Algoritmo de optimización de mapeo de media varianza aplicado al despacho óptimo de potencia reactiva

Mean-variance mapping optimization algorithm applied to the optimal reactive power dispatch

dc.creatorLondoño Tamayo, Daniel Camilo
dc.creatorLopez Lezama, Jesus Maria
dc.creatorVilla Acevedo, Walter Mauricio
dc.date2023-07-10T16:43:59Z
dc.date2023-07-10T16:43:59Z
dc.date2021
dc.date.accessioned2023-10-03T19:53:46Z
dc.date.available2023-10-03T19:53:46Z
dc.identifierD. Londoño Tamayo, J. López Lezama & W. Villa Acevedo, “ Mean-Variance Mapping Optimization Algorithm Applied to the Optimal Reactive Power Dispatch”, INGECUC, vol. 17. no. 1, pp. 239–255. DOI: http://doi.org/10.17981/ingecuc.17.1.2021.19
dc.identifier0122-6517
dc.identifierhttps://hdl.handle.net/11323/10314
dc.identifier10.17981/ingecuc.17.1.2021.19
dc.identifier2382-4700
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9173079
dc.descriptionIntroduction— The optimal reactive power dispatch (ORPD) problem consists on finding the optimal settings of several reactive power resources in order to minimize system power losses. The ORPD is a complex combinatorial optimization problem that involves discrete and continuous variables as well as a nonlinear objective function and nonlinear constraints. Objective— This article seeks to compare the performance of the mean-variance mapping optimization (MVMO) algorithm with other techniques reported in the specialized literature applied to the ORPD solution. Methodology— Two different constraint handling approaches are implemented within the MVMO algorithm: a conventional penalization of deviations from feasible solutions and a penalization by means of a product of subfunctions that serves to identify both when a solution is optimal and feasible. Several tests are carried out in IEEE benchmark power systems of 30 and 57 buses. Conclusions— The MVMO algorithm is effective in solving the ORPD problem. Results evidence that the MVMO algorithm outperforms or matches the quality of solutions reported by several solution techniques reported in the technical literature. The alternative handling constraint proposed for the MVMO reduces the computation time and guarantees both feasibility and optimality of the solutions found.
dc.descriptionIntroducción— El problema del despacho óptimo de potencia reactiva (DOPR) consiste en encontrar la configuración óptima de diferentes recursos de potencia reactiva para minimizar las pérdidas de potencia del sistema. El DOPR es un problema complejo de optimización combinatorial que involucra variables discretas y continuas, así como una función objetivo no lineal y restricciones no lineales. Objetivo— En este artículo se busca comparar el desempeño del algoritmo de optimización de mapeo de media varianza (MVMO, por sus siglas en inglés) con otras técnicas reportadas en la literatura especializada aplicadas a la solución del DOPR. Metodología— En el algoritmo MVMO se aplican dos enfoques diferentes de manejo de restricciones: penalización convencional de las desviaciones de las soluciones factibles y penalización por medio del producto de subfunciones que sirve para identificar cuándo una solución es óptima y factible. Se realizan simulaciones en sistemas de prueba IEEE de 30 y 57 barras. Conclusiones— El algoritmo MVMO es efectivo para solucionar el DOPR. Los resultados evidencian que el algoritmo MVMO supera o iguala a varias técnicas reportadas en la literatura técnica en la calidad de soluciones. El manejo alternativo de restricciones propuesto para el MVMO reduce el tiempo de cálculo y garantiza tanto factibilidad como optimalidad de las soluciones encontradas.
dc.format17 páginas
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languagespa
dc.publisherCorporación Universidad de la Costa
dc.publisherColombia
dc.relationINGE CUC
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dc.rightsDerechos de autor 2021 INGE CUC
dc.rightsAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourcehttps://revistascientificas.cuc.edu.co/ingecuc/article/view/3109
dc.subjectReactive power
dc.subjectMetaheuristic techniques
dc.subjectPower loss minimization
dc.subjectConstraint handling
dc.subjectMean-variance mapping optimization
dc.subjectPotencia reactiva
dc.subjectTécnicas metaheurísticas
dc.subjectMinimización de pérdidas
dc.subjectManejo de restricciones
dc.subjectOptimización de mapeo de media-varianza
dc.titleAlgoritmo de optimización de mapeo de media varianza aplicado al despacho óptimo de potencia reactiva
dc.titleMean-variance mapping optimization algorithm applied to the optimal reactive power dispatch
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/publishedVersion
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