Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm

This paper presents a new methodology to simultaneously solve the optimal conductor selection and optimal phase-balancing problems in unbalanced three-phase distribution systems. Both problems were represented by means of a mathematical model known as the Mixed-Integer Nonlinear Programming (MINLP)...

Full description

Autores:
Cortés-Caicedo, Brandon
Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
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:20.500.12585/12417
Acceso en línea:
https://hdl.handle.net/20.500.12585/12417
Palabra clave:
Conductor selection
Mathematical optimization
Phase-balancing
Salp swarm algorithm
Total annual operating costs
Unbalanced three-phase distribution systems
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
id UTB2_15eb16d89370286a99c731e402b824f2
oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/12417
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
dc.title.spa.fl_str_mv Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm
title Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm
spellingShingle Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm
Conductor selection
Mathematical optimization
Phase-balancing
Salp swarm algorithm
Total annual operating costs
Unbalanced three-phase distribution systems
title_short Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm
title_full Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm
title_fullStr Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm
title_full_unstemmed Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm
title_sort Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm
dc.creator.fl_str_mv Cortés-Caicedo, Brandon
Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
dc.contributor.author.none.fl_str_mv Cortés-Caicedo, Brandon
Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
dc.subject.keywords.spa.fl_str_mv Conductor selection
Mathematical optimization
Phase-balancing
Salp swarm algorithm
Total annual operating costs
Unbalanced three-phase distribution systems
topic Conductor selection
Mathematical optimization
Phase-balancing
Salp swarm algorithm
Total annual operating costs
Unbalanced three-phase distribution systems
description This paper presents a new methodology to simultaneously solve the optimal conductor selection and optimal phase-balancing problems in unbalanced three-phase distribution systems. Both problems were represented by means of a mathematical model known as the Mixed-Integer Nonlinear Programming (MINLP) model, and the objective function was the minimization of the total annual operating costs. The latter included the costs associated with energy losses, investment in conductors per network segment, and phase reconfiguration at each node in the system. To solve the problem addressed in this study, a master–slave methodology was implemented. The master stage employs a discrete version of the Salp Swarm Algorithm (SSA) to determine the set of conductors to be installed in each line, as well as the set of connections per phase at each of the nodes that compose the system. Afterward, the slave stage uses the three-phase version of the backward/forward sweep power flow method to determine the value of the fitness function of each individual provided by the master stage. Compared to those of the Hurricane-based Optimization Algorithm (HOA) and the Sine Cosine Algorithm (SCA), the numerical results obtained by the proposed solution methodology in the IEEE 8- and 25-node test systems demonstrate its applicability and effectiveness. All the numerical validations were performed in MATLAB.
publishDate 2022
dc.date.issued.none.fl_str_mv 2022-09-14
dc.date.accessioned.none.fl_str_mv 2023-07-24T20:48:44Z
dc.date.available.none.fl_str_mv 2023-07-24T20:48:44Z
dc.date.submitted.none.fl_str_mv 2023-07
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.hasversion.spa.fl_str_mv info:eu-repo/semantics/draft
dc.type.spa.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
status_str draft
dc.identifier.citation.spa.fl_str_mv Cortés-Caicedo, B.; Grisales-Noreña, L.F.; Montoya, O.D. Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm. Mathematics 2022, 10, 3327. https://doi.org/10.3390/math10183327
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/12417
dc.identifier.doi.none.fl_str_mv 10.3390/math10183327
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 Cortés-Caicedo, B.; Grisales-Noreña, L.F.; Montoya, O.D. Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm. Mathematics 2022, 10, 3327. https://doi.org/10.3390/math10183327
10.3390/math10183327
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/12417
dc.language.iso.spa.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.cc.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.extent.none.fl_str_mv 34 páginas
dc.format.medium.none.fl_str_mv Pdf
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 - Vol. 10 No. 18 (2022)
institution Universidad Tecnológica de Bolívar
bitstream.url.fl_str_mv https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/1/mathematics-10-03327.pdf
https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/2/license_rdf
https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/3/license.txt
https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/4/mathematics-10-03327.pdf.txt
https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/5/mathematics-10-03327.pdf.jpg
bitstream.checksum.fl_str_mv 53c51dcc06e196b486837eefaae9797f
4460e5956bc1d1639be9ae6146a50347
e20ad307a1c5f3f25af9304a7a7c86b6
b6740ea3be52a2eca7b8554f6ec1b102
82aa9d46311626095a28de3528bc33b0
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Institucional UTB
repository.mail.fl_str_mv repositorioutb@utb.edu.co
_version_ 1814021790004936704
spelling Cortés-Caicedo, Brandon0b676225-338d-48dc-8f2a-694085d9bb42Grisales-Noreña, Luis Fernando7c27cda4-5fe4-4686-8f72-b0442c58a5d1Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d44802023-07-24T20:48:44Z2023-07-24T20:48:44Z2022-09-142023-07Cortés-Caicedo, B.; Grisales-Noreña, L.F.; Montoya, O.D. Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithm. Mathematics 2022, 10, 3327. https://doi.org/10.3390/math10183327https://hdl.handle.net/20.500.12585/1241710.3390/math10183327Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis paper presents a new methodology to simultaneously solve the optimal conductor selection and optimal phase-balancing problems in unbalanced three-phase distribution systems. Both problems were represented by means of a mathematical model known as the Mixed-Integer Nonlinear Programming (MINLP) model, and the objective function was the minimization of the total annual operating costs. The latter included the costs associated with energy losses, investment in conductors per network segment, and phase reconfiguration at each node in the system. To solve the problem addressed in this study, a master–slave methodology was implemented. The master stage employs a discrete version of the Salp Swarm Algorithm (SSA) to determine the set of conductors to be installed in each line, as well as the set of connections per phase at each of the nodes that compose the system. Afterward, the slave stage uses the three-phase version of the backward/forward sweep power flow method to determine the value of the fitness function of each individual provided by the master stage. Compared to those of the Hurricane-based Optimization Algorithm (HOA) and the Sine Cosine Algorithm (SCA), the numerical results obtained by the proposed solution methodology in the IEEE 8- and 25-node test systems demonstrate its applicability and effectiveness. All the numerical validations were performed in MATLAB.34 páginasPdfapplication/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 - Vol. 10 No. 18 (2022)Optimal Selection of Conductor Sizes in Three-Phase Asymmetric Distribution Networks Considering Optimal Phase-Balancing: An Application of the Salp Swarm Algorithminfo: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_2df8fbb1Conductor selectionMathematical optimizationPhase-balancingSalp swarm algorithmTotal annual operating costsUnbalanced three-phase distribution systemsCartagena de IndiasLöfquist, L. Is there a universal human right to electricity? (2020) International Journal of Human Rights, 24 (6), pp. 711-723. Cited 21 times. http://www.tandfonline.com/toc/fjhr20/current doi: 10.1080/13642987.2019.1671355Sarkodie, S.A., Adams, S. Electricity access, human development index, governance and income inequality in Sub-Saharan Africa (2020) Energy Reports, 6, pp. 455-466. Cited 91 times. http://www.journals.elsevier.com/energy-reports/ doi: 10.1016/j.egyr.2020.02.009Ghiasi, M. Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources (2019) Energy, 169, pp. 496-507. Cited 108 times. www.elsevier.com/inca/publications/store/4/8/3/ doi: 10.1016/j.energy.2018.12.083Shen, T., Li, Y., Xiang, J. A graph-based power flow method for balanced distribution systems (2018) Energies, 11 (3), art. no. 511. Cited 58 times. http://www.mdpi.com/journal/energies/ doi: 10.3390/en11030511Ghiasi, M., Niknam, T., Dehghani, M., Siano, P., Alhelou, H.H., Al-Hinai, A. Optimal multi-operation energy management in smart microgrids in the presence of ress based on multi-objective improved de algorithm: Cost-emission based optimization (2021) Applied Sciences (Switzerland), 11 (8), art. no. 3661. Cited 36 times. https://www.mdpi.com/2076-3417/11/8/3661/pdf doi: 10.3390/app11083661Ouali, S., Cherkaoui, A. An Improved Backward/Forward Sweep Power Flow Method Based on a New Network Information Organization for Radial Distribution Systems (2020) Journal of Electrical and Computer Engineering, 2020, art. no. 5643410. Cited 31 times. http://www.hindawi.com/journals/jece/ doi: 10.1155/2020/5643410Aboshady, F.M., Thomas, D.W.P., Sumner, M. A Wideband Single End Fault Location Scheme for Active Untransposed Distribution Systems (2020) IEEE Transactions on Smart Grid, 11 (3), art. no. 8871156, pp. 2115-2124. Cited 11 times. https://ieeexplore.ieee.org/servlet/opac?punumber=5165411 doi: 10.1109/TSG.2019.2947870Arias, J., Calle, M., Turizo, D., Guerrero, J., Candelo-Becerra, J.E. Historical load balance in distribution systems using the branch and bound algorithm (2019) Energies, 12 (7), art. no. 1219. Cited 16 times. https://www.mdpi.com/1996-1073/12/7 doi: 10.3390/en12071219Garcés-Ruiz, A. Power Flow in Unbalanced Three-Phase Power Distribution Networks Using Matlab: Theory, analysis, and quasi-dynamic simulation (2022) Ingeniería, 27, p. e19252. Cited 2 times.Cortés-Caicedo, B., Avellaneda-Gómez, L.S., Montoya, O.D., Alvarado-Barrios, L., Chamorro, H.R. Application of the vortex search algorithm to the phase-balancing problem in distribution systems (2021) Energies, 14 (5), art. no. 1282. Cited 22 times. https://www.mdpi.com/1996-1073/14/5/1282/pdf doi: 10.3390/en14051282Cabrera, J.B., Veiga, M.F., Morales, D.X., Medina, R. Reducing power losses in smart grids with cooperative game theory (2019) Advanced Communication and Control Methods for Future Smartgrids, p. 49. Cited 6 times. Intechopen, London, UKTrentini, C., de Oliveira Guedes, W., de Oliveira, L.W., Dias, B.H., Ferreira, V.H. Maintenance Planning of Electric Distribution Systems—A Review (2021) Journal of Control, Automation and Electrical Systems, 32 (1), pp. 186-202. Cited 8 times. http://rd.springer.com/journal/40313 doi: 10.1007/s40313-020-00663-zMartínez-Gil, J.F., Moyano-García, N.A., Montoya, O.D., Alarcon-Villamil, J.A. Optimal selection of conductors in three-phase distribution networks using a discrete version of the vortex search algorithm (2021) Computation, 9 (7), art. no. 80. Cited 8 times. www.mdpi.com/journal/computation doi: 10.3390/computation9070080Wang, Z., Liu, H., Yu, D.C., Wang, X., Song, H. A practical approach to the conductor size selection in planning radial distribution systems (2000) IEEE Transactions on Power Delivery, 15 (1), pp. 350-354. Cited 51 times. doi: 10.1109/61.847272Zhu, J. Phase balancing using simulated annealing (1999) IEEE Transactions on Power Systems, 14 (4), pp. 1508-1513. Cited 94 times. doi: 10.1109/59.801943Han, X., Wang, H., Liang, D. Master-slave game optimization method of smart energy systems considering the uncertainty of renewable energy (Open Access) (2021) International Journal of Energy Research, 45 (1), pp. 642-660. Cited 3 times. http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-114X doi: 10.1002/er.5798Montoya, O.D., Grajales, A., Hincapié, R.A. (2018) Optimal Selection of Conductors in Distribution Systems Using Tabu Search Algorithm [Selección óptima de Conductores en Sistemas de Distribución Empleando el Algoritmo Búsqueda Tabú] Available online https://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-33052018000200283&lng=en&nrm=isoIsmael, S.M., Abdel Aleem, S.H.E., Abdelaziz, A.Y. Optimal conductor selection in radial distribution systems using whale optimization algorithm (2019) Journal of Engineering Science and Technology, 14 (1), pp. 87-107. Cited 7 times. http://jestec.taylors.edu.my/Vol%2014%20issue%201%20February%202019/14_1_07.pdfKumari, M., Singh, V.R., Ranjan, R. Optimal selection of conductor in RDS considering weather condition (2018) 2018 International Conference on Computing, Power and Communication Technologies, GUCON 2018, art. no. 8675051, pp. 647-651. Cited 5 times. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8671767 ISBN: 978-153864491-1 doi: 10.1109/GUCON.2018.8675051Mohanty, S., Kasturi, K., Nayak, M.R. Application of ER-WCA to determine conductor size for performance improvement in distribution system (2021) Proceedings of the 2021 1st International Conference on Advances in Electrical, Computing, Communications and Sustainable Technologies, ICAECT 2021, art. no. 9392495. Cited 2 times. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9392383 ISBN: 978-172815790-0 doi: 10.1109/ICAECT49130.2021.9392495Montoya, O.D., Serra, F.M., De Angelo, C.H., Chamorro, H.R., Alvarado-Barrios, L. Heuristic methodology for planning ac rural medium-voltage distribution grids (2021) Energies, 14 (16), art. no. 5141. Cited 5 times. https://www.mdpi.com/1996-1073/14/16/5141/pdf doi: 10.3390/en14165141Garces, A., Gil-González, W., Montoya, O.D., Chamorro, H.R., Alvarado-Barrios, L. A Mixed-Integer Quadratic Formulation of the Phase-Balancing Problem in Residential Microgrids (2021) Appl. Sci, 11. Cited 10 times.Cortés-Caicedo, B., Avellaneda-Gómez, L.S., Montoya, O.D., Alvarado-Barrios, L., Álvarez-Arroyo, C. An improved crow search algorithm applied to the phase swapping problem in asymmetric distribution systems (2021) Symmetry, 13 (8), art. no. 1329. Cited 7 times. https://www.mdpi.com/2073-8994/13/8/1329/pdf doi: 10.3390/sym13081329Cruz-Reyes, J.L., Salcedo-Marcelo, S.S., Montoya, O.D. Application of the Hurricane-Based Optimization Algorithm to the Phase-Balancing Problem in Three-Phase Asymmetric Networks (2022) Computers, 11 (3), art. no. 43. Cited 3 times. https://www.mdpi.com/2073-431X/11/3/43/pdf doi: 10.3390/computers11030043Montoya, O.D., Molina-Cabrera, A., Grisales-Noreña, L.F., Hincapié, R.A., Granada, A. Improved genetic algorithm for phase-balancing in three-phase distribution networks: A master-slave optimization approach (2021) Computation, 9 (6), art. no. 67. Cited 11 times. https://www.mdpi.com/2079-3197/9/6/67/pdf doi: 10.3390/computation9060067Montoya, O.D., Alarcon-Villamil, J.A., Hernández, J.C. Operating cost reduction in distribution networks based on the optimal phase-swapping including the costs of the working groups and energy losses (2021) Energies, 14 (15), art. no. 4535. Cited 10 times. https://www.mdpi.com/1996-1073/14/15/4535/pdf doi: 10.3390/en14154535Mandal, S., Pahwa, A. Optimal selection of conductors for distribution feeders (Open Access) (2002) IEEE Transactions on Power Systems, 17 (1), pp. 192-197. Cited 45 times. doi: 10.1109/59.982213Joshi, D., Burada, S., Mistry, K.D. Distribution system planning with optimal conductor selection (2017) 2017 Recent Developments in Control, Automation and Power Engineering, RDCAPE 2017, pp. 263-268. Cited 4 times. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8356462 ISBN: 978-150903978-4 doi: 10.1109/RDCAPE.2017.8358279Rao, R.S., Satish, K., Narasimham, S.V.L. Optimal conductor size selection in distribution systems using the harmony search algorithm with a differential operator (2011) Electric Power Components and Systems, 40 (1), pp. 41-56. Cited 31 times. doi: 10.1080/15325008.2011.621922López, L., Hincapié, R.A., Gallego, R.A. Multi-objective Distribution System Planning using an NSGA II Evolutionary Algorithm [Planeamiento multiobjetivo de sistemas de distribución usando un algoritmo evolutivo NSGA-II] (2011) Rev. EIA, 8, pp. 141-151. Cited 3 times. Available online https://revistas.eia.edu.co/index.php/reveia/article/view/252Khalil, T.M., Gorpinich, A.V. Optimal conductor selection and capacitor placement for loss reduction of radial distribution systems by selective particle swarm optimization (2012) Proceedings - ICCES 2012: 2012 International Conference on Computer Engineering and Systems, art. no. 6408516, pp. 215-220. Cited 12 times. ISBN: 978-146732961-3 doi: 10.1109/ICCES.2012.6408516Legha, M.M., Javaheri, H., Legha, M.M. Optimal Conductor Selection in Radial Distribution Systems for Productivity Improvement Using Genetic Algorithm (2013) Iraqi J. Electr. Electron. Eng, 9, pp. 29-35. Cited 13 times.Legha, M.M., Noormohamadi, H., Barkhori, A. Optimal conductor selection in radial distribution using bacterial foraging algorithm and comparison with ICA method (2015) WALIA J, 31, pp. 37-43. Cited 8 times.Ismael, S.M., Aleem, S.H.E.A., Abdelaziz, A.Y. Optimal selection of conductors in Egyptian radial distribution systems using sine-cosine optimization algorithm (Open Access) (2018) 2017 19th International Middle-East Power Systems Conference, MEPCON 2017 - Proceedings, 2018-February, pp. 103-107. Cited 24 times. ISBN: 978-153860990-3 doi: 10.1109/MEPCON.2017.8301170Abdelaziz, A.Y., Fathy, A. A novel approach based on crow search algorithm for optimal selection of conductor size in radial distribution networks (Open Access) (2017) Engineering Science and Technology, an International Journal, 20 (2), pp. 391-402. Cited 95 times. www.journals.elsevier.com/engineering-science-and-technology-an-international-journal/ doi: 10.1016/j.jestch.2017.02.004Montoya, O.D., Gil-González, W., Grisales-Noreña, L.F. On the mathematical modeling for optimal selecting of calibers of conductors in DC radial distribution networks: An MINLP approach (Open Access) (2021) Electric Power Systems Research, 194, art. no. 107072. Cited 10 times. https://www.journals.elsevier.com/electric-power-systems-research doi: 10.1016/j.epsr.2021.107072Chen, Tsai-Hsiang, Cherng, Jeng-Tyan Optimal phase arrangement of distribution transformers connected to a primary feeder for system unbalance improvement and loss reduction using a genetic algorithm (1999) IEEE Power Industry Computer Applications Conference, pp. 145-151. Cited 12 times. ISBN: 0780354796Gandomkar, M. Phase balancing using genetic algorithm (2004) 39th International Universities Power Engineering Conference, UPEC 2004 - Conference Proceedings, 1, pp. 377-379. Cited 15 times. ISBN: 1860433650Granada Echeverri, M., Gallego Rendón, R.A., López Lezama, J.M. Optimal phase balancing planning for loss reduction in distribution systems using a specialized genetic algorithm (2012) Ing. Cienc, 8, pp. 121-140. Cited 27 times.Rios, M.A., Castano, J.C., Garces, A., Molina-Cabrera, A. Phase balancing in power distribution systems: A heuristic approach based on group-theory (Open Access) (2019) 2019 IEEE Milan PowerTech, PowerTech 2019, art. no. 8810723. Cited 9 times. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8792346 ISBN: 978-153864722-6 doi: 10.1109/PTC.2019.8810723Garcés-Ruiz, A., Granada-Echeverri, M., Gallego, R.A. Balance de fases usando colonia de hormigas (2005) Ing. Compet, 7, pp. 43-52. Cited 3 times.Tuppadung, Y., Kurutach, W. The modified particle swarm optimization for phase balancing (2006) IEEE Region 10 Annual International Conference, Proceedings/TENCON, art. no. 4142320. Cited 8 times. http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000751 ISBN: 1424405491; 978-142440549-7 doi: 10.1109/TENCON.2006.344014Toma, N., Ivanov, O., Neagu, B., Gavrila, M. A PSO Algorithm for Phase Load Balancing in Low Voltage Distribution Networks (2018) EPE 2018 - Proceedings of the 2018 10th International Conference and Expositions on Electrical And Power Engineering, art. no. 8559805, pp. 857-862. Cited 19 times. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8540800 ISBN: 978-153865062-2 doi: 10.1109/ICEPE.2018.8559805Huang, M.-Y., Chen, C.-S., Lin, C.-H., Kang, M.-S., Chuang, H.-J., Huang, C.-W. Three-phase balancing of distribution feeders using immune algorithm (2008) IET Generation, Transmission and Distribution, 2 (3), pp. 383-392. Cited 53 times. doi: 10.1049/iet-gtd:20070206Sathiskumar, M., Nirmal Kumar, A., Lakshminarasimman, L., Thiruvenkadam, S. A self adaptive hybrid differential evolution algorithm for phase balancing of unbalanced distribution system (Open Access) (2012) International Journal of Electrical Power and Energy Systems, 42 (1), pp. 91-97. Cited 34 times. doi: 10.1016/j.ijepes.2012.03.029Hooshmand, R., Soltani, S.H. Simultaneous optimization of phase balancing and reconfiguration in distribution networks using BF-NM algorithm (Open Access) (2012) International Journal of Electrical Power and Energy Systems, 41 (1), pp. 76-86. Cited 29 times. doi: 10.1016/j.ijepes.2012.03.010Montoya, O.D., Arias-Londoño, A., Grisales-Noreña, L.F., Barrios, J.Á., Chamorro, H.R. Optimal demand reconfiguration in three-phase distribution grids using an mi-convex model (2021) Symmetry, 13 (7). Cited 9 times. https://www.mdpi.com/2073-8994/13/7/1124/pdf doi: 10.3390/sym13071124Montoya, O.D., Grisales-Noreña, L.F., Rivas-Trujillo, E. Approximated mixed-integer convex model for phase balancing in three-phase electric networks (Open Access) (2021) Computers, 10 (9), art. no. 109. Cited 5 times. https://www.mdpi.com/2073-431X/10/9/109/pdf doi: 10.3390/computers10090109Hu, R., Li, Q., Qiu, F. Ensemble Learning Based Convex Approximation of Three-Phase Power Flow (Open Access) (2021) IEEE Transactions on Power Systems, 36 (5), art. no. 9340012, pp. 4042-4051. Cited 8 times. https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=59 doi: 10.1109/TPWRS.2021.3055481Carreno, I.L., Scaglione, A., Saha, S.S., Arnold, D., Ngo, S.-T., Roberts, C. Log(v) 3LPF: A Linear Power Flow Formulation for Unbalanced Three-Phase Distribution Systems (Open Access) (2023) IEEE Transactions on Power Systems, 38 (1), pp. 100-113. https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=59 doi: 10.1109/TPWRS.2022.3166725Lavorato, M., Franco, J.F., Rider, M.J., Romero, R. Imposing radiality constraints in distribution system optimization problems (Open Access) (2012) IEEE Transactions on Power Systems, 27 (1), art. no. 5982115, pp. 172-180. Cited 411 times. doi: 10.1109/TPWRS.2011.2161349Devikanniga, D., Vetrivel, K., Badrinath, N. Review of meta-heuristic optimization based artificial neural networks and its applications (2019) Journal of Physics: Conference Series, 1362 (1), art. no. 012074. Cited 32 times. http://iopscience.iop.org/journal/1742-6596 doi: 10.1088/1742-6596/1362/1/012074Mirjalili, S., Gandomi, A.H., Mirjalili, S.Z., Saremi, S., Faris, H., Mirjalili, S.M. Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems (2017) Advances in Engineering Software, 114, pp. 163-191. Cited 2966 times. http://www.journals.elsevier.com/advances-in-engineering-software/ doi: 10.1016/j.advengsoft.2017.07.002Salimon, S.A., Aderinko, H.A., Fajuke, F., Suuti, K.A. Load flow analysis of nigerian radial distribution network using backward/forward sweep technique (2019) J. VLSI Des. Adv, 2, pp. 1-11. Cited 11 times.Jabari, F., Sohrabi, F., Pourghasem, P., Mohammadi-Ivatloo, B. Backward-Forward Sweep Based Power Flow Algorithm in Distribution Systems (Open Access) (2020) Studies in Systems, Decision and Control, 262, pp. 365-382. Cited 9 times. www.springer.com/series/13304 doi: 10.1007/978-3-030-34050-6_14Hegazy, A.E., Makhlouf, M.A., El-Tawel, G.S. Improved salp swarm algorithm for feature selection (Open Access) (2020) Journal of King Saud University - Computer and Information Sciences, 32 (3), pp. 335-344. Cited 143 times. www.journals.elsevier.com/journal-of-king-saud-university-computer-and-information-sciences/ doi: 10.1016/j.jksuci.2018.06.003Abualigah, L., Shehab, M., Alshinwan, M., Alabool, H. Salp swarm algorithm: a comprehensive survey (2020) Neural Computing and Applications, 32 (15), pp. 11195-11215. Cited 145 times. http://link.springer.com/journal/521 doi: 10.1007/s00521-019-04629-4Ibrahim, R.A., Ewees, A.A., Oliva, D., Abd Elaziz, M., Lu, S. Improved salp swarm algorithm based on particle swarm optimization for feature selection (2019) Journal of Ambient Intelligence and Humanized Computing, 10 (8), pp. 3155-3169. Cited 223 times. http://www.springer.com/engineering/journal/12652 doi: 10.1007/s12652-018-1031-9Zhang, H., Liu, T., Ye, X., Heidari, A.A., Liang, G., Chen, H., Pan, Z. Differential evolution-assisted salp swarm algorithm with chaotic structure for real-world problems (2023) Engineering with Computers, 39 (3), pp. 1735-1769. Cited 15 times. https://www.springer.com/journal/366 doi: 10.1007/s00366-021-01545-xAdetunji, K.E., Hofsajer, I.W., Abu-Mahfouz, A.M., Cheng, L. A Review of Metaheuristic Techniques for Optimal Integration of Electrical Units in Distribution Networks (2021) IEEE Access, 9, art. no. 9311503, pp. 5046-5068. Cited 23 times. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639 doi: 10.1109/ACCESS.2020.3048438Faris, H., Mirjalili, S., Aljarah, I., Mafarja, M., Heidari, A.A. Salp swarm algorithm: Theory, literature review, and application in extreme learning machines (2020) Studies in Computational Intelligence, 811, pp. 185-199. Cited 103 times. http://www.springer.com/series/7092 doi: 10.1007/978-3-030-12127-3_11Castelli, M., Manzoni, L., Mariot, L., Nobile, M.S., Tangherloni, A. Salp Swarm Optimization: A critical review (Open Access) (2022) Expert Systems with Applications, 189, art. no. 116029. Cited 19 times. https://www.journals.elsevier.com/expert-systems-with-applications doi: 10.1016/j.eswa.2021.116029Montano, J., Mejia, A.F.T., Muñoz, A.A.R., Andrade, F., Garzon Rivera, O.D., Palomeque, J.M. Salp swarm optimization algorithm for estimating the parameters of photovoltaic panels based on the three-diode model (Open Access) (2021) Electronics (Switzerland), 10 (24), art. no. 3123. Cited 7 times. https://www.mdpi.com/2079-9292/10/24/3123/pdf doi: 10.3390/electronics10243123Keihan Asl, D., Seifi, A.R., Rastegar, M., Mohammadi, M. Optimal energy flow in integrated energy distribution systems considering unbalanced operation of power distribution systems (Open Access) (2020) International Journal of Electrical Power and Energy Systems, 121, art. no. 106132. Cited 30 times. https://www.journals.elsevier.com/international-journal-of-electrical-power-and-energy-systems doi: 10.1016/j.ijepes.2020.106132Pandey, A., Jereminov, M., Wagner, M.R., Bromberg, D.M., Hug, G., Pileggi, L. Robust Power Flow and Three-Phase Power Flow Analyses (2019) IEEE Transactions on Power Systems, 34 (1), art. no. 8424869, pp. 616-626. Cited 55 times. https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=59 doi: 10.1109/TPWRS.2018.2863042Kersting, W.H. Distribution system modeling and analysis: Fourth edition (Open Access) (2017) Distribution System Modeling and Analysis: Fourth Edition, pp. 1-526. Cited 822 times. http://www.tandfebooks.com/doi/book/10.1201/9781315120782 ISBN: 978-149877214-3; 978-149877213-6 doi: 10.1201/9781315120782Souza, B., Araujo, L., Penido, D. An extended kron method for power system applications (Open Access) (2020) IEEE Latin America Transactions, 18 (8), art. no. 9111684, pp. 1470-1477. Cited 2 times. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9907 doi: 10.1109/TLA.2020.9111684Kerting, W.H. Radial distribution test feeders IEEE distribution planning working group report (Open Access) (1991) IEEE Transactions on Power Systems, 6 (3), pp. 975-985. Cited 919 times. doi: 10.1109/59.119237Mwakabuta, N., Sekar, A. Comparative study of the IEEE 34 node test feeder under practical simplifications (Open Access) (2007) 2007 39th North American Power Symposium, NAPS, art. no. 4402354, pp. 484-491. Cited 60 times. ISBN: 978-142441726-1 doi: 10.1109/NAPS.2007.4402354Montoya, O.D., Giraldo, J.S., Grisales-Noreña, L.F., Chamorro, H.R., Alvarado-Barrios, L. Accurate and efficient derivative-free three-phase power flow method for unbalanced distribution networks (Open Access) (2021) Computation, 9 (6), art. no. 61. Cited 18 times. https://www.mdpi.com/2079-3197/9/6/61/pdf doi: 10.3390/computation9060061Gil-González, W., Montoya, O.D., Grisales-Noreña, L.F., Perea-Moreno, A.-J., Hernandez-Escobedo, Q. Optimal placement and sizing ofwind generators in ac grids considering reactive power capability and wind speed curves (Open Access) (2020) Sustainability (Switzerland), 12 (7), art. no. 2983. Cited 20 times. https://res.mdpi.com/d_attachment/sustainability/sustainability-12-02983/article_deploy/sustainability-12-02983-v2.pdf doi: 10.3390/su12072983Montoya, O.D., Gil-González, W., Giral, D.A. On the matricial formulation of iterative sweep power flow for radial and meshed distribution networks with guarantee of convergence (Open Access) (2020) Applied Sciences (Switzerland), 10 (17), art. no. 5802. Cited 14 times. https://res.mdpi.com/d_attachment/applsci/applsci-10-05802/article_deploy/applsci-10-05802.pdf doi: 10.3390/app10175802Sahoo, R.R., Ray, M. PSO based test case generation for critical path using improved combined fitness function (Open Access) (2020) Journal of King Saud University - Computer and Information Sciences, 32 (4), pp. 479-490. Cited 29 times. www.journals.elsevier.com/journal-of-king-saud-university-computer-and-information-sciences/ doi: 10.1016/j.jksuci.2019.09.010Zhang, X., Beram, S.M., Haq, M.A., Wawale, S.G., Buttar, A.M. Research on algorithms for control design of human–machine interface system using ML (Open Access) (2022) International Journal of System Assurance Engineering and Management, 13, pp. 462-469. Cited 4 times. http://www.springer.com/engineering/production+eng/journal/13198 doi: 10.1007/s13198-021-01469-1Harman, M., Jia, Y., Zhang, Y. Achievements, open problems and challenges for search based software testing (Open Access) (2015) 2015 IEEE 8th International Conference on Software Testing, Verification and Validation, ICST 2015 - Proceedings, art. no. 7102580. Cited 149 times. ISBN: 978-147997125-1 doi: 10.1109/ICST.2015.7102580Enel Codensa, S.A. LA202 Circuito Primario Sencillo Construcción Tangencial, Bogotá, Colombia Available online https://likinormas.micodensa.com/Norma/lineas_aereas_urbanas_distribucion/lineas_aereas_11_4_13_2_kv/la202_circuito_primario_sencillo_construccion_tangencialEnel Codensa, S.A. LA006 Distancias de Construcción Para Circuitos de 13,2 -11,4 kv Y B.T., Bogotá, Colombia Available online https://likinormas.micodensa.com/Norma/lineas_aereas_urbanas_distribucion/la006_distancias_construccion_circuitos_13_2_11Gil-González, W., Montoya, O.D., Holguín, E., Garces, A., Grisales-Noreña, L.F. Economic dispatch of energy storage systems in dc microgrids employing a semidefinite programming model (Open Access) (2019) Journal of Energy Storage, 21, pp. 1-8. Cited 90 times. http://www.journals.elsevier.com/journal-of-energy-storage/ doi: 10.1016/j.est.2018.10.025Montoya, O.D., Gil-González, W., Grisales-Norena, L., Orozco-Henao, C., Serra, F. Economic sispatch of BESS and renewable generators in DC microgrids using voltage-dependent load models (Open Access) (2019) Energies, 12 (23), art. no. 4494. Cited 32 times. https://www.mdpi.com/1996-1073/12/23 doi: 10.3390/en12234494(1995) Resolución 025 de 1995, Bogotá, Colombia Available online http://apolo.creg.gov.co/Publicac.nsf/Indice01/Resoluci%C3%B3n-1995-CRG95025http://purl.org/coar/resource_type/c_2df8fbb1ORIGINALmathematics-10-03327.pdfmathematics-10-03327.pdfapplication/pdf496213https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/1/mathematics-10-03327.pdf53c51dcc06e196b486837eefaae9797fMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXTmathematics-10-03327.pdf.txtmathematics-10-03327.pdf.txtExtracted texttext/plain114777https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/4/mathematics-10-03327.pdf.txtb6740ea3be52a2eca7b8554f6ec1b102MD54THUMBNAILmathematics-10-03327.pdf.jpgmathematics-10-03327.pdf.jpgGenerated Thumbnailimage/jpeg8369https://repositorio.utb.edu.co/bitstream/20.500.12585/12417/5/mathematics-10-03327.pdf.jpg82aa9d46311626095a28de3528bc33b0MD5520.500.12585/12417oai:repositorio.utb.edu.co:20.500.12585/124172023-07-25 00:17:45.337Repositorio Institucional UTBrepositorioutb@utb.edu.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

Publicaciones similares