Hybrid Differential Evolution Particle Swarm Optimization Algorithm for Reactive Power Optimization

Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimi...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2010 Asia-Pacific Power and Energy Engineering Conference s. 1 - 4
Hlavní autori: Shouzheng Wang, Lixin Ma, Dashuai Sun
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.03.2010
Predmet:
Hybrid power systems
Linear programming
Niobium
Particle swarm optimization
Power generation
Power system simulation
Quadratic programming
Reactive power
Sun
Voltage
ISBN:1424448123, 9781424448128
ISSN:2157-4839
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimization is minimization of system losses and improvement of voltage profiles in a power system. A hybrid differential evolution particle swarm optimization algorithm is presented to obtain the global optimum. The proposed algorithm is implemented on the IEEE 14-bus system. To validate the effectiveness of the algorithm, the simulation results are compared with other optimization algorithms'. It is shown that the approach developed is feasible and efficient.
AbstractList Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimization is minimization of system losses and improvement of voltage profiles in a power system. A hybrid differential evolution particle swarm optimization algorithm is presented to obtain the global optimum. The proposed algorithm is implemented on the IEEE 14-bus system. To validate the effectiveness of the algorithm, the simulation results are compared with other optimization algorithms'. It is shown that the approach developed is feasible and efficient.
Author Shouzheng Wang
Dashuai Sun
Lixin Ma
Author_xml – sequence: 1
  surname: Shouzheng Wang
  fullname: Shouzheng Wang
  email: wlwarren@126.com
  organization: Dept. of Electr. Eng., Univ. of Shanghai for Sci. & Tech., Shanghai, China
– sequence: 2
  surname: Lixin Ma
  fullname: Lixin Ma
  email: ma_eeepsi@usst.edu.cn
  organization: Dept. of Electr. Eng., Univ. of Shanghai for Sci. & Tech., Shanghai, China
– sequence: 3
  surname: Dashuai Sun
  fullname: Dashuai Sun
  organization: Dept. of Electr. Eng., Univ. of Shanghai for Sci. & Tech., Shanghai, China
BookMark eNpVkNtOAjEYhGuERECegJu-wOLfE9u9JLiCCQkbD9ek2_2rNXsgpULw6SVKYryafDOTuZgh6bVdi4RMGEwZg-xuXhR5vphyOBtKSq1BXJEhk1yegQl2_Qdc9MiAM5UmUousT4YcIMtASeA3ZLzffwCA4CAUlwNiV6cy-Iree-cwYBu9qWl-6OrP6LuWFiZEb2ukz0cTGrrZRd_4L_OTzeu3Lvj43lDXBfqExkZ_QFp0Rwz_mrek70y9x_FFR-T1IX9ZrJL1Zvm4mK8Tz1IVE2k1M6ZMLQAXMpuZ1FhgBmbagrJQQmW0yqRNlazQaSdYWdpKo0Om0WAlRmTyu-sRcbsLvjHhtL28Jb4BWw1ekw
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/APPEEC.2010.5448803
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISBN 1424448131
9781424448135
EndPage 4
ExternalDocumentID 5448803
Genre orig-research
GroupedDBID 6IE
6IF
6IL
6IN
AAJGR
AAWTH
ADZIZ
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
IEGSK
OCL
RIE
RIL
ID FETCH-LOGICAL-i175t-4c81aab7c0023496a7ac01a068c05c0b0da8594c754def8f31bbcd8efe18eaed3
IEDL.DBID RIE
ISBN 1424448123
9781424448128
ISICitedReferencesCount 0
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000396400802215&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 2157-4839
IngestDate Wed Aug 27 02:26:03 EDT 2025
IsPeerReviewed false
IsScholarly false
LCCN 2009905402
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i175t-4c81aab7c0023496a7ac01a068c05c0b0da8594c754def8f31bbcd8efe18eaed3
PageCount 4
ParticipantIDs ieee_primary_5448803
PublicationCentury 2000
PublicationDate 2010-March
PublicationDateYYYYMMDD 2010-03-01
PublicationDate_xml – month: 03
  year: 2010
  text: 2010-March
PublicationDecade 2010
PublicationTitle 2010 Asia-Pacific Power and Energy Engineering Conference
PublicationTitleAbbrev APPEEC
PublicationYear 2010
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0003203524
ssj0000452411
Score 1.4508768
Snippet Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal...
SourceID ieee
SourceType Publisher
StartPage 1
SubjectTerms Hybrid power systems
Linear programming
Niobium
Particle swarm optimization
Power generation
Power system simulation
Quadratic programming
Reactive power
Sun
Voltage
Title Hybrid Differential Evolution Particle Swarm Optimization Algorithm for Reactive Power Optimization
URI https://ieeexplore.ieee.org/document/5448803
WOSCitedRecordID wos000396400802215&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T8MwELbaigEWHi3iLQ-MhMbEsZ2xKqk6lYiH1K26XFyo1AcKaRH_HjtxC5VY2OIoUqzT2Z99d993hFxLgwpg7smeVavzeAbMA8GVp5BhGvoYAEDZbEIOBmo4jJIaudlwYbTWZfGZvrWPZS4_W-DShsraIbfuFtRJXUpRcbU28RQrDc6dr9pxcGeVPm1S2YCatDGzaM3r4gbUgrXckxsrp0jE_KjdSZI47lZlX-6XW71XSujp7f9v0gek9cPho8kGnQ5JTc-PyN4v-cEmwf6X5WvRe9ckxSz2KY1Xzhlp4ryKPn1CPqMPZnOZOdYm7UxfF_mkeJtRc-iljxrKbZMmtufa1pct8tKLn7t9zzVd8CbmJFF4HBUDSCVaNOeRAAnoM_CFQj9EP_UzUGHEUYY802M1DliaYqb0WDOlQWfBMWnMF3N9QmjGUMpUKB4ZO2cCIUUxlshACCVCxFPStOYavVe6GiNnqbO_X5-T3Spzb-u_LkijyJf6kuzgqph85FelM3wDGbuvwg
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG4QTdSLDzS-7cGjK1u223aPBCEYETeKCTcyO1uUhIdBwPjvbZeCknjx1m426WYy26-dme8bQq6kQQUw92TPqtV5PAXmgeDKU8gwCX0MACBrNiGbTdVuR3GOXC-5MFrrrPhM39hhlstPRzi1obJiyK27BWtk3YxK_pyttYyoWHFw7rzVzoOS1fq0aWUDa9JGzaIFs4sbWAsWgk9urpwmEfOjYjmOq9XKvPDLLbrSfSUDn9rO_z57lxz8sPhovMSnPZLTw32y_UuAsECw_mUZW_TWtUkxv3ufVmfOHWns_Io-f8J4QB_N9jJwvE1a7r-Oxr3J24CaYy990pBtnDS2XddW3jwgL7Vqq1L3XNsFr2fOEhOPo2IAiUSL5zwSIAF9Br5Q6IfoJ34KKow4ypCnuqu6AUsSTJXuaqY06DQ4JPnhaKiPCE0ZSpkIxSNj51QgJCi6EhkIoUSIeEwK1lyd97myRsdZ6uTvx5dks956aHQad837U7I1z-PbarAzkp-Mp_qcbOBs0vsYX2SO8Q1wBbMJ
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%3Abook&rft.genre=proceeding&rft.title=2010+Asia-Pacific+Power+and+Energy+Engineering+Conference&rft.atitle=Hybrid+Differential+Evolution+Particle+Swarm+Optimization+Algorithm+for+Reactive+Power+Optimization&rft.au=Shouzheng+Wang&rft.au=Lixin+Ma&rft.au=Dashuai+Sun&rft.date=2010-03-01&rft.pub=IEEE&rft.isbn=9781424448128&rft.issn=2157-4839&rft.spage=1&rft.epage=4&rft_id=info:doi/10.1109%2FAPPEEC.2010.5448803&rft.externalDocID=5448803
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2157-4839&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2157-4839&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2157-4839&client=summon