Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach
In this study, we analyzed the optimal location and sizing of distributed generators (DGs) in radial distributed networks using a hybrid master-slave metaheuristic technique. The master stage corresponds to the selection of suitable points for the locations of the DGs, whereas the slave stage is the...
- Autores:
-
Montoya, Oscar Danilo
Gil-González, Walter
Orozco-Henao, César
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9540
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9540
https://www.sciencedirect.com/science/article/pii/S2215098619312054
- Palabra clave:
- Combinatorial optimization
Distributed generators
Genetic algorithm
Distribution networks
Power losses reduction
Vortex search optimization algorith
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach |
| title |
Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach |
| spellingShingle |
Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach Combinatorial optimization Distributed generators Genetic algorithm Distribution networks Power losses reduction Vortex search optimization algorith |
| title_short |
Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach |
| title_full |
Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach |
| title_fullStr |
Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach |
| title_full_unstemmed |
Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach |
| title_sort |
Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach |
| dc.creator.fl_str_mv |
Montoya, Oscar Danilo Gil-González, Walter Orozco-Henao, César |
| dc.contributor.author.none.fl_str_mv |
Montoya, Oscar Danilo Gil-González, Walter Orozco-Henao, César |
| dc.subject.keywords.spa.fl_str_mv |
Combinatorial optimization Distributed generators Genetic algorithm Distribution networks Power losses reduction Vortex search optimization algorith |
| topic |
Combinatorial optimization Distributed generators Genetic algorithm Distribution networks Power losses reduction Vortex search optimization algorith |
| description |
In this study, we analyzed the optimal location and sizing of distributed generators (DGs) in radial distributed networks using a hybrid master-slave metaheuristic technique. The master stage corresponds to the selection of suitable points for the locations of the DGs, whereas the slave stage is the optimal dimensioning problem. The Chu-Beasley genetic algorithm (CBGA) is employed to solve the master stage, and the optimal power flow (OPF) method via the vortex search algorithm (VSA) is employed to solve the slave stage. The OPF solution from the VSA technique uses a successive approximation power flow to determine the voltage profiles and power losses by guaranteeing the energy balance in all the nodes of the network. The conventional and widely used 33- and 69-node test feeders are used to validate the hybrid CBGA-VSA for analyzing the optimal location and sizing of the DGs in the distribution networks using MATLAB software. The numerical results demonstrate the efficiency of the proposed optimization method in terms of power loss reduction as compared with the results available in the literature. An additional 24-h dimensioning analysis is included for demonstrating the efficiency and applicability of the proposed methodology for daily operations with renewable generation. |
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2020 |
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2020-11-04T21:21:09Z |
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2020-11-04T21:21:09Z |
| dc.date.issued.none.fl_str_mv |
2020-08-03 |
| dc.date.submitted.none.fl_str_mv |
2020-11-03 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_6501 |
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publishedVersion |
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O. D. Montoya, W. Gil-González and C. Orozco-Henao, Vortex search and Chu-Beasley genetic algorithms for optimal location andsizing of distributed generators in distribution networks: A novel hybrid approach, Engineering Science and Technology, an International Journal,https://doi.org/10.1016/j.jestch.2020.08.002 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/9540 |
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https://www.sciencedirect.com/science/article/pii/S2215098619312054 |
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10.1016/j.jestch.2020.08.002 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
O. D. Montoya, W. Gil-González and C. Orozco-Henao, Vortex search and Chu-Beasley genetic algorithms for optimal location andsizing of distributed generators in distribution networks: A novel hybrid approach, Engineering Science and Technology, an International Journal,https://doi.org/10.1016/j.jestch.2020.08.002 10.1016/j.jestch.2020.08.002 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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https://hdl.handle.net/20.500.12585/9540 https://www.sciencedirect.com/science/article/pii/S2215098619312054 |
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eng |
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eng |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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openAccess |
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13 páginas |
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Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Gil-González, Walterce1f5078-74c6-4b5c-b56a-784f85e52a08Orozco-Henao, Césarcfb1cfea-5d74-4fc8-8a2e-223843a0e4aa2020-11-04T21:21:09Z2020-11-04T21:21:09Z2020-08-032020-11-03O. D. Montoya, W. Gil-González and C. Orozco-Henao, Vortex search and Chu-Beasley genetic algorithms for optimal location andsizing of distributed generators in distribution networks: A novel hybrid approach, Engineering Science and Technology, an International Journal,https://doi.org/10.1016/j.jestch.2020.08.002https://hdl.handle.net/20.500.12585/9540https://www.sciencedirect.com/science/article/pii/S221509861931205410.1016/j.jestch.2020.08.002Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarIn this study, we analyzed the optimal location and sizing of distributed generators (DGs) in radial distributed networks using a hybrid master-slave metaheuristic technique. The master stage corresponds to the selection of suitable points for the locations of the DGs, whereas the slave stage is the optimal dimensioning problem. The Chu-Beasley genetic algorithm (CBGA) is employed to solve the master stage, and the optimal power flow (OPF) method via the vortex search algorithm (VSA) is employed to solve the slave stage. The OPF solution from the VSA technique uses a successive approximation power flow to determine the voltage profiles and power losses by guaranteeing the energy balance in all the nodes of the network. The conventional and widely used 33- and 69-node test feeders are used to validate the hybrid CBGA-VSA for analyzing the optimal location and sizing of the DGs in the distribution networks using MATLAB software. The numerical results demonstrate the efficiency of the proposed optimization method in terms of power loss reduction as compared with the results available in the literature. An additional 24-h dimensioning analysis is included for demonstrating the efficiency and applicability of the proposed methodology for daily operations with renewable generation.13 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_abf2Engineering Science and Technology, an International Journal (In Press)Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approachinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Combinatorial optimizationDistributed generatorsGenetic algorithmDistribution networksPower losses reductionVortex search optimization algorithCartagena de IndiasInvestigadoresO.D. Montoya, A. Grajales, A. Garces, C.A. Castro Distribution systems operation considering energy storage devices and distributed generation IEEE Latin Am. Trans., 15 (5) (2017), pp. 890-900L.F. Grisales-Noreña, D. Gonzalez-Montoya, C.A. Ramos-Paja Optimal sizing and location of distributed generators based on PBIL and PSO techniques Energies, 11 (1018) (2018), pp. 1-27O.D. Montoya, L.F. Grisales-Noreña, W.T. Amin, L.A. Rojas, J. Campillo Vortex search algorithm for optimal sizing of distributed generators in AC distribution networks with radial topology Commun. Comput. Inform. Sci., 1052 (2019), pp. 235-249S. Sultana, P.K. Roy Multi-objective quasi-oppositional teaching learning based optimization for optimal location of distributed generator in radial distribution systems Int. J. Electr. Power Energy Syst., 63 (2014), pp. 534-545M. Moradi, M. Abedini A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems Int. J. Electr. Power Energy Syst., 34 (1) (2012), pp. 66-74O.D. Montoya, V.M. Garrido, L.F. Grisales-Noreña, D. González-Montoya, C.A. Ramos-Paja, Optimal Sizing of DGs in AC Distribution Networks via Black Hole Optimization, in: 2018 IEEE 9th Power, Instrumentation and Measurement Meeting (EPIM), 2018, pp. 1–6.S.R. Salkuti, Y.H. Lho Optimum location of voltage regulators in the radial distribution systems Int. J. Emerging Electr. Power Syst., 17 (3) (2016), pp. 351-361, 10.1515/ijeeps-2015-0197O.D. Montoya, W. Gil-González, L. Grisales-Noreña, An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach, Ain Shams Eng. J. doi: 10.1016/j.asej.2019.08.011. URL: http://www.sciencedirect.com/science/article/pii/S2090447919301200.S.Y. Bocanegra, O.D. Montoya Heuristic approach for optimal location and sizing of distributed generators in AC distribution networks Wseas Trans. Power Syst., 14 (2019), pp. 113-121K. Gholami, M.H. Parvaneh A mutated salp swarm algorithm for optimum allocation of active and reactive power sources in radial distribution systems Appl. Soft Comput., 105833 (2019)L. Grisales-Noreña, O.D. Montoya, W. Gil-González Integration of energy storage systems in AC distribution networks: optimal location, selecting, and operation approach based on genetic algorithms J. Energy Storage, 25 (2019), Article 100891S. Kaur, G. Kumbhar, J. Sharma A MINLP technique for optimal placement of multiple DG units in distribution systems Int. J. Electr. Power Energy Syst., 63 (Supplement C) (2014), pp. 609-617S.F. Santos, D.Z. Fitiwi, M.R. Cruz, C.M. Cabrita, J.P. Catalão Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems Appl. Energy, 185 (2017), pp. 44-55M.R. Cruz, D.Z. Fitiwi, S.F. Santos, J.P. 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Hernandez-Escobedo Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators Symmetry, 12 (2) (2020), p. 322, 10.3390/sym12020322O.D. Montoya, W. Gil-González, L. Grisales-Noreña, C. Orozco-Henao, F. Serra Economic dispatch of BESS and renewable generators in DC microgrids using voltage-dependent load models Energies, 12 (23) (2019), p. 4494, 10.3390/en12234494K. Muthukumar, S. Jayalalitha Optimal placement and sizing of distributed generators and shunt capacitors for power loss minimization in radial distribution networks using hybrid heuristic search optimization technique Int. J. Electr. Power Energy Syst., 78 (2016), pp. 299-319M. Moradi, M. Abedini A novel method for optimal DG units capacity and location in Microgrids Int. J. Electr. Power Energy Syst., 75 (2016), pp. 236-244A. Bayat, A. Bagheri Optimal active and reactive power allocation in distribution networks using a novel heuristic approach Appl. 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