Recursive convex approximations for optimal power flow solution in direct current networks
The optimal power flow problem in direct current (DC) networks considering dispersal generation is addressed in this paper from the recursive programming point of view. The nonlinear programming model is transformed into two quadratic programming approximations that are convex since the power balanc...
- Autores:
-
Ocampo-Toro, Jauder Alexander
Montoya, Oscar Danilo
Grisales-Norena, Luis Fernando
- 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:20.500.12585/12215
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12215
- Palabra clave:
- Approximation
Direct current networks
Metaheuristic optimization
Optimal power flow problem
Programming
Quadratic convex
Recursive convex
Techniques
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Recursive convex approximations for optimal power flow solution in direct current networks |
| title |
Recursive convex approximations for optimal power flow solution in direct current networks |
| spellingShingle |
Recursive convex approximations for optimal power flow solution in direct current networks Approximation Direct current networks Metaheuristic optimization Optimal power flow problem Programming Quadratic convex Recursive convex Techniques |
| title_short |
Recursive convex approximations for optimal power flow solution in direct current networks |
| title_full |
Recursive convex approximations for optimal power flow solution in direct current networks |
| title_fullStr |
Recursive convex approximations for optimal power flow solution in direct current networks |
| title_full_unstemmed |
Recursive convex approximations for optimal power flow solution in direct current networks |
| title_sort |
Recursive convex approximations for optimal power flow solution in direct current networks |
| dc.creator.fl_str_mv |
Ocampo-Toro, Jauder Alexander Montoya, Oscar Danilo Grisales-Norena, Luis Fernando |
| dc.contributor.author.none.fl_str_mv |
Ocampo-Toro, Jauder Alexander Montoya, Oscar Danilo Grisales-Norena, Luis Fernando |
| dc.subject.keywords.spa.fl_str_mv |
Approximation Direct current networks Metaheuristic optimization Optimal power flow problem Programming Quadratic convex Recursive convex Techniques |
| topic |
Approximation Direct current networks Metaheuristic optimization Optimal power flow problem Programming Quadratic convex Recursive convex Techniques |
| description |
The optimal power flow problem in direct current (DC) networks considering dispersal generation is addressed in this paper from the recursive programming point of view. The nonlinear programming model is transformed into two quadratic programming approximations that are convex since the power balance constraint is approximated between affine equivalents. These models are recursively (iteratively) solved from the initial point vt equal to 1.0 pu with t equal to 0, until that the error between both consecutive voltage iterations reaches the desired convergence criteria. The main advantage of the proposed quadratic programming models is that the global optimum finding is ensured due to the convexity of the solution space around vt. Numerical results in the DC version of the IEEE 69-bus system demonstrate the effectiveness and robustness of both proposals when compared with classical metaheuristic approaches such as particle swarm and antlion optimizers, among others. All the numerical validations are carried out in the MATLAB programming environment version 2021b with the software for disciplined convex programming known as CVX tool in conjuction with the Gurobi solver version 9.0; while the metaheuristic optimizers are directly implemented in the MATLAB scripts. |
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2022 |
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2022-08-12 |
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2023-07-19T21:22:30Z |
| dc.date.available.none.fl_str_mv |
2023-07-19T21:22:30Z |
| dc.date.submitted.none.fl_str_mv |
2023-07 |
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http://purl.org/coar/version/c_b1a7d7d4d402bcce |
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Ocampo-Toro, J.A., Montoya, O.D., Grisales-Norena, L.F. Recursive convex approximations for optimal power flow solution in direct current networks (2022) International Journal of Electrical and Computer Engineering, 12 (6), pp. 5674-5682. DOI: 10.11591/ijece.v12i6.pp5674-5682 |
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https://hdl.handle.net/20.500.12585/12215 |
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10.11591/ijece.v12i6.pp5674-5682 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Ocampo-Toro, J.A., Montoya, O.D., Grisales-Norena, L.F. Recursive convex approximations for optimal power flow solution in direct current networks (2022) International Journal of Electrical and Computer Engineering, 12 (6), pp. 5674-5682. DOI: 10.11591/ijece.v12i6.pp5674-5682 10.11591/ijece.v12i6.pp5674-5682 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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https://hdl.handle.net/20.500.12585/12215 |
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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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openAccess |
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9 páginas |
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International Journal of Electrical and Computer Engineering - Vol. 12 No. 6 (2022) |
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Ocampo-Toro, Jauder Alexander9c64c41f-1bbf-4b40-9176-04c57560cd08Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Grisales-Norena, Luis Fernando46211f56-02d8-4fd8-b13b-7dc04b35bd052023-07-19T21:22:30Z2023-07-19T21:22:30Z2022-08-122023-07Ocampo-Toro, J.A., Montoya, O.D., Grisales-Norena, L.F. Recursive convex approximations for optimal power flow solution in direct current networks (2022) International Journal of Electrical and Computer Engineering, 12 (6), pp. 5674-5682. DOI: 10.11591/ijece.v12i6.pp5674-5682https://hdl.handle.net/20.500.12585/1221510.11591/ijece.v12i6.pp5674-5682Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe optimal power flow problem in direct current (DC) networks considering dispersal generation is addressed in this paper from the recursive programming point of view. The nonlinear programming model is transformed into two quadratic programming approximations that are convex since the power balance constraint is approximated between affine equivalents. These models are recursively (iteratively) solved from the initial point vt equal to 1.0 pu with t equal to 0, until that the error between both consecutive voltage iterations reaches the desired convergence criteria. The main advantage of the proposed quadratic programming models is that the global optimum finding is ensured due to the convexity of the solution space around vt. Numerical results in the DC version of the IEEE 69-bus system demonstrate the effectiveness and robustness of both proposals when compared with classical metaheuristic approaches such as particle swarm and antlion optimizers, among others. All the numerical validations are carried out in the MATLAB programming environment version 2021b with the software for disciplined convex programming known as CVX tool in conjuction with the Gurobi solver version 9.0; while the metaheuristic optimizers are directly implemented in the MATLAB scripts.9 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_abf2International Journal of Electrical and Computer Engineering - Vol. 12 No. 6 (2022)Recursive convex approximations for optimal power flow solution in direct current 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_2df8fbb1ApproximationDirect current networksMetaheuristic optimizationOptimal power flow problemProgrammingQuadratic convexRecursive convexTechniquesCartagena de IndiasArévalo, J., Santos, F., Rivera, S. 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