Algoritmo de Optimización de Mapeo de Media Varianza Aplicado al Despacho Óptimo de Potencia Reactiva

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Auteur principal: Daniel Camilo Londoño Tamayo
Format: Artículo científico
Langue:es
Publié: Corporación Universitaria de la Costa 2021
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author Daniel Camilo Londoño Tamayo
author_facet Daniel Camilo Londoño Tamayo
contents Algoritmo de Optimización de Mapeo de Media Varianza Aplicado al Despacho Óptimo de Potencia Reactiva Daniel Camilo Londoño Tamayo Jesús María López Lezama Walter Mauricio Villa Acevedo Ingeniería mean Reactive power constraint handling power loss minimization metaheuristic techniques Introduction— 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. 2021 artículo científico 0122-6517 https://www.redalyc.org/articulo.oa?id=497779339012 es http://www.redalyc.org/revista.oa?id=4977 INGE CUC application/pdf Corporación Universitaria de la Costa INGE CUC (Colombia) Num.1 Vol.17
format Artículo científico
id redalyc_497779339012
institution Redalyc
language es
publishDate 2021
publisher Corporación Universitaria de la Costa
spellingShingle Algoritmo de Optimización de Mapeo de Media Varianza Aplicado al Despacho Óptimo de Potencia Reactiva
Daniel Camilo Londoño Tamayo
Ingeniería
mean
Reactive power
constraint handling
power loss minimization
metaheuristic techniques
Algoritmo de Optimización de Mapeo de Media Varianza Aplicado al Despacho Óptimo de Potencia Reactiva Daniel Camilo Londoño Tamayo Jesús María López Lezama Walter Mauricio Villa Acevedo Ingeniería mean Reactive power constraint handling power loss minimization metaheuristic techniques Introduction— 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. 2021 artículo científico 0122-6517 https://www.redalyc.org/articulo.oa?id=497779339012 es http://www.redalyc.org/revista.oa?id=4977 INGE CUC application/pdf Corporación Universitaria de la Costa INGE CUC (Colombia) Num.1 Vol.17
title Algoritmo de Optimización de Mapeo de Media Varianza Aplicado al Despacho Óptimo de Potencia Reactiva
topic Ingeniería
mean
Reactive power
constraint handling
power loss minimization
metaheuristic techniques
url https://www.redalyc.org/articulo.oa?id=497779339012