A Mixed-Integer Linear Programming Model for the Simultaneous Optimal Distribution Network Reconfiguration and Optimal Placement of Distributed Generation

Distributed generation (DG) aims to generate part of the required electrical energy on a small scale closer to the places of consumption. Integration of DG into an existing electric distribution network (EDN) has technical, economic, and environmental benefits. DG placement is typically determined b...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Energies (Basel) Ročník 15; číslo 9; s. 3063
Hlavní autoři: Gallego Pareja, Luis A., López-Lezama, Jesús M., Gómez Carmona, Oscar
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.05.2022
Témata:
ISSN:1996-1073, 1996-1073
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract Distributed generation (DG) aims to generate part of the required electrical energy on a small scale closer to the places of consumption. Integration of DG into an existing electric distribution network (EDN) has technical, economic, and environmental benefits. DG placement is typically determined by investors and local conditions such as the availability of energy resources, space, and licenses, among other factors. When the location of DG is not a decision of the distribution network operator (DNO), the simultaneous integration of distribution network reconfiguration (DNR) and DG placement can maximize the benefits of DG and mitigate eventual negative impacts. DNR consists of altering the EDN topology to improve its performance while maintaining the radiality of the network. DNR and optimal placement of DG (OPDG) are challenging optimization problems since they involve integer and continuous variables subject to nonlinear constraints and a nonlinear objective function. Due to their nonlinear and nonconvex nature, most approaches to solve these problems resort to metaheuristic techniques. The main drawbacks of such methodologies lie in the fact that they are not guaranteed to reach an optimal solution, and most of them require the fine-tuning of several parameters. This paper recasts the nonlinear DNR and OPGD problems into linear equivalents to obtain a mixed-integer linear programming (MILP) model that guarantees global optimal solutions. Several tests were carried out on benchmark EDNs evidencing the applicability and effectiveness of the proposed approach. It was found that when no DG units are considered, the proposed model can find the same results reported in the specialized literature but in less computational time; furthermore, the inclusion of DG units along with DNR usually allows the model to find better solutions than those previously reported in the specialized literature.
AbstractList Distributed generation (DG) aims to generate part of the required electrical energy on a small scale closer to the places of consumption. Integration of DG into an existing electric distribution network (EDN) has technical, economic, and environmental benefits. DG placement is typically determined by investors and local conditions such as the availability of energy resources, space, and licenses, among other factors. When the location of DG is not a decision of the distribution network operator (DNO), the simultaneous integration of distribution network reconfiguration (DNR) and DG placement can maximize the benefits of DG and mitigate eventual negative impacts. DNR consists of altering the EDN topology to improve its performance while maintaining the radiality of the network. DNR and optimal placement of DG (OPDG) are challenging optimization problems since they involve integer and continuous variables subject to nonlinear constraints and a nonlinear objective function. Due to their nonlinear and nonconvex nature, most approaches to solve these problems resort to metaheuristic techniques. The main drawbacks of such methodologies lie in the fact that they are not guaranteed to reach an optimal solution, and most of them require the fine-tuning of several parameters. This paper recasts the nonlinear DNR and OPGD problems into linear equivalents to obtain a mixed-integer linear programming (MILP) model that guarantees global optimal solutions. Several tests were carried out on benchmark EDNs evidencing the applicability and effectiveness of the proposed approach. It was found that when no DG units are considered, the proposed model can find the same results reported in the specialized literature but in less computational time; furthermore, the inclusion of DG units along with DNR usually allows the model to find better solutions than those previously reported in the specialized literature.
Author Gallego Pareja, Luis A.
Gómez Carmona, Oscar
López-Lezama, Jesús M.
Author_xml – sequence: 1
  givenname: Luis A.
  orcidid: 0000-0002-0592-6190
  surname: Gallego Pareja
  fullname: Gallego Pareja, Luis A.
– sequence: 2
  givenname: Jesús M.
  orcidid: 0000-0002-2369-6173
  surname: López-Lezama
  fullname: López-Lezama, Jesús M.
– sequence: 3
  givenname: Oscar
  orcidid: 0000-0001-9646-6793
  surname: Gómez Carmona
  fullname: Gómez Carmona, Oscar
BookMark eNptkd1u1DAQhS1UJErpDU9giTukgB0ncXxZFSgrbWnFz7U1scfBS2IvjiPgVXhazC5qEcIXtnX0nTOjmcfkJMSAhDzl7IUQir3EwFumBOvEA3LKleoqzqQ4-ev_iJwvy46VIwQXQpySnxf02n9HW21CxhET3fqAkOhtimOCefZhpNfR4kRdTDR_RvrBz-uUIWBcF3qzz36Gib7yS05-WLOPgb7D_C2mL_Q9mhicH9cEBx2CvTPcTmBwxpBpdPdutPQKAx75J-Shg2nB8z_vGfn05vXHy7fV9uZqc3mxrYzoeK7apremgUZ2QpgWgA9WguwNA1EbC86hKfrQKFUuhlLJRvbcMMWbunC9OCObY66NsNP7VPpLP3QErw9CTKOGlL2ZUNfMsdbAUDvbN0I6JQfXd860jUNwVpWsZ8esfYpfV1yy3sU1hdK-rrtOlLm3oi7U8yNlUlyWhO6uKmf69yr1_SoLzP6Bjc-HAeUEfvqf5RcOX6WO
CitedBy_id crossref_primary_10_1007_s00202_024_02675_3
crossref_primary_10_1016_j_epsr_2024_110743
crossref_primary_10_1080_15325008_2024_2343403
crossref_primary_10_3390_en15196994
crossref_primary_10_1109_ACCESS_2024_3350207
crossref_primary_10_1007_s13369_023_08663_2
crossref_primary_10_1016_j_egyr_2024_02_031
crossref_primary_10_3390_cleantechnol4040076
crossref_primary_10_3390_en18123005
crossref_primary_10_1080_15567036_2023_2216167
crossref_primary_10_1109_ACCESS_2023_3319456
crossref_primary_10_3390_en17235840
crossref_primary_10_1016_j_segan_2023_101199
crossref_primary_10_1109_ACCESS_2023_3326758
crossref_primary_10_1016_j_est_2023_107962
crossref_primary_10_1155_etep_5580709
crossref_primary_10_3390_su15010854
crossref_primary_10_1002_adc2_227
crossref_primary_10_3390_en17194877
crossref_primary_10_1016_j_compeleceng_2025_110061
crossref_primary_10_3390_su162310307
crossref_primary_10_1007_s40313_024_01134_5
crossref_primary_10_3390_en16114340
crossref_primary_10_3390_en17112633
crossref_primary_10_3390_en16196998
crossref_primary_10_3390_en18112961
crossref_primary_10_3390_en16176154
crossref_primary_10_1109_ACCESS_2024_3387400
crossref_primary_10_1109_ACCESS_2025_3547277
crossref_primary_10_3390_en15249419
crossref_primary_10_1016_j_egyr_2024_07_042
crossref_primary_10_3390_su15065171
Cites_doi 10.1109/ACCESS.2021.3083688
10.1016/j.ijepes.2021.107049
10.1109/ACCESS.2020.3027654
10.1109/59.486140
10.3390/en12030553
10.1109/TPWRS.2012.2184307
10.1109/ACCESS.2017.2726586
10.1109/TPWRS.2005.846180
10.1109/TPWRD.2009.2027510
10.1016/j.renene.2017.12.106
10.3390/en12193779
10.1109/TPWRS.2005.846096
10.1109/TPWRS.2010.2076839
10.1016/j.epsr.2006.06.005
10.1007/s00500-019-04597-w
10.15446/dyna.v82n192.48578
10.1109/KBEI.2017.8324880
10.1016/j.aej.2020.12.012
10.1016/j.ijepes.2015.02.026
10.1016/j.asoc.2020.106867
10.1016/j.ijepes.2014.06.076
10.1109/TPWRS.2014.2332953
10.1016/j.enconman.2009.04.022
10.1016/j.ijepes.2015.11.039
10.1080/15325000500240854
10.1007/s40313-013-0070-x
10.1016/j.epsr.2012.01.014
10.1109/61.107303
10.1049/iet-gtd.2010.0020
10.1109/TPWRS.2013.2238259
10.1049/iet-gtd.2020.0917
10.1109/TPWRS.2008.926084
10.1109/TPWRD.2014.2300854
10.1049/iet-gtd.2016.0539
10.1109/JSYST.2018.2808197
10.1109/ACCESS.2019.2918480
10.1109/TPWRS.2015.2481508
10.1049/iet-gtd.2012.0737
10.1016/j.epsr.2010.01.001
10.1080/01430750.2019.1583604
10.1016/S0378-7796(02)00041-X
10.1016/j.egyr.2021.12.023
10.1109/ACCESS.2019.2947308
10.3390/en14206699
10.1016/S0142-0615(99)00057-5
10.1016/j.ijepes.2013.11.008
10.3390/en15051686
10.1080/15325000701735389
10.1109/TPWRS.2015.2418333
10.1016/j.asoc.2020.106293
10.1016/j.epsr.2012.12.005
10.1016/j.energy.2014.09.004
10.1109/PESMG.2013.6672876
10.1109/59.761869
10.35833/MPCE.2019.000055
10.11648/j.ijepe.20160505.11
10.1016/j.epsr.2009.05.004
10.1109/TPWRS.2014.2360363
10.3390/en10101449
10.1109/61.25637
10.1016/0378-7796(94)90018-3
10.3390/en11123351
10.1080/15325008.2019.1689449
10.1080/15325008.2016.1183729
10.3390/en14217145
10.1049/iet-gtd.2015.0303
10.1016/j.ijepes.2012.11.027
10.1109/59.207317
10.1016/j.scs.2019.101514
10.1016/j.asoc.2016.07.031
10.1016/j.ijepes.2014.06.011
10.3390/app11199207
10.1016/j.asej.2020.06.005
10.1109/TPWRS.2006.879290
10.1109/TPWRS.2011.2161349
10.1109/TSTE.2015.2406915
10.1109/61.193906
10.1016/S0378-7796(01)00124-9
10.1016/S0142-0615(00)00044-2
10.1049/iet-gtd.2019.0264
ContentType Journal Article
Copyright 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID AAYXX
CITATION
ABUWG
AFKRA
AZQEC
BENPR
CCPQU
DWQXO
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
DOA
DOI 10.3390/en15093063
DatabaseName CrossRef
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials - QC
ProQuest Central
ProQuest One
ProQuest Central
ProQuest Central Premium
ProQuest One Academic
Publicly Available Content Database (ProQuest)
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest One Academic Eastern Edition
ProQuest Central (Alumni Edition)
ProQuest One Community College
ProQuest Central China
ProQuest Central
ProQuest One Academic UKI Edition
ProQuest Central Korea
ProQuest Central (New)
ProQuest One Academic
ProQuest One Academic (New)
DatabaseTitleList Publicly Available Content Database

CrossRef
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: PIMPY
  name: ProQuest - Publicly Available Content Database
  url: http://search.proquest.com/publiccontent
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1996-1073
ExternalDocumentID oai_doaj_org_article_20f05cab2fd8437f97bf86fc54feafd9
10_3390_en15093063
GroupedDBID 29G
2WC
2XV
5GY
5VS
7XC
8FE
8FG
8FH
AADQD
AAHBH
AAYXX
ABDBF
ACUHS
ADBBV
ADMLS
AENEX
AFFHD
AFKRA
AFZYC
ALMA_UNASSIGNED_HOLDINGS
BCNDV
BENPR
CCPQU
CITATION
CS3
DU5
EBS
ESX
FRP
GROUPED_DOAJ
GX1
I-F
IAO
ITC
KQ8
L6V
L8X
MODMG
M~E
OK1
OVT
P2P
PHGZM
PHGZT
PIMPY
PROAC
TR2
TUS
ABUWG
AZQEC
DWQXO
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
ID FETCH-LOGICAL-c361t-548dc4a47633c5aa1bd7a78c0a32cdaffec3c5b4995b40e7974781c09142a7883
IEDL.DBID DOA
ISICitedReferencesCount 38
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000794611900001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1996-1073
IngestDate Fri Oct 03 12:52:54 EDT 2025
Mon Jun 30 07:32:15 EDT 2025
Sat Nov 29 07:12:24 EST 2025
Tue Nov 18 22:13:37 EST 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 9
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c361t-548dc4a47633c5aa1bd7a78c0a32cdaffec3c5b4995b40e7974781c09142a7883
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0002-0592-6190
0000-0002-2369-6173
0000-0001-9646-6793
OpenAccessLink https://doaj.org/article/20f05cab2fd8437f97bf86fc54feafd9
PQID 2663003532
PQPubID 2032402
ParticipantIDs doaj_primary_oai_doaj_org_article_20f05cab2fd8437f97bf86fc54feafd9
proquest_journals_2663003532
crossref_primary_10_3390_en15093063
crossref_citationtrail_10_3390_en15093063
PublicationCentury 2000
PublicationDate 2022-05-01
PublicationDateYYYYMMDD 2022-05-01
PublicationDate_xml – month: 05
  year: 2022
  text: 2022-05-01
  day: 01
PublicationDecade 2020
PublicationPlace Basel
PublicationPlace_xml – name: Basel
PublicationTitle Energies (Basel)
PublicationYear 2022
Publisher MDPI AG
Publisher_xml – name: MDPI AG
References Abdelaziz (ref_14) 2009; 79
Mahmoud (ref_34) 2016; 31
Sanjay (ref_37) 2017; 5
Abdelaziz (ref_25) 2010; 80
Eldurssi (ref_19) 2015; 30
Shirmohammadi (ref_5) 1989; 4
Raut (ref_61) 2020; 92
Franco (ref_63) 2013; 48
ref_57
ref_11
ref_10
ref_53
ref_52
Schmidt (ref_76) 2005; 20
Wang (ref_18) 2013; 28
Lavorato (ref_7) 2012; 27
Nara (ref_75) 1992; 7
ref_15
Salah (ref_69) 2018; 8
Quadri (ref_59) 2020; 24
Ahmadi (ref_8) 2015; 64
Mahdavi (ref_33) 2021; 9
Seyedi (ref_85) 2017; 11
Sarfi (ref_4) 1996; 11
McDermott (ref_79) 1999; 14
Ali (ref_40) 2021; 9
Murthy (ref_43) 2012; 3
ref_66
ref_21
Cespedes (ref_65) 1990; 5
Rahiminejad (ref_50) 2016; 44
Kashem (ref_71) 2000; 22
Arun (ref_84) 2009; 50
Brigatto (ref_29) 2020; 14
ref_27
ref_26
Ali (ref_38) 2022; 8
Franco (ref_42) 2013; 97
Chiou (ref_68) 2005; 20
Sambaiah (ref_56) 2021; 42
Akbari (ref_35) 2018; 12
Zhang (ref_24) 2007; 77
Aman (ref_49) 2016; 10
Kashem (ref_83) 2001; 23
Raju (ref_81) 2008; 23
Sedighizadeh (ref_46) 2014; 76
Hijazi (ref_6) 2015; 72
Khodr (ref_82) 2009; 24
Narasimham (ref_28) 2011; 26
Imran (ref_45) 2014; 63
Shaheen (ref_62) 2021; 98
Haghighat (ref_31) 2016; 31
Gomes (ref_86) 2014; 56
(ref_2) 2021; 60
Bayat (ref_48) 2016; 77
Hormozi (ref_51) 2016; 5
Gallego (ref_64) 2021; 131
Ganguly (ref_39) 2015; 6
Salah (ref_55) 2018; 121
Ferdavani (ref_78) 2013; 7
Kumar (ref_67) 2020; 16
Chang (ref_73) 1994; 29
Taylor (ref_80) 2012; 27
Civanlar (ref_3) 1988; 3
Gerez (ref_23) 2019; 7
Castro (ref_20) 2010; 4
Borges (ref_32) 2014; 25
ref_44
Su (ref_72) 2001; 58
Gomes (ref_12) 2006; 21
Nguyen (ref_60) 2021; 12
Amin (ref_22) 2019; 13
ref_1
Zhu (ref_16) 2002; 62
Muthukumar (ref_47) 2017; 52
(ref_74) 2012; 88
Elkadeem (ref_41) 2019; 7
Sivanagaraju (ref_17) 2006; 34
Eid (ref_36) 2020; 8
Siahbalaee (ref_58) 2019; 47
Ahmadi (ref_70) 2015; 30
Ahmadi (ref_77) 2015; 30
Nazarian (ref_30) 2019; 47
Sivanagaraju (ref_13) 2008; 36
Saleh (ref_54) 2018; 14
Agudelo (ref_9) 2015; 82
References_xml – volume: 9
  start-page: 79961
  year: 2021
  ident: ref_33
  article-title: An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2021.3083688
– volume: 131
  start-page: 107049
  year: 2021
  ident: ref_64
  article-title: A fast-specialized point estimate method for the probabilistic optimal power flow in distribution systems with renewable distributed generation
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2021.107049
– volume: 8
  start-page: 178493
  year: 2020
  ident: ref_36
  article-title: An Enhanced Artificial Ecosystem-Based Optimization for Optimal Allocation of Multiple Distributed Generations
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2020.3027654
– volume: 11
  start-page: 504
  year: 1996
  ident: ref_4
  article-title: Distribution system reconfiguration for loss reduction: An algorithm based on network partitioning theory
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/59.486140
– ident: ref_57
  doi: 10.3390/en12030553
– volume: 27
  start-page: 1407
  year: 2012
  ident: ref_80
  article-title: Convex Models of Distribution System Reconfiguration
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2012.2184307
– volume: 5
  start-page: 14807
  year: 2017
  ident: ref_37
  article-title: Optimal Allocation of Distributed Generation Using Hybrid Grey Wolf Optimizer
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2017.2726586
– volume: 20
  start-page: 1311
  year: 2005
  ident: ref_76
  article-title: Fast reconfiguration of distribution systems considering loss minimization
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2005.846180
– volume: 24
  start-page: 2166
  year: 2009
  ident: ref_82
  article-title: Distribution Systems Reconfiguration Based on OPF Using Benders Decomposition
  publication-title: IEEE Trans. Power Deliv.
  doi: 10.1109/TPWRD.2009.2027510
– ident: ref_26
– volume: 121
  start-page: 66
  year: 2018
  ident: ref_55
  article-title: Optimal network reconfiguration and renewable DG integration considering time sequence variation in load and DGs
  publication-title: Renew. Energy
  doi: 10.1016/j.renene.2017.12.106
– ident: ref_1
  doi: 10.3390/en12193779
– volume: 20
  start-page: 668
  year: 2005
  ident: ref_68
  article-title: Variable scaling hybrid differential evolution for solving network reconfiguration of distribution systems
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2005.846096
– volume: 26
  start-page: 1080
  year: 2011
  ident: ref_28
  article-title: Optimal Network Reconfiguration of Large-Scale Distribution System Using Harmony Search Algorithm
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2010.2076839
– volume: 77
  start-page: 685
  year: 2007
  ident: ref_24
  article-title: An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/j.epsr.2006.06.005
– volume: 24
  start-page: 11315
  year: 2020
  ident: ref_59
  article-title: A hybrid technique for simultaneous network reconfiguration and optimal placement of distributed generation resources
  publication-title: Soft Comput.
  doi: 10.1007/s00500-019-04597-w
– volume: 82
  start-page: 78
  year: 2015
  ident: ref_9
  article-title: Vulnerability assessment of power systems to intentional attacks using a specialized genetic algorithm
  publication-title: Dyna
  doi: 10.15446/dyna.v82n192.48578
– ident: ref_52
  doi: 10.1109/KBEI.2017.8324880
– volume: 60
  start-page: 2093
  year: 2021
  ident: ref_2
  article-title: Optimal coordination of over-current relays in microgrids considering multiple characteristic curves
  publication-title: Alex. Eng. J.
  doi: 10.1016/j.aej.2020.12.012
– volume: 72
  start-page: 136
  year: 2015
  ident: ref_6
  article-title: Optimal distribution systems reconfiguration for radial and meshed grids
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2015.02.026
– volume: 98
  start-page: 106867
  year: 2021
  ident: ref_62
  article-title: Equilibrium optimization algorithm for network reconfiguration and distributed generation allocation in power systems
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2020.106867
– volume: 64
  start-page: 293
  year: 2015
  ident: ref_8
  article-title: Mathematical representation of radiality constraint in distribution system reconfiguration problem
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2014.06.076
– volume: 30
  start-page: 593
  year: 2015
  ident: ref_19
  article-title: A Fast Nondominated Sorting Guided Genetic Algorithm for Multi-Objective Power Distribution System Reconfiguration Problem
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2014.2332953
– volume: 50
  start-page: 2148
  year: 2009
  ident: ref_84
  article-title: A new reconfiguration scheme for voltage stability enhancement of radial distribution systems
  publication-title: Energy Convers. Manag.
  doi: 10.1016/j.enconman.2009.04.022
– volume: 77
  start-page: 360
  year: 2016
  ident: ref_48
  article-title: Optimal siting and sizing of distributed generation accompanied by reconfiguration of distribution networks for maximum loss reduction by using a new UVDA-based heuristic method
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2015.11.039
– volume: 34
  start-page: 249
  year: 2006
  ident: ref_17
  article-title: An Efficient Genetic Algorithm for Loss Minimum Distribution System Reconfiguration
  publication-title: Electr. Power Components Syst.
  doi: 10.1080/15325000500240854
– volume: 25
  start-page: 103
  year: 2014
  ident: ref_32
  article-title: Optimal Reconfiguration of Electrical Distribution Systems Using Mathematical Programming
  publication-title: J. Control. Autom. Electr. Syst.
  doi: 10.1007/s40313-013-0070-x
– volume: 16
  start-page: 181
  year: 2020
  ident: ref_67
  article-title: Simultaneous Reconfiguration and Optimal Capacitor Placement Using Adaptive Whale Optimization Algorithm for Radial Distribution System
  publication-title: J. Electr. Eng. Technol.
– volume: 88
  start-page: 137
  year: 2012
  ident: ref_74
  article-title: Mixed-integer linear programming model for solving reconfiguration problems in large-scale distribution systems
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/j.epsr.2012.01.014
– volume: 5
  start-page: 391
  year: 1990
  ident: ref_65
  article-title: New method for the analysis of distribution networks
  publication-title: IEEE Trans. Power Deliv.
  doi: 10.1109/61.107303
– volume: 4
  start-page: 1213
  year: 2010
  ident: ref_20
  article-title: Distribution systems operation optimization through reconfiguration and capacitor allocation by a dedicated genetic algorithm
  publication-title: IET Gener. Transm. Distrib.
  doi: 10.1049/iet-gtd.2010.0020
– volume: 28
  start-page: 3638
  year: 2013
  ident: ref_18
  article-title: Determination of Power Distribution Network Configuration Using Non-Revisiting Genetic Algorithm
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2013.2238259
– volume: 14
  start-page: 6526
  year: 2020
  ident: ref_29
  article-title: Methodology of solution for the distribution network reconfiguration problem based on improved harmony search algorithm
  publication-title: IET Gener. Transm. Distrib.
  doi: 10.1049/iet-gtd.2020.0917
– volume: 23
  start-page: 1280
  year: 2008
  ident: ref_81
  article-title: An Efficient Algorithm for Minimum Loss Reconfiguration of Distribution System Based on Sensitivity and Heuristics
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2008.926084
– volume: 14
  start-page: 36
  year: 2018
  ident: ref_54
  article-title: Enhancement of radial distribution network with distributed generation and system reconfiguration
  publication-title: J. Electr. Syst.
– volume: 30
  start-page: 25
  year: 2015
  ident: ref_70
  article-title: Distribution System Optimization Based on a Linear Power-Flow Formulation
  publication-title: IEEE Trans. Power Deliv.
  doi: 10.1109/TPWRD.2014.2300854
– ident: ref_66
– volume: 11
  start-page: 82
  year: 2017
  ident: ref_85
  article-title: Reconfiguration of distribution networks considering coordination of the protective devices
  publication-title: IET Gener. Transm. Distrib.
  doi: 10.1049/iet-gtd.2016.0539
– volume: 12
  start-page: 3497
  year: 2018
  ident: ref_35
  article-title: Convex Models for Optimal Utility-Based Distributed Generation Allocation in Radial Distribution Systems
  publication-title: IEEE Syst. J.
  doi: 10.1109/JSYST.2018.2808197
– volume: 7
  start-page: 67874
  year: 2019
  ident: ref_23
  article-title: Distribution Network Reconfiguration Using Selective Firefly Algorithm and a Load Flow Analysis Criterion for Reducing the Search Space
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2918480
– volume: 31
  start-page: 2666
  year: 2016
  ident: ref_31
  article-title: Distribution System Reconfiguration Under Uncertain Load and Renewable Generation
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2015.2481508
– volume: 7
  start-page: 1492
  year: 2013
  ident: ref_78
  article-title: Reconfiguration of distribution system through two minimum-current neighbor-chain updating methods
  publication-title: Gener. Transm. Distrib. IET
  doi: 10.1049/iet-gtd.2012.0737
– volume: 80
  start-page: 943
  year: 2010
  ident: ref_25
  article-title: Distribution system reconfiguration using a modified Tabu Search algorithm
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/j.epsr.2010.01.001
– volume: 42
  start-page: 1018
  year: 2021
  ident: ref_56
  article-title: Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems
  publication-title: Int. J. Ambient Energy
  doi: 10.1080/01430750.2019.1583604
– volume: 8
  start-page: 345
  year: 2018
  ident: ref_69
  article-title: Optimal integration of distributed generations with network reconfiguration using a Pareto algorithm
  publication-title: Int. J. Renew. Energy Res.
– volume: 62
  start-page: 37
  year: 2002
  ident: ref_16
  article-title: Optimal reconfiguration of electrical distribution network using the refined genetic algorithm
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/S0378-7796(02)00041-X
– volume: 8
  start-page: 582
  year: 2022
  ident: ref_38
  article-title: An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks
  publication-title: Energy Rep.
  doi: 10.1016/j.egyr.2021.12.023
– volume: 7
  start-page: 164887
  year: 2019
  ident: ref_41
  article-title: Optimal Planning of Renewable Energy-Integrated Distribution System Considering Uncertainties
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2947308
– ident: ref_21
  doi: 10.3390/en14206699
– volume: 22
  start-page: 269
  year: 2000
  ident: ref_71
  article-title: A new approach of distribution system reconfiguration for loss minimization
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/S0142-0615(99)00057-5
– volume: 56
  start-page: 64
  year: 2014
  ident: ref_86
  article-title: Artificial Immune Systems applied to the reconfiguration of electrical power distribution networks for energy loss minimization
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2013.11.008
– ident: ref_11
  doi: 10.3390/en15051686
– volume: 36
  start-page: 513
  year: 2008
  ident: ref_13
  article-title: Discrete Particle Swarm Optimization to Network Reconfiguration for Loss Reduction and Load Balancing
  publication-title: Electr. Power Components Syst.
  doi: 10.1080/15325000701735389
– volume: 31
  start-page: 960
  year: 2016
  ident: ref_34
  article-title: Optimal Distributed Generation Allocation in Distribution Systems for Loss Minimization
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2015.2418333
– volume: 92
  start-page: 106293
  year: 2020
  ident: ref_61
  article-title: An improved sine–cosine algorithm for simultaneous network reconfiguration and DG allocation in power distribution systems
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2020.106293
– volume: 3
  start-page: 50
  year: 2012
  ident: ref_43
  article-title: Artificial bee colony algorithm for distribution feeder reconfiguration with distributed generation
  publication-title: Int. J. Eng. Sci. Emerg. Technol.
– volume: 97
  start-page: 133
  year: 2013
  ident: ref_42
  article-title: A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/j.epsr.2012.12.005
– volume: 76
  start-page: 920
  year: 2014
  ident: ref_46
  article-title: Application of the hybrid Big Bang-Big Crunch algorithm to optimal reconfiguration and distributed generation power allocation in distribution systems
  publication-title: Energy
  doi: 10.1016/j.energy.2014.09.004
– ident: ref_44
  doi: 10.1109/PESMG.2013.6672876
– volume: 14
  start-page: 478
  year: 1999
  ident: ref_79
  article-title: A heuristic nonlinear constructive method for distribution system reconfiguration
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/59.761869
– volume: 9
  start-page: 404
  year: 2021
  ident: ref_40
  article-title: Optimal Site and Size of Distributed Generation Allocation in Radial Distribution Network Using Multi-objective Optimization
  publication-title: J. Mod. Power Syst. Clean Energy
  doi: 10.35833/MPCE.2019.000055
– volume: 5
  start-page: 163
  year: 2016
  ident: ref_51
  article-title: Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm
  publication-title: Int. J. Energy Power Eng.
  doi: 10.11648/j.ijepe.20160505.11
– volume: 79
  start-page: 1521
  year: 2009
  ident: ref_14
  article-title: Distribution Systems Reconfiguration using a modified particle swarm optimization algorithm
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/j.epsr.2009.05.004
– volume: 30
  start-page: 2073
  year: 2015
  ident: ref_77
  article-title: Linear Current Flow Equations With Application to Distribution Systems Reconfiguration
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2014.2360363
– ident: ref_10
  doi: 10.3390/en10101449
– volume: 4
  start-page: 1492
  year: 1989
  ident: ref_5
  article-title: Reconfiguration of electric distribution networks for resistive line losses reduction
  publication-title: IEEE Trans. Power Deliv.
  doi: 10.1109/61.25637
– volume: 29
  start-page: 227
  year: 1994
  ident: ref_73
  article-title: Network reconfiguration in distribution systems using simulated annealing
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/0378-7796(94)90018-3
– ident: ref_53
  doi: 10.3390/en11123351
– volume: 47
  start-page: 1475
  year: 2019
  ident: ref_58
  article-title: Reconfiguration and DG Sizing and Placement Using Improved Shuffled Frog Leaping Algorithm
  publication-title: Electr. Power Components Syst.
  doi: 10.1080/15325008.2019.1689449
– volume: 44
  start-page: 1631
  year: 2016
  ident: ref_50
  article-title: Simultaneous Distributed Generation Placement, Capacitor Placement, and Reconfiguration using a Modified Teaching-Learning-based Optimization Algorithm
  publication-title: Electr. Power Components Syst.
  doi: 10.1080/15325008.2016.1183729
– ident: ref_15
  doi: 10.3390/en14217145
– volume: 10
  start-page: 2277
  year: 2016
  ident: ref_49
  article-title: Optimum Tie Switches Allocation and DG Placement Based On Maximization of System Loadability Using Discrete Artificial Bee Colony (DABC) Algorithm
  publication-title: IET Gener. Transm. Distrib.
  doi: 10.1049/iet-gtd.2015.0303
– volume: 48
  start-page: 123
  year: 2013
  ident: ref_63
  article-title: A mixed-integer LP model for the optimal allocation of voltage regulators and capacitors in radial distribution systems
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2012.11.027
– volume: 7
  start-page: 1044
  year: 1992
  ident: ref_75
  article-title: Implementation of genetic algorithm for distribution systems loss minimum re-configuration
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/59.207317
– volume: 47
  start-page: 101514
  year: 2019
  ident: ref_30
  article-title: Multi-objective optimization model for optimal reconfiguration of distribution networks with demand response services
  publication-title: Sustain. Cities Soc.
  doi: 10.1016/j.scs.2019.101514
– volume: 52
  start-page: 1262
  year: 2017
  ident: ref_47
  article-title: Integrated approach of network reconfiguration with distributed generation and shunt capacitors placement for power loss minimization in radial distribution networks
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2016.07.031
– volume: 63
  start-page: 461
  year: 2014
  ident: ref_45
  article-title: A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2014.06.011
– ident: ref_27
  doi: 10.3390/app11199207
– volume: 12
  start-page: 665
  year: 2021
  ident: ref_60
  article-title: A novel method based on coyote algorithm for simultaneous network reconfiguration and distribution generation placement
  publication-title: Ain Shams Eng. J.
  doi: 10.1016/j.asej.2020.06.005
– volume: 21
  start-page: 1616
  year: 2006
  ident: ref_12
  article-title: A New Distribution System Reconfiguration Approach Using Optimum Power Flow and Sensitivity Analysis for Loss Reduction
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2006.879290
– volume: 27
  start-page: 172
  year: 2012
  ident: ref_7
  article-title: Imposing Radiality Constraints in Distribution System Optimization Problems
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2011.2161349
– volume: 6
  start-page: 688
  year: 2015
  ident: ref_39
  article-title: Distributed Generation Allocation on Radial Distribution Networks Under Uncertainties of Load and Generation Using Genetic Algorithm
  publication-title: IEEE Trans. Sustain. Energy
  doi: 10.1109/TSTE.2015.2406915
– volume: 3
  start-page: 1217
  year: 1988
  ident: ref_3
  article-title: Distribution feeder reconfiguration for loss reduction
  publication-title: IEEE Trans. Power Deliv.
  doi: 10.1109/61.193906
– volume: 58
  start-page: 97
  year: 2001
  ident: ref_72
  article-title: Feeder reconfiguration and capacitor setting for loss reduction of distribution systems
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/S0378-7796(01)00124-9
– volume: 23
  start-page: 295
  year: 2001
  ident: ref_83
  article-title: A geometrical approach for network reconfiguration based loss minimization in distribution systems
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/S0142-0615(00)00044-2
– volume: 13
  start-page: 5071
  year: 2019
  ident: ref_22
  article-title: Enhancement of Simultaneous Network Reconfiguration and DG Sizing via Hamming dataset approach and Firefly Algorithm
  publication-title: IET Gener. Transm. Distrib.
  doi: 10.1049/iet-gtd.2019.0264
SSID ssj0000331333
Score 2.487955
Snippet Distributed generation (DG) aims to generate part of the required electrical energy on a small scale closer to the places of consumption. Integration of DG...
SourceID doaj
proquest
crossref
SourceType Open Website
Aggregation Database
Enrichment Source
Index Database
StartPage 3063
SubjectTerms Algorithms
distributed generation
distribution systems
Electricity distribution
Heuristic
Linear programming
Mathematical programming
mixed-integer linear programming
Mutation
Optimization techniques
reconfiguration
SummonAdditionalLinks – databaseName: Publicly Available Content Database (ProQuest)
  dbid: PIMPY
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9QwEB7BlgM9tDzFtqWyBBcO1iaxd-OcqrZQlUOXSIBUTpHjx2qlNmn3UfW39NcyE3t3QSBOXKIoGSuRZjyebzz-BuC9lD7xJpfcy0RzqazjymSCF6bWQ5lpU_jQbCIfj9XlZVHG49HzWFa58omdow5sz1S3jU54YFtDGfMBLiuCNsFEdnRzy6mHFO21xoYaj2GLiLdUD7bKzxflj3XOJRECIZkILKUC0f7ANRgQFRg2i9_WpY6-_w_v3C05Z7v_92efwU4MPdlxsJXn8Mg1L2D7F0LCl_BwzC6m985yShRO3IwhVMWpwMpQxXWNQoy6p10xjHUZxo7s65RKEnXj2uWcfUH_c42f-EhsvLGRFhuHQnNGQLfx08ky2BzTjV0PKCmZT3lK1vrNaGdZYMUm-Vfw_ezTt9NzHrs3cCNG6YIjFLJGaokOTJih1mltc50rk2iRGaupWgWf14i48JK4nICNSg3GL2giCMzFa-g1bePeAEMf4aRJCU9L1Ouo0GnmElXbQuO9Un34sNJdZSK1OXXYuKoQ4pCeq42e-_BuLXsTCD3-KnVCJrCWIBLu7kE7m1RxTldZ4pOh0XXmrZIi90VeezXyZii9094WfThYWUcVPcO82hjD3r9f78PTjI5adMWVB9BbzJbuLTwxd4vpfHYYTfsnw_MOCQ
  priority: 102
  providerName: ProQuest
Title A Mixed-Integer Linear Programming Model for the Simultaneous Optimal Distribution Network Reconfiguration and Optimal Placement of Distributed Generation
URI https://www.proquest.com/docview/2663003532
https://doaj.org/article/20f05cab2fd8437f97bf86fc54feafd9
Volume 15
WOSCitedRecordID wos000794611900001&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
journalDatabaseRights – providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 1996-1073
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000331333
  issn: 1996-1073
  databaseCode: DOA
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 1996-1073
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000331333
  issn: 1996-1073
  databaseCode: M~E
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
– providerCode: PRVPQU
  databaseName: ProQuest - Publicly Available Content Database
  customDbUrl:
  eissn: 1996-1073
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000331333
  issn: 1996-1073
  databaseCode: PIMPY
  dateStart: 20080301
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/publiccontent
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl:
  eissn: 1996-1073
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000331333
  issn: 1996-1073
  databaseCode: BENPR
  dateStart: 20080301
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LS8QwEA6iHvQgPnF1lYBePBTbJt2mx13dRQ-7Fh-gp5LmIQWtsu6KJ3-Iv9aZpruuKHjxUkqYkJKZTOZLJ98Qcsi59a2KuWe5Lz0utPGECpmXqFxGPJQqsa7YRDwYiNvbJJ0p9YU5YY4e2E0cgHPrR0rmodWCs9gmcW5Fy6qIWyOtrq7uQdQzA6YqH8wYgC_m-EgZ4PpjU0Lok0CAzL7tQBVR_w8_XG0uvVWyUkeFtO2-Zo3MmXKdLM9wBW6QjzbtF29Ge3iGd2-GFFAkWClNXYLVIwhRLGz2QCEMpRDW0asCswVlaQDc0wtwDY8wxCkS5dY1rujA5YBTxKClLe7HzhyoLPW0Q4rn7HiESJ_sV2-jqSOsRvlNctPrXp-ceXVhBU-xVjDyAKVoxSUH38JUJGWQ61jGQvmShUpLTCSB9hzAEDx8EyPmEIGC0AK0B5iZbZH58qk024TC8jVcBQh1OSC9ViKD0Pgi14mEdyEa5Ggy2ZmqWcex-MVDBugDFZN9KaZBDqayz45r41epDupsKoH82FUDWE1WW032l9U0SHOi8axetC8ZxCoM_6yycOc_xtglSyHelaiyI5tkfjQcmz2yqF5Hxctwnyx0uoP0cr-yW3j237vQlp7307tPOY75Rw
linkProvider Directory of Open Access Journals
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VLRJwKG-xtIAl4MAhamJ7N84BoT6oump3iUSRyil1_Fit1CZlHzz-Cj-C38hMHrsgELceuESRM04s5_O8PJ4BeCGlD72JZeBlqAOprAuU4SJITK57kmuT-LrYRDwaqdPTJF2DH-1ZGAqrbHlixahtachHvo2CRNC2l-BvLj8FVDWKdlfbEho1LI7cty9oss1eD_bx_77k_ODtyd5h0FQVCIzoR_MAVXRrpJa4sITpaR3lNtaxMqEW3FhNURTYnqMlgJfQxaRwq8igXMWho8Eo8L3XYF0i2FUH1tPBMP249OqEQqDRJ-o8qEIk4bYrUOVKUDEXv0m-qkDAH_y_EmoHt_-36bgDG436zHZqvN-FNVfcg1u_JFW8D9932HDy1dmAnJ1jN2VobuNAWVpHol0gEaMKcOcM9XWG-i97P6GwSl24cjFj75CHXuAn9imjcFMMjI3qYHlGxnrhJ-NFvW6YLuyyQ0obEuRrZaVf9XaW1Zm9if4BfLiSyXkInaIs3CNgyOecNBH5BCSaxP1ER9yFKreJxnuluvCqRUdmmvTsVCXkPEMzjZCUrZDUhedL2ss6KclfqXYJZEsKSiReNZTTcdbwpYyHPuwZnXNvlRSxT-Lcq743Pemd9jbpwlaLv6zhbrNsBb7H_378DG4cngyPs-PB6GgTbnI6OlIFi25BZz5duCdw3XyeT2bTp81CYnB21WD9CVnJXz0
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9NAEB6VFCE4lLcIFFgJOHCwYu9u4vUBVYUQEZUGS4BUTma9jyhSa5c8ePyV_pT-Omb8SEAgbj1wsaz1rB_rb-e1szMAT6X0oTexDLwMdSCVdYEyXASJyXVfcm0SXxebiCcTdXSUpFtw3u6FobDKlidWjNqWhnzkPRQkgpa9BO_5JiwiHY72Tr8EVEGKVlrbcho1RA7cj29ovi1ejIf4r59xPnr94dWboKkwEBgxiJYBquvWSC1xkgnT1zrKbaxjZUItuLGaIiqwPUerAA-hi0n5VpFBGYufgcajwPtegm1slbID2-n4MP209vCEQqABKOqcqEIkYc8VqH4lqKSL36RgVSzgD1lQCbjR9f95aG7ATqNWs_16HtyELVfcgmu_JFu8DWf77HD23dmAnKBTN2dohuOLsrSOUDtBIkaV4Y4Z6vEM9WL2fkbhlrpw5WrB3iFvPcFHDCnTcFMkjE3qIHpGRnzhZ9NVPZ-YLuy6Q0oLFeSDZaXf9HaW1Rm_if4OfLyQwbkLnaIs3D1gyP-cNBH5CiSayoNER9yFKreJxnOluvC8RUpmmrTtVD3kOEPzjVCVbVDVhSdr2tM6WclfqV4S4NYUlGC8aijn06zhVxkPfdg3OufeKilin8S5VwNv-tI77W3Shd0Wi1nD9RbZBoj3_335MVxBhGZvx5ODB3CV046SKoZ0FzrL-co9hMvm63K2mD9q5hSDzxeN1Z9ZBWf-
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=A+Mixed-Integer+Linear+Programming+Model+for+the+Simultaneous+Optimal+Distribution+Network+Reconfiguration+and+Optimal+Placement+of+Distributed+Generation&rft.jtitle=Energies+%28Basel%29&rft.au=Gallego+Pareja%2C+Luis+A.&rft.au=L%C3%B3pez-Lezama%2C+Jes%C3%BAs+M.&rft.au=G%C3%B3mez+Carmona%2C+Oscar&rft.date=2022-05-01&rft.issn=1996-1073&rft.eissn=1996-1073&rft.volume=15&rft.issue=9&rft.spage=3063&rft_id=info:doi/10.3390%2Fen15093063&rft.externalDBID=n%2Fa&rft.externalDocID=10_3390_en15093063
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1996-1073&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1996-1073&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1996-1073&client=summon