Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks

This paper presents an efficient master–slave methodology to solve the problem of integrating photovoltaic (PV) generators into DC grids for a planning period of 20 years. The problem is mathematically formulated as Mixed-Integer Nonlinear Programming (MINLP) with the objective of minimizing the tot...

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Autores:
Grisales-Noreña, Luis Fernando
Cortés-Caicedo, Brandon
Alcalá, Gerardo
Montoya, Oscar Danilo
Tipo de recurso:
Fecha de publicación:
2023
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/12282
Acceso en línea:
https://hdl.handle.net/20.500.12585/12282
https://doi.org/10.3390/math11020387
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 Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks
title Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks
spellingShingle Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks
Placement;
Active Distribution Network;
Voltage Stability
LEMB
title_short Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks
title_full Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks
title_fullStr Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks
title_full_unstemmed Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks
title_sort Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks
dc.creator.fl_str_mv Grisales-Noreña, Luis Fernando
Cortés-Caicedo, Brandon
Alcalá, Gerardo
Montoya, Oscar Danilo
dc.contributor.author.none.fl_str_mv Grisales-Noreña, Luis Fernando
Cortés-Caicedo, Brandon
Alcalá, Gerardo
Montoya, Oscar Danilo
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 This paper presents an efficient master–slave methodology to solve the problem of integrating photovoltaic (PV) generators into DC grids for a planning period of 20 years. The problem is mathematically formulated as Mixed-Integer Nonlinear Programming (MINLP) with the objective of minimizing the total annual operating cost. The main stage, consisting of a discrete-continuous version of the Crow search algorithm (DCCSA), is in charge of determining the installation positions of the PV generators and their corresponding power ratings. On the other hand, at the slave level, the successive approximation power flow method is used to determine the objective function value. Numerical results on 33- and 69-bus test systems demonstrate the applicability, efficiency and robustness of the developed approach with respect to different methodologies previously discussed in the scientific literature, such as the vortex search algorithm, the generalized normal distribution optimizer and the particle swarm optimization algorithm. Numerical tests are performed in the MATLAB programming environment using proprietary scripts. © 2023 by the authors.
publishDate 2023
dc.date.accessioned.none.fl_str_mv 2023-07-21T15:45:30Z
dc.date.available.none.fl_str_mv 2023-07-21T15:45:30Z
dc.date.issued.none.fl_str_mv 2023
dc.date.submitted.none.fl_str_mv 2023
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dc.identifier.citation.spa.fl_str_mv Grisales-Noreña, L.F.; Cortés-Caicedo, B.; Alcalá, G.; Montoya, O.D. Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks. Mathematics 2023, 11, 387. https://doi.org/10.3390/math11020387
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/12282
dc.identifier.doi.none.fl_str_mv https://doi.org/10.3390/math11020387
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 Grisales-Noreña, L.F.; Cortés-Caicedo, B.; Alcalá, G.; Montoya, O.D. Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks. Mathematics 2023, 11, 387. https://doi.org/10.3390/math11020387
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/12282
https://doi.org/10.3390/math11020387
dc.language.iso.spa.fl_str_mv eng
language eng
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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 18 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 Mathematics 2023, 11, 387
institution Universidad Tecnológica de Bolívar
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spelling Grisales-Noreña, Luis Fernando7c27cda4-5fe4-4686-8f72-b0442c58a5d1Cortés-Caicedo, Brandon0b676225-338d-48dc-8f2a-694085d9bb42Alcalá, Gerardo04e0a0ab-2e1e-47e9-aa21-c0cb13133579Montoya, Oscar Danilo9fa8a75a-58fa-436d-a6e2-d80f718a4ea82023-07-21T15:45:30Z2023-07-21T15:45:30Z20232023Grisales-Noreña, L.F.; Cortés-Caicedo, B.; Alcalá, G.; Montoya, O.D. Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks. Mathematics 2023, 11, 387. https://doi.org/10.3390/math11020387https://hdl.handle.net/20.500.12585/12282https://doi.org/10.3390/math11020387Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis paper presents an efficient master–slave methodology to solve the problem of integrating photovoltaic (PV) generators into DC grids for a planning period of 20 years. The problem is mathematically formulated as Mixed-Integer Nonlinear Programming (MINLP) with the objective of minimizing the total annual operating cost. The main stage, consisting of a discrete-continuous version of the Crow search algorithm (DCCSA), is in charge of determining the installation positions of the PV generators and their corresponding power ratings. On the other hand, at the slave level, the successive approximation power flow method is used to determine the objective function value. Numerical results on 33- and 69-bus test systems demonstrate the applicability, efficiency and robustness of the developed approach with respect to different methodologies previously discussed in the scientific literature, such as the vortex search algorithm, the generalized normal distribution optimizer and the particle swarm optimization algorithm. Numerical tests are performed in the MATLAB programming environment using proprietary scripts. © 2023 by the authors.18 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_abf2Mathematics 2023, 11, 387Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networksinfo: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 IndiasValencia, A., Hincapie, R.A., Gallego, R.A. Optimal location, selection, and operation of battery energy storage systems and renewable distributed generation in medium–low voltage distribution networks (2021) Journal of Energy Storage, 34, art. no. 102158. 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