Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
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| Natura: | Artículo científico |
| Lingua: | en |
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Universidad Nacional de Colombia
2014
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| _version_ | 1876430606898823168 |
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| author | Miguel A. Medina |
| author_facet | Miguel A. Medina |
| contents | Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system Miguel A. Medina Juan M. Ramirez Carlos A. Coello Swagatam Das Ingeniería D) Multi objective Teaching learning algorithm Optimal reactive power dispatch This paper presents a multi-objective teaching learning algorithm based on decomposition for solving the optimal reactive power dispatch problem (ORPD). The effectiveness and performance of the proposed algorithm are compared with respect to a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and the NSGA-II. A benchmark power system model is used to test the algorithms’ performance. The results of the power losses reduction as well as the performance metrics indicate that the proposed algorithm is a reliable choice for solving the problem. 2014 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49631031029 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.185 Vol.81 |
| format | Artículo científico |
| id | redalyc_49631031029 |
| institution | Redalyc |
| language | en |
| publishDate | 2014 |
| publisher | Universidad Nacional de Colombia |
| spellingShingle | Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system Miguel A. Medina Ingeniería D) Multi objective Teaching learning algorithm Optimal reactive power dispatch Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system Miguel A. Medina Juan M. Ramirez Carlos A. Coello Swagatam Das Ingeniería D) Multi objective Teaching learning algorithm Optimal reactive power dispatch This paper presents a multi-objective teaching learning algorithm based on decomposition for solving the optimal reactive power dispatch problem (ORPD). The effectiveness and performance of the proposed algorithm are compared with respect to a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and the NSGA-II. A benchmark power system model is used to test the algorithms’ performance. The results of the power losses reduction as well as the performance metrics indicate that the proposed algorithm is a reliable choice for solving the problem. 2014 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49631031029 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.185 Vol.81 |
| title | Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system |
| topic | Ingeniería D) Multi objective Teaching learning algorithm Optimal reactive power dispatch |
| url | https://www.redalyc.org/articulo.oa?id=49631031029 |