Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer
This document presents a solution method for optimal power flow (OPF) problem in direct current (DC) networks by implementing a master-slave optimization methodology that combines an antlion optimizer (ALO) and a power flow approach based on successive approximation (SA ). In the master stage, the A...
- Autores:
-
Garzón Rivera O.D.
Ocampo, J.A
Grisales-Noreña, Luis Fernando
Montoya, O.D
Rojas-Montano, J.J.
- 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:20.500.12585/9998
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9998
http://www.iapress.org/index.php/soic/article/view/1022
- Palabra clave:
- Antlion optimization
Direct current microgrids
Metaheuristic optimization methods
Optimal power flow analysis
Power flow
Successive approximation
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer |
| title |
Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer |
| spellingShingle |
Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer Antlion optimization Direct current microgrids Metaheuristic optimization methods Optimal power flow analysis Power flow Successive approximation LEMB |
| title_short |
Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer |
| title_full |
Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer |
| title_fullStr |
Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer |
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Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer |
| title_sort |
Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer |
| dc.creator.fl_str_mv |
Garzón Rivera O.D. Ocampo, J.A Grisales-Noreña, Luis Fernando Montoya, O.D Rojas-Montano, J.J. |
| dc.contributor.author.none.fl_str_mv |
Garzón Rivera O.D. Ocampo, J.A Grisales-Noreña, Luis Fernando Montoya, O.D Rojas-Montano, J.J. |
| dc.subject.keywords.spa.fl_str_mv |
Antlion optimization Direct current microgrids Metaheuristic optimization methods Optimal power flow analysis Power flow Successive approximation |
| topic |
Antlion optimization Direct current microgrids Metaheuristic optimization methods Optimal power flow analysis Power flow Successive approximation LEMB |
| dc.subject.armarc.none.fl_str_mv |
LEMB |
| description |
This document presents a solution method for optimal power flow (OPF) problem in direct current (DC) networks by implementing a master-slave optimization methodology that combines an antlion optimizer (ALO) and a power flow approach based on successive approximation (SA ). In the master stage, the ALO determines the optimal amount of power to be delivered by all the distributed generators (DGs) in order to minimize the total power losses in the distribution lines of the DC network. In slave stage, the power flow problem is solved considering constant power loads and power outputs of DGs as constants. To validate the effectiveness and robustness of the proposed model, two additional comparative methods were implemented: particle swarm optimization (PSO) and black hole optimization (BHO). Two distribution test feeders (21 and 69 nodes) were simulated under different scenarios of distributed power generation. The simulations, conducted in MATLAB 2018$b$, show that the proposed method (ALO) presents a better balance between power loss minimization and computational time required to find the optimal solution regardless of the size of the DC network. |
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2020 |
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2020-10-06 |
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2021-02-15T16:13:11Z |
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2021-02-15T16:13:11Z |
| dc.date.submitted.none.fl_str_mv |
2021-02-12 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/article |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Garzon-Rivera, O., Ocampo, J., Grisales-Norena, L., Montoya, O., & Rojas-Montano, J. (2020). Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer. Statistics, Optimization & Information Computing, 8(4), 846-857. https://doi.org/10.19139/soic-2310-5070-1022 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/9998 |
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http://www.iapress.org/index.php/soic/article/view/1022 |
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10.19139/soic-2310-5070-1022 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Garzon-Rivera, O., Ocampo, J., Grisales-Norena, L., Montoya, O., & Rojas-Montano, J. (2020). Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer. Statistics, Optimization & Information Computing, 8(4), 846-857. https://doi.org/10.19139/soic-2310-5070-1022 10.19139/soic-2310-5070-1022 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/9998 http://www.iapress.org/index.php/soic/article/view/1022 |
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eng |
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eng |
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info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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12 páginas |
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application/pdf |
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Cartagena de Indias |
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Statistics, Optimization & Information Computing Vol 8 No 4 (2020) |
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Universidad Tecnológica de Bolívar |
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Garzón Rivera O.D.7f839c44-6d86-4cd0-a102-b788eda85288Ocampo, J.Ab3256834-32a1-4b89-b646-e40b233189a4Grisales-Noreña, Luis Fernando98ba5e2d-fa38-40c5-a05c-d73772e8ab17Montoya, O.Dc350cd1a-09d0-4e77-8444-83ccfd0773e1Rojas-Montano, J.J.057d2dbe-412e-4ed2-9b0f-5c120939aa3a2021-02-15T16:13:11Z2021-02-15T16:13:11Z2020-10-062021-02-12Garzon-Rivera, O., Ocampo, J., Grisales-Norena, L., Montoya, O., & Rojas-Montano, J. (2020). Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer. Statistics, Optimization & Information Computing, 8(4), 846-857. https://doi.org/10.19139/soic-2310-5070-1022https://hdl.handle.net/20.500.12585/9998http://www.iapress.org/index.php/soic/article/view/102210.19139/soic-2310-5070-1022Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis document presents a solution method for optimal power flow (OPF) problem in direct current (DC) networks by implementing a master-slave optimization methodology that combines an antlion optimizer (ALO) and a power flow approach based on successive approximation (SA ). In the master stage, the ALO determines the optimal amount of power to be delivered by all the distributed generators (DGs) in order to minimize the total power losses in the distribution lines of the DC network. In slave stage, the power flow problem is solved considering constant power loads and power outputs of DGs as constants. To validate the effectiveness and robustness of the proposed model, two additional comparative methods were implemented: particle swarm optimization (PSO) and black hole optimization (BHO). Two distribution test feeders (21 and 69 nodes) were simulated under different scenarios of distributed power generation. The simulations, conducted in MATLAB 2018$b$, show that the proposed method (ALO) presents a better balance between power loss minimization and computational time required to find the optimal solution regardless of the size of the DC network.12 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_abf2Statistics, Optimization & Information Computing Vol 8 No 4 (2020)Optimal Power Flow in Direct Current Networks Using the Antlion Optimizerinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Antlion optimizationDirect current microgridsMetaheuristic optimization methodsOptimal power flow analysisPower flowSuccessive approximationLEMBCartagena de IndiasW. LI, Y. GU, H. YANG, W. SUN, Y. CHI and X. HE Hierarchical control of DC microgrids combining robustness and smartness. 2019 CSEE Journal of Power and Energy Systems, pp.1-10. ISSN 2096-0042. DOI:10.17775/CSEEJPES.2017.00920.MANRIQUE, MAR´IA LOURDES, MONTOYA, OSCAR DANILO, GARRIDO, V´ICTOR MANUEL, GRISALES-NORENA˜ LUIS FERNANDO and GIL-GONZALEZ ´ , WALTER Sine-Cosine Algorithm for OPF Analysis in Distribution Systems to Size Distributed Generators. Springer International Publishing. 2019, vol.119, pp.28–39. WEA 2019. DOI:10.1007/978-3-030-31019-63.Z. CHEN, K. WANG, Z. LI and T. ZHENG. A review on control strategies of AC/DC micro grid. 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I CPS Europe), pp.1-6. DOI:10.1109/EEEIC.2017.7977807.OMAR ELLABBAN, HAITHAM ABU-RUB and FREDE BLAABJERG. Renewable energy resources: Current status, future prospects and their enabling technology. 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