Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach

The problem of optimal siting and dimensioning of photovoltaic (PV) generators in medium-voltage distribution networks is addressed in this research from the perspective of combinatorial optimization. The exact mixed-integer programming (MINLP) model is solved using a master–slave (MS) optimization...

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Autores:
Montoya, Oscar Danilo
Grisales-Noreña, Luis Fernando
Ramos-Paja, Carlos Andres
Tipo de recurso:
Fecha de publicación:
2022
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/12431
Acceso en línea:
https://hdl.handle.net/20.500.12585/12431
Palabra clave:
Placement;
Active Distribution Network;
Voltage Stability
LEMB
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.spa.fl_str_mv Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach
title Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach
spellingShingle Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach
Placement;
Active Distribution Network;
Voltage Stability
LEMB
title_short Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach
title_full Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach
title_fullStr Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach
title_full_unstemmed Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach
title_sort Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach
dc.creator.fl_str_mv Montoya, Oscar Danilo
Grisales-Noreña, Luis Fernando
Ramos-Paja, Carlos Andres
dc.contributor.author.none.fl_str_mv Montoya, Oscar Danilo
Grisales-Noreña, Luis Fernando
Ramos-Paja, Carlos Andres
dc.subject.keywords.spa.fl_str_mv Placement;
Active Distribution Network;
Voltage Stability
topic Placement;
Active Distribution Network;
Voltage Stability
LEMB
dc.subject.armarc.none.fl_str_mv LEMB
description The problem of optimal siting and dimensioning of photovoltaic (PV) generators in medium-voltage distribution networks is addressed in this research from the perspective of combinatorial optimization. The exact mixed-integer programming (MINLP) model is solved using a master–slave (MS) optimization approach. In the master stage, the generalized normal distribution optimization (GNDO) with a discrete–continuous codification is used to represent the locations and sizes of the PV generators. In the slave stage, the generalization of the backward/forward power method, known as the successive approximation power flow method, is adopted. Numerical simulations in the IEEE 33-bus and 69-bus systems demonstrated that the GNDO approach is the most efficient method for solving the exact MINLP model, as it obtained better results than the genetic algorithm, vortex-search algorithm, Newton-metaheuristic optimizer, and exact solution using the General Algebraic Modeling System (GAMS) software with the BONMIN solver. Simulations showed that, on average, the proposed MS optimizer reduced the total annual operative costs by approximately 27% for both test feeders when compared with the reference case. In addition, variations in renewable generation availability showed that from 30% ahead, positive reductions with respect to the reference case were obtained.
publishDate 2022
dc.date.issued.none.fl_str_mv 2022
dc.date.accessioned.none.fl_str_mv 2023-07-25T12:10:42Z
dc.date.available.none.fl_str_mv 2023-07-25T12:10:42Z
dc.date.submitted.none.fl_str_mv 2023
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dc.identifier.citation.spa.fl_str_mv Montoya, O. D., Grisales-Noreña, L. F., & Ramos-Paja, C. A. (2022). Optimal allocation and sizing of PV generation units in distribution networks via the generalized normal distribution optimization approach. Computers, 11(4), 53.
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/12431
dc.identifier.doi.none.fl_str_mv 10.3390/computers11040053
dc.identifier.instname.spa.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.spa.fl_str_mv Repositorio Universidad Tecnológica de Bolívar
identifier_str_mv Montoya, O. D., Grisales-Noreña, L. F., & Ramos-Paja, C. A. (2022). Optimal allocation and sizing of PV generation units in distribution networks via the generalized normal distribution optimization approach. Computers, 11(4), 53.
10.3390/computers11040053
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/12431
dc.language.iso.spa.fl_str_mv eng
language eng
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dc.rights.cc.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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eu_rights_str_mv openAccess
dc.format.extent.none.fl_str_mv 22 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.place.spa.fl_str_mv Cartagena de Indias
dc.source.spa.fl_str_mv Computers
institution Universidad Tecnológica de Bolívar
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spelling Montoya, Oscar Danilo9fa8a75a-58fa-436d-a6e2-d80f718a4ea8Grisales-Noreña, Luis Fernando7c27cda4-5fe4-4686-8f72-b0442c58a5d1Ramos-Paja, Carlos Andres6c8f6752-cad7-4a04-9a85-1d54832135102023-07-25T12:10:42Z2023-07-25T12:10:42Z20222023Montoya, O. D., Grisales-Noreña, L. F., & Ramos-Paja, C. A. (2022). Optimal allocation and sizing of PV generation units in distribution networks via the generalized normal distribution optimization approach. Computers, 11(4), 53.https://hdl.handle.net/20.500.12585/1243110.3390/computers11040053Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe problem of optimal siting and dimensioning of photovoltaic (PV) generators in medium-voltage distribution networks is addressed in this research from the perspective of combinatorial optimization. The exact mixed-integer programming (MINLP) model is solved using a master–slave (MS) optimization approach. In the master stage, the generalized normal distribution optimization (GNDO) with a discrete–continuous codification is used to represent the locations and sizes of the PV generators. In the slave stage, the generalization of the backward/forward power method, known as the successive approximation power flow method, is adopted. Numerical simulations in the IEEE 33-bus and 69-bus systems demonstrated that the GNDO approach is the most efficient method for solving the exact MINLP model, as it obtained better results than the genetic algorithm, vortex-search algorithm, Newton-metaheuristic optimizer, and exact solution using the General Algebraic Modeling System (GAMS) software with the BONMIN solver. Simulations showed that, on average, the proposed MS optimizer reduced the total annual operative costs by approximately 27% for both test feeders when compared with the reference case. In addition, variations in renewable generation availability showed that from 30% ahead, positive reductions with respect to the reference case were obtained.22 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2ComputersOptimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approachinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Placement;Active Distribution Network;Voltage StabilityLEMBCartagena de IndiasMuhammad Ridzuan, M.I., Mohd Fauzi, N.F.F., Roslan, N.N.R., Mohd Saad, N. Urban and rural medium voltage networks reliability assessment (2020) SN Applied Sciences, 2 (2), art. no. 241. 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Cited 64 times. doi: 10.1016/j.ijepes.2018.11.012Lima, M.A., Mendes, L.F.R., Mothé, G.A., Linhares, F.G., de Castro, M.P.P., da Silva, M.G., Sthel, M.S. Renewable energy in reducing greenhouse gas emissions: Reaching the goals of the Paris agreement in Brazil (2020) Environmental Development, 33, art. no. 100504. Cited 89 times. http://www.sciencedirect.com/science/journal/22114645 doi: 10.1016/j.envdev.2020.100504Pimm, A.J., Palczewski, J., Barbour, E.R., Cockerill, T.T. Using electricity storage to reduce greenhouse gas emissions (2021) Applied Energy, Part A 282, art. no. 116199. Cited 22 times. https://www.journals.elsevier.com/applied-energy doi: 10.1016/j.apenergy.2020.116199Rotz, C.A., Asem-Hiablie, S., Place, S., Thoma, G. Environmental footprints of beef cattle production in the United States (Open Access) (2019) Agricultural Systems, 169, pp. 1-13. 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