Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm

Detalhes bibliográficos
Autor(a) principal: Muhammad, Munir Azam
Data de Publicação: 2020
Outros Autores: Mokhlis, Hazlie, Naidu, Kanendra, Amin, Adil, Franco, John F. [UNESP], Othman, Mohamadariff
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.35833/MPCE.2018.000503
http://hdl.handle.net/11449/196830
Resumo: The integration of network reconfiguration and distributed generation (DG) can enhance the performances of overall networks. Thus, proper sizing and siting of DG need to be determined, otherwise it will cause degradation in system performance. However, determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space. This search space mostly contains non-radial network configurations. Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution. To reduce the searching complexity, this paper considers the discretized network reconfiguration via dataset approach. Water cycle algorithm (WCA) is used to obtain the near optimal solution of network reconfiguration, and sizing and sitting of DG. In addition, the power factor of DG is also optimized to reduce the power loss. The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor. The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima. The proposed method out-performs other technique such as harmony search algorithm (HSA), fireworks algorithm (FWA), Cuckoo search algorithm (CSA) and uniform voltage distribution based constructive algorithm (UVDA) and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20% and 27.88%, respectively.
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spelling Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle AlgorithmReactive power injectionsizing and siting of distributed generation (DG)dataset approachactive distribution networkpower systemThe integration of network reconfiguration and distributed generation (DG) can enhance the performances of overall networks. Thus, proper sizing and siting of DG need to be determined, otherwise it will cause degradation in system performance. However, determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space. This search space mostly contains non-radial network configurations. Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution. To reduce the searching complexity, this paper considers the discretized network reconfiguration via dataset approach. Water cycle algorithm (WCA) is used to obtain the near optimal solution of network reconfiguration, and sizing and sitting of DG. In addition, the power factor of DG is also optimized to reduce the power loss. The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor. The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima. The proposed method out-performs other technique such as harmony search algorithm (HSA), fireworks algorithm (FWA), Cuckoo search algorithm (CSA) and uniform voltage distribution based constructive algorithm (UVDA) and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20% and 27.88%, respectively.University of MalayaUniv Malaya, Fac Engn, Dept Elect Engn, Kuala Lumpur 50603, MalaysiaUniv Kuala Lumpur, British Malaysian Inst, Elect Technol Sect, Bt 8,Jalan Sungai Pusu, Gombak 53100, Selangor Daryl, MalaysiaSao Paulo State Univ, Campus Rosana, BR-19274000 Rosana, BrazilSao Paulo State Univ, Campus Rosana, BR-19274000 Rosana, BrazilUniversity of Malaya: GPF016A-2019Ieee-inst Electrical Electronics Engineers IncUniv MalayaUniv Kuala LumpurUniversidade Estadual Paulista (Unesp)Muhammad, Munir AzamMokhlis, HazlieNaidu, KanendraAmin, AdilFranco, John F. [UNESP]Othman, Mohamadariff2020-12-10T19:57:32Z2020-12-10T19:57:32Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article86-93http://dx.doi.org/10.35833/MPCE.2018.000503Journal Of Modern Power Systems And Clean Energy. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 8, n. 1, p. 86-93, 2020.2196-5625http://hdl.handle.net/11449/19683010.35833/MPCE.2018.000503WOS:000528860300009Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal Of Modern Power Systems And Clean Energyinfo:eu-repo/semantics/openAccess2021-10-23T07:34:09Zoai:repositorio.unesp.br:11449/196830Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T07:34:09Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm
title Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm
spellingShingle Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm
Muhammad, Munir Azam
Reactive power injection
sizing and siting of distributed generation (DG)
dataset approach
active distribution network
power system
title_short Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm
title_full Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm
title_fullStr Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm
title_full_unstemmed Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm
title_sort Distribution Network Planning Enhancement via Network Reconfiguration and DG Integration Using Dataset Approach and Water Cycle Algorithm
author Muhammad, Munir Azam
author_facet Muhammad, Munir Azam
Mokhlis, Hazlie
Naidu, Kanendra
Amin, Adil
Franco, John F. [UNESP]
Othman, Mohamadariff
author_role author
author2 Mokhlis, Hazlie
Naidu, Kanendra
Amin, Adil
Franco, John F. [UNESP]
Othman, Mohamadariff
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Univ Malaya
Univ Kuala Lumpur
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Muhammad, Munir Azam
Mokhlis, Hazlie
Naidu, Kanendra
Amin, Adil
Franco, John F. [UNESP]
Othman, Mohamadariff
dc.subject.por.fl_str_mv Reactive power injection
sizing and siting of distributed generation (DG)
dataset approach
active distribution network
power system
topic Reactive power injection
sizing and siting of distributed generation (DG)
dataset approach
active distribution network
power system
description The integration of network reconfiguration and distributed generation (DG) can enhance the performances of overall networks. Thus, proper sizing and siting of DG need to be determined, otherwise it will cause degradation in system performance. However, determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space. This search space mostly contains non-radial network configurations. Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution. To reduce the searching complexity, this paper considers the discretized network reconfiguration via dataset approach. Water cycle algorithm (WCA) is used to obtain the near optimal solution of network reconfiguration, and sizing and sitting of DG. In addition, the power factor of DG is also optimized to reduce the power loss. The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor. The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima. The proposed method out-performs other technique such as harmony search algorithm (HSA), fireworks algorithm (FWA), Cuckoo search algorithm (CSA) and uniform voltage distribution based constructive algorithm (UVDA) and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20% and 27.88%, respectively.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-10T19:57:32Z
2020-12-10T19:57:32Z
2020-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.35833/MPCE.2018.000503
Journal Of Modern Power Systems And Clean Energy. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 8, n. 1, p. 86-93, 2020.
2196-5625
http://hdl.handle.net/11449/196830
10.35833/MPCE.2018.000503
WOS:000528860300009
url http://dx.doi.org/10.35833/MPCE.2018.000503
http://hdl.handle.net/11449/196830
identifier_str_mv Journal Of Modern Power Systems And Clean Energy. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 8, n. 1, p. 86-93, 2020.
2196-5625
10.35833/MPCE.2018.000503
WOS:000528860300009
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal Of Modern Power Systems And Clean Energy
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 86-93
dc.publisher.none.fl_str_mv Ieee-inst Electrical Electronics Engineers Inc
publisher.none.fl_str_mv Ieee-inst Electrical Electronics Engineers Inc
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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