Optimal Placement of UPQC in Distribution Network Using Hybrid Approach

This study represents a power quality enhancement approach using a new hybrid algorithm which merges both Path Finder Algorithm (PFA) and Grey Wolf Optimizer (GWO) for determining the precise position and sizing of a unified power quality conditioner (UPQC). For this optimal selection, the adopted m...

Full description

Saved in:
Bibliographic Details
Published in:Cybernetics and systems Vol. 54; no. 7; pp. 1014 - 1036
Main Authors: Yadav, Shravan Kumar, Sabitha, B., Prabhakaran, Anush
Format: Journal Article
Language:English
Published: Taylor & Francis 03-10-2023
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract This study represents a power quality enhancement approach using a new hybrid algorithm which merges both Path Finder Algorithm (PFA) and Grey Wolf Optimizer (GWO) for determining the precise position and sizing of a unified power quality conditioner (UPQC). For this optimal selection, the adopted model named as Grey Wolf Insisted Inertia-based Path finder Algorithm is used. To determine the best location of the UPQC device, the suggested model focuses on the cost of UPQC, power losses, and voltage stability index. Further, the presented concept was implemented using IEEE 69 and IEEE 33 bus networks and the proposed model's performance was compared to that of other traditional approaches with respect to minimum fitness value. Accordingly, for a 50% loading scenario, the proposed model is 0.30%, 0.20%, 0.348%, 0.277%, and 0.105% better than PF, GWO, GM-DA, DA, and GA schemes. Likewise, in convergence analysis for 100th iteration, the suggested approach reaches the least value of 536.80. Therefore, it is evident that the proposed PF-GWO algorithm is more efficient than existing models with lower convergence rates. Thus, it is concluded that the proposed model achieves power quality enhancement for the optimal location and sizing of UPQC in power systems.
AbstractList This study represents a power quality enhancement approach using a new hybrid algorithm which merges both Path Finder Algorithm (PFA) and Grey Wolf Optimizer (GWO) for determining the precise position and sizing of a unified power quality conditioner (UPQC). For this optimal selection, the adopted model named as Grey Wolf Insisted Inertia-based Path finder Algorithm is used. To determine the best location of the UPQC device, the suggested model focuses on the cost of UPQC, power losses, and voltage stability index. Further, the presented concept was implemented using IEEE 69 and IEEE 33 bus networks and the proposed model's performance was compared to that of other traditional approaches with respect to minimum fitness value. Accordingly, for a 50% loading scenario, the proposed model is 0.30%, 0.20%, 0.348%, 0.277%, and 0.105% better than PF, GWO, GM-DA, DA, and GA schemes. Likewise, in convergence analysis for 100th iteration, the suggested approach reaches the least value of 536.80. Therefore, it is evident that the proposed PF-GWO algorithm is more efficient than existing models with lower convergence rates. Thus, it is concluded that the proposed model achieves power quality enhancement for the optimal location and sizing of UPQC in power systems.
Author Yadav, Shravan Kumar
Sabitha, B.
Prabhakaran, Anush
Author_xml – sequence: 1
  givenname: Shravan Kumar
  surname: Yadav
  fullname: Yadav, Shravan Kumar
  organization: Department of Electrical Engineering, NIT Jamshedpur
– sequence: 2
  givenname: B.
  surname: Sabitha
  fullname: Sabitha, B.
  organization: Electrical Engineering Department, Kumaraguru College of Technology
– sequence: 3
  givenname: Anush
  surname: Prabhakaran
  fullname: Prabhakaran, Anush
  organization: Electrical Engineering Department, Kumaraguru College of Technology
BookMark eNp9kN1KAzEQhYNUsK0-gpAX2Jqf_cneWaq2QrEV7HWYpIlGt8mSrEjf3l1ab72ZuZhzDnO-CRr54A1Ct5TMKBHkjtC6rCvGZowMg7KaV-ICjftjlZVFwUdoPGiyQXSFJil9EkI4r-gYLTdt5w7Q4G0D2hyM73CweLd9XWDn8YNLXXTqu3PB4xfT_YT4hXfJ-Xe8Oqro9njetjGA_rhGlxaaZG7Oe4p2T49vi1W23iyfF_N1pjklXQY5I0KAqIgwWilVWUEEy4mtlCYsr8FSxnRZGgPaFmCVzTUHKJQAykFQPkXFKVfHkFI0Vrax_z8eJSVyoCH_aMiBhjzT6H33J5_zNsQD9E2avezg2IRoI3jtkuT_R_wC1d5opQ
CitedBy_id crossref_primary_10_1016_j_rico_2024_100420
crossref_primary_10_1080_15435075_2023_2297775
Cites_doi 10.1002/jnm.2467
10.1109/TII.2018.2834628
10.1016/j.aej.2018.02.002
10.1080/03772063.2021.1888325
10.1049/iet-gtd.2013.0382
10.1016/j.advengsoft.2013.12.007
10.46253/jcmps.v3i3.a1
10.1049/iet-pel.2016.0999
10.46253/jcmps.v4i1.a4
10.1007/s40313-020-00564-1
10.1016/j.epsr.2020.106259
10.1016/j.ijepes.2016.04.007
10.1016/j.ijepes.2021.106893
10.1108/JEDT-04-2019-0113
10.1016/j.epsr.2015.03.007
10.1109/ic-ETITE47903.2020.330
10.1155/2009/109501
10.1155/2012/838629
10.1016/j.asoc.2019.03.012
10.1109/TPWRS.2019.2919786
10.1007/s00521-015-1920-1
10.1109/TSG.2016.2624273
10.1109/ICPES.2017.8387268
10.1016/j.ijepes.2016.05.010
10.1049/iet-gtd.2015.1040
10.1016/j.matpr.2017.11.172
10.1007/978-3-540-73190-0_7
10.1049/iet-pel.2015.0642
10.46253/jcmps.v3i2.a4
10.1049/iet-gtd.2013.0423
10.1109/TPWRD.2011.2165301
10.1016/j.neucom.2015.07.099
ContentType Journal Article
Copyright 2022 Taylor & Francis Group, LLC 2022
Copyright_xml – notice: 2022 Taylor & Francis Group, LLC 2022
DBID AAYXX
CITATION
DOI 10.1080/01969722.2022.2129378
DatabaseName CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Sciences (General)
EISSN 1087-6553
EndPage 1036
ExternalDocumentID 10_1080_01969722_2022_2129378
2129378
Genre Research Articles
GroupedDBID -~X
.7F
.DC
.QJ
0BK
0R~
29F
2DF
30N
3YN
4.4
5GY
5VS
AAAVI
AAENE
AAJMT
AALDU
AAMIU
AAPUL
AAQRR
ABBKH
ABCCY
ABFIM
ABHAV
ABJVF
ABLIJ
ABPEM
ABPTK
ABQHQ
ABTAI
ABXUL
ABXYU
ACGEJ
ACGFS
ACTIO
ADCVX
ADGTB
ADXPE
AEGYZ
AEISY
AENEX
AEOZL
AEPSL
AEYOC
AFKVX
AFOLD
AFWLO
AGDLA
AGMYJ
AHDLD
AIJEM
AIRXU
AJWEG
AKBVH
AKOOK
ALMA_UNASSIGNED_HOLDINGS
ALQZU
AQRUH
AVBZW
AWYRJ
BLEHA
CCCUG
CE4
COF
CS3
DKSSO
DU5
EBS
E~A
E~B
F5P
FPAXQ
FUNRP
FVPDL
GTTXZ
HF~
HZ~
H~P
IPNFZ
J.P
KYCEM
LJTGL
M4Z
NA5
NX~
O9-
P2P
RIG
RNANH
ROSJB
RTWRZ
S-T
SNACF
TEN
TFL
TFT
TFW
TN5
TNC
TTHFI
TWF
UT5
UU3
V1K
ZGOLN
~S~
AAYXX
ABJNI
ABPAQ
AHDZW
CITATION
DGEBU
H13
TBQAZ
TUROJ
ID FETCH-LOGICAL-c310t-a42088a8708ecbbb7f808240f7bc0249af122c66eeacf5afbf4c3aa5b8a13a813
IEDL.DBID TFW
ISSN 0196-9722
IngestDate Thu Nov 21 22:02:45 EST 2024
Tue Jul 11 04:11:17 EDT 2023
IsPeerReviewed true
IsScholarly true
Issue 7
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c310t-a42088a8708ecbbb7f808240f7bc0249af122c66eeacf5afbf4c3aa5b8a13a813
PageCount 23
ParticipantIDs informaworld_taylorfrancis_310_1080_01969722_2022_2129378
crossref_primary_10_1080_01969722_2022_2129378
PublicationCentury 2000
PublicationDate 2023-10-03
PublicationDateYYYYMMDD 2023-10-03
PublicationDate_xml – month: 10
  year: 2023
  text: 2023-10-03
  day: 03
PublicationDecade 2020
PublicationTitle Cybernetics and systems
PublicationYear 2023
Publisher Taylor & Francis
Publisher_xml – name: Taylor & Francis
References CIT0030
CIT0010
CIT0032
CIT0031
CIT0012
CIT0034
CIT0033
Dheeban S. S. (CIT0008) 2021
CIT0014
CIT0013
CIT0035
CIT0016
CIT0015
CIT0018
CIT0017
CIT0019
CIT0021
CIT0020
CIT0001
CIT0023
CIT0022
CIT0003
Gaddala K. (CIT0011) 2020; 14
CIT0025
CIT0002
CIT0024
CIT0005
CIT0027
CIT0004
CIT0026
CIT0007
CIT0029
CIT0006
CIT0028
CIT0009
References_xml – ident: CIT0014
  doi: 10.1002/jnm.2467
– ident: CIT0034
  doi: 10.1109/TII.2018.2834628
– ident: CIT0033
  doi: 10.1016/j.aej.2018.02.002
– ident: CIT0007
  doi: 10.1080/03772063.2021.1888325
– volume: 14
  start-page: 1
  year: 2020
  ident: CIT0011
  publication-title: Evolutionary Intelligence
  contributor:
    fullname: Gaddala K.
– ident: CIT0013
  doi: 10.1049/iet-gtd.2013.0382
– ident: CIT0022
  doi: 10.1016/j.advengsoft.2013.12.007
– ident: CIT0031
  doi: 10.46253/jcmps.v3i3.a1
– ident: CIT0006
  doi: 10.1049/iet-pel.2016.0999
– ident: CIT0002
– ident: CIT0020
  doi: 10.46253/jcmps.v4i1.a4
– ident: CIT0012
  doi: 10.1007/s40313-020-00564-1
– ident: CIT0025
  doi: 10.1016/j.epsr.2020.106259
– ident: CIT0026
  doi: 10.1016/j.ijepes.2016.04.007
– ident: CIT0004
  doi: 10.1016/j.ijepes.2021.106893
– ident: CIT0010
  doi: 10.1108/JEDT-04-2019-0113
– ident: CIT0015
  doi: 10.1016/j.epsr.2015.03.007
– ident: CIT0009
  doi: 10.1109/ic-ETITE47903.2020.330
– ident: CIT0029
  doi: 10.1155/2009/109501
– ident: CIT0030
  doi: 10.1155/2012/838629
– ident: CIT0032
  doi: 10.1016/j.asoc.2019.03.012
– ident: CIT0019
  doi: 10.1109/TPWRS.2019.2919786
– ident: CIT0021
  doi: 10.1007/s00521-015-1920-1
– ident: CIT0035
  doi: 10.1109/TSG.2016.2624273
– ident: CIT0018
  doi: 10.1109/ICPES.2017.8387268
– ident: CIT0024
  doi: 10.1016/j.ijepes.2016.05.010
– ident: CIT0027
  doi: 10.1049/iet-gtd.2015.1040
– start-page: 1
  year: 2021
  ident: CIT0008
  publication-title: Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
  contributor:
    fullname: Dheeban S. S.
– ident: CIT0016
  doi: 10.1016/j.matpr.2017.11.172
– ident: CIT0028
  doi: 10.1007/978-3-540-73190-0_7
– ident: CIT0023
  doi: 10.1049/iet-pel.2015.0642
– ident: CIT0003
  doi: 10.46253/jcmps.v3i2.a4
– ident: CIT0005
  doi: 10.1049/iet-gtd.2013.0423
– ident: CIT0017
  doi: 10.1109/TPWRD.2011.2165301
– ident: CIT0001
  doi: 10.1016/j.neucom.2015.07.099
SSID ssj0003371
Score 2.373676
Snippet This study represents a power quality enhancement approach using a new hybrid algorithm which merges both Path Finder Algorithm (PFA) and Grey Wolf Optimizer...
SourceID crossref
informaworld
SourceType Aggregation Database
Publisher
StartPage 1014
SubjectTerms Grey Wolf optimization
path finder algorithm
power quality
UPQC placement
VSI
Title Optimal Placement of UPQC in Distribution Network Using Hybrid Approach
URI https://www.tandfonline.com/doi/abs/10.1080/01969722.2022.2129378
Volume 54
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwED5BJxagPER5yQMDDIEkTuJ0rPqgUymiFWyR7fgkBlJE04F_jy9xUDvAAksmXxRd7pXLfd8BXKHva1t1hF4XTeLZ6BfTInf0YtGN_STPMRIEFB4_iclLOhgSTU6vwcLQWCV9Q2NNFFHFanJuqZbNRNxdRekiQoJR0YUyliC4L3FuW4uejZ6_YzHnwm0kTDwSaTA8P91lIzttcJeuZZ3R3j887z7supKT9WobacOWKQ6g7Zx6ya4d8_TNIdw_2ADyZs9OqblOfUO2QDafPvbZa8EGxLHr1mOxST0-zqqRAzb-JOAX6zmC8iOYj4az_thzmxY8bcu70pP0kz2V1ndTo5VSAlNbGkQ-CqWJU1BiEIY6SYwN0xhLVBhpLmWsUhlwmQb8GFrFojAnwKLcoNAq5JoO2eIrN0GgOSJyzKM46sBto-HsvSbUyIKGp9QpKiNFZU5RHeiuv4esrDoZWK8dyfivsqd_kD2DHVotXw3u8XNolR8rcwHby3x1WdnYF8u-zRg
link.rule.ids 315,782,786,1455,1509,27933,27934,58021,59734,60523
linkProvider Taylor & Francis
linkToHtml http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwED7RMsAClIcoTw8MMASaOInTseqDIEopohVskePkJAZSRNuBf48vcap2gAWWTHYUXXx3Xy533wdwgY2G0qjDsZqY-paOfh4JuaPliabX8JMEXUGDwuGzGLwGnS7R5CxmYaitkr6hsSCKyGM1OTcVo8uWuJuc00U4NEdFF0pZIqjAugbHnPjzR72XRTTmXBhNQt-iPeUUz0-3WclPK-ylS3mnt_0fT7wDWwZ1slZxTGqwlma7UDN-PWWXhnz6ag9uH3UMeddrh1Rfp9IhmyAbD5_a7C1jHaLZNQpZbFB0kLO864CFXzT7xVqGo3wfxr3uqB1aRmzBUhrhzSxJ_9kDqd03SFUcxwIDjQ7cBopYEa2gRNtxlO-nOlKjJzFGV3EpvTiQNpeBzQ-gmk2y9BCYm6QoVOxwRYs0_kpS21YcETkmrufW4bo0cfRRcGpEdklVagwVkaEiY6g6NJdfRDTLixlYKI9E_Ne9R3_Yew4b4eihH_XvBvfHsElK83kfHz-B6uxznp5CZZrMz_ID9w3bV9E8
linkToPdf http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwELZokRALUB6iPD0wwBBI4iR2x6ptKAKVIlrBFjmOT2IgrWg78O_xJQ5qB1hgyeSLosu9crn7PkIuwHWVqTp8pwU6ckz0C5HIHZyQt0I3yjIIOC4K95_54FV0ewiT0652YXCsEr-hoQSKKGI1Ovc0g2oi7qaAdOE-rlHhBTMWFzWyHgqTsIxJj-KX72DMGLeUhJGDMtUSz0-3WUlPK-ClS2kn3v6HB94hW7bmpO3SSBpkTee7pGG9ekYvLfT01R65fTQR5N2cHWJ3HRuHdAJ0PHzq0LecdhFk1_Jj0UE5P06LmQPa_8TNL9q2COX7ZBz3Rp2-Y6kWHGXqu7kj8S-7kMZ5hVZpmnIQpjYIXOCpQlBBCZ7vqyjSJk5DKCGFQDEpw1RIj0nhsQNSzye5PiQ0yDRwlfpM4SFTfWXa8xQDAAZZEAZNcl1pOJmWiBqJVwGVWkUlqKjEKqpJWsvvIZkXrQwoeUcS9qvs0R9kz8nGsBsnD3eD-2OyiTTzxRAfOyH1-cdCn5LaLFucFeb2BWGfz-A
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=Optimal+Placement+of+UPQC+in+Distribution+Network+Using+Hybrid+Approach&rft.jtitle=Cybernetics+and+systems&rft.au=Yadav%2C+Shravan+Kumar&rft.au=Sabitha%2C+B.&rft.au=Prabhakaran%2C+Anush&rft.date=2023-10-03&rft.pub=Taylor+%26+Francis&rft.issn=0196-9722&rft.eissn=1087-6553&rft.volume=54&rft.issue=7&rft.spage=1014&rft.epage=1036&rft_id=info:doi/10.1080%2F01969722.2022.2129378&rft.externalDocID=2129378
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0196-9722&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0196-9722&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0196-9722&client=summon