Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration

Bibliographic Details
Main Author: Ayikpa, Malinwo Estone [UNESP]
Publication Date: 2025
Format: Conference object
Language: eng
Source: Repositório Institucional da UNESP
Download full: http://dx.doi.org/10.1109/TPEC63981.2025.10906970
https://hdl.handle.net/11449/305283
Summary: The distribution network is likely to experience higher active losses and lower voltage profiles due to its radial topology, the nature of loads and transformers, and recently with increased penetration of distributed generations. The power quality study in the distribution system aims to decrease power losses and mitigate voltage drops. This has been carried out using empirical techniques or exact optimization methods. However, distribution feeder reconfiguration (DFR) has become the best way to reduce losses and improve voltage profiles in the distribution system. In this study, the DFR was addressed simultaneously with the integration of distributed generation (DG) and capacitor bank (CB) into a large-scale distribution network. The stochastic fractal search algorithm (SFS) has been implemented to solve this problem. The loss-sensitive factor (LSF) approach was applied to reduce the search space of candidate buses for DG and CB placement when initializing the optimization variables and when correcting the boundary violation during the optimization process. Furthermore, we proposed two efficient mathematical strategies to control and correct the violation of tie-switches bounds at the diffusion and updating stages of the SFS, and to define CB sizes for better integration of them into the grid. The proposed algorithm was tested on the 136-bus distribution network. Different simulation cases have been carried out, and the results showed a significant impact on reducing the losses and enhancing the minimum voltage value of the feeder, especially when distributed generations and capacitor banks are simultaneously addressed in the DFR problem.
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spelling Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfigurationcapacitor bankcombinatorial optimizationdistributed generationDistribution feeder reconfigurationmathematical strategypower losses reductionstochastic fractal searchThe distribution network is likely to experience higher active losses and lower voltage profiles due to its radial topology, the nature of loads and transformers, and recently with increased penetration of distributed generations. The power quality study in the distribution system aims to decrease power losses and mitigate voltage drops. This has been carried out using empirical techniques or exact optimization methods. However, distribution feeder reconfiguration (DFR) has become the best way to reduce losses and improve voltage profiles in the distribution system. In this study, the DFR was addressed simultaneously with the integration of distributed generation (DG) and capacitor bank (CB) into a large-scale distribution network. The stochastic fractal search algorithm (SFS) has been implemented to solve this problem. The loss-sensitive factor (LSF) approach was applied to reduce the search space of candidate buses for DG and CB placement when initializing the optimization variables and when correcting the boundary violation during the optimization process. Furthermore, we proposed two efficient mathematical strategies to control and correct the violation of tie-switches bounds at the diffusion and updating stages of the SFS, and to define CB sizes for better integration of them into the grid. The proposed algorithm was tested on the 136-bus distribution network. Different simulation cases have been carried out, and the results showed a significant impact on reducing the losses and enhancing the minimum voltage value of the feeder, especially when distributed generations and capacitor banks are simultaneously addressed in the DFR problem.Sao Paulo State University (UNESP) School of Engineering Dept. of Electrical EngineeringSao Paulo State University (UNESP) School of Engineering Dept. of Electrical EngineeringUniversidade Estadual Paulista (UNESP)Ayikpa, Malinwo Estone [UNESP]2025-04-29T20:02:40Z2025-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/TPEC63981.2025.109069702025 IEEE Texas Power and Energy Conference, TPEC 2025.https://hdl.handle.net/11449/30528310.1109/TPEC63981.2025.109069702-s2.0-105001056703Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2025 IEEE Texas Power and Energy Conference, TPEC 2025info:eu-repo/semantics/openAccess2025-04-30T14:32:40Zoai:repositorio.unesp.br:11449/305283Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462025-04-30T14:32:40Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration
title Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration
spellingShingle Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration
Ayikpa, Malinwo Estone [UNESP]
capacitor bank
combinatorial optimization
distributed generation
Distribution feeder reconfiguration
mathematical strategy
power losses reduction
stochastic fractal search
title_short Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration
title_full Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration
title_fullStr Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration
title_full_unstemmed Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration
title_sort Optimal Placement and Sizing of Distributed Generations and Capacitor Banks in Large-Scale Distribution Network Using Feeder Reconfiguration
author Ayikpa, Malinwo Estone [UNESP]
author_facet Ayikpa, Malinwo Estone [UNESP]
author_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Ayikpa, Malinwo Estone [UNESP]
dc.subject.por.fl_str_mv capacitor bank
combinatorial optimization
distributed generation
Distribution feeder reconfiguration
mathematical strategy
power losses reduction
stochastic fractal search
topic capacitor bank
combinatorial optimization
distributed generation
Distribution feeder reconfiguration
mathematical strategy
power losses reduction
stochastic fractal search
description The distribution network is likely to experience higher active losses and lower voltage profiles due to its radial topology, the nature of loads and transformers, and recently with increased penetration of distributed generations. The power quality study in the distribution system aims to decrease power losses and mitigate voltage drops. This has been carried out using empirical techniques or exact optimization methods. However, distribution feeder reconfiguration (DFR) has become the best way to reduce losses and improve voltage profiles in the distribution system. In this study, the DFR was addressed simultaneously with the integration of distributed generation (DG) and capacitor bank (CB) into a large-scale distribution network. The stochastic fractal search algorithm (SFS) has been implemented to solve this problem. The loss-sensitive factor (LSF) approach was applied to reduce the search space of candidate buses for DG and CB placement when initializing the optimization variables and when correcting the boundary violation during the optimization process. Furthermore, we proposed two efficient mathematical strategies to control and correct the violation of tie-switches bounds at the diffusion and updating stages of the SFS, and to define CB sizes for better integration of them into the grid. The proposed algorithm was tested on the 136-bus distribution network. Different simulation cases have been carried out, and the results showed a significant impact on reducing the losses and enhancing the minimum voltage value of the feeder, especially when distributed generations and capacitor banks are simultaneously addressed in the DFR problem.
publishDate 2025
dc.date.none.fl_str_mv 2025-04-29T20:02:40Z
2025-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/TPEC63981.2025.10906970
2025 IEEE Texas Power and Energy Conference, TPEC 2025.
https://hdl.handle.net/11449/305283
10.1109/TPEC63981.2025.10906970
2-s2.0-105001056703
url http://dx.doi.org/10.1109/TPEC63981.2025.10906970
https://hdl.handle.net/11449/305283
identifier_str_mv 2025 IEEE Texas Power and Energy Conference, TPEC 2025.
10.1109/TPEC63981.2025.10906970
2-s2.0-105001056703
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2025 IEEE Texas Power and Energy Conference, TPEC 2025
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
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 repositoriounesp@unesp.br
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