small-Disturbance%20Angle%20Stability%20of%20Power%20Systems%20with%20Parametric%20Uncertainties&rft.jtitle=Revista%20IEEE%20Am%C3%A9rica%20Latina&rft.au=Santos,%20Moises&rft.date=2021-12-01&rft.volume=19&rft.issue=12&rft.spage=2054&rft.epage=2061&rft.pages=2054-2061&rft.issn=1548-0992&rft.eissn=1548-0992&rft_id=info:doi/10.1109/TLA.2021.9480147&rft_dat=%3Cproquest_ieee_%3E2551370143%3C/proquest_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c291t-1f9397d78e0934225073448e4d7006014690b070ab60ceadae67cb68fc2b14d43%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2551370143&rft_id=info:pmid/&rft_ieee_id=9480147&rfr_iscdi=true |