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Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system

Medina, Miguel A and Ramirez, Juan M and Coello, Carlos A and Das, Swagatam (2014) Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system. DYNA; Vol. 81, núm. 185 (2014); 196-203 Dyna; Vol. 81, núm. 185 (2014); 196-203 2346-2183 0012-7353 .

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URL oficial: http://revistas.unal.edu.co/index.php/dyna/article...

Resumen

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.

Tipo de documento:Artículo - Article
Información adicional:Derechos de autor reservados
Palabras clave:Multi-objective evolutionary algorithm based on decomposition (MOEA/D), Multi-objective Teaching-learning algorithm, Optimal reactive power dispatch.
Unidad administrativa:Revistas electrónicas UN > Dyna
Código ID:37002
Enviado por : Dirección Nacional de Bibliotecas STECNICO
Enviado el día :02 Julio 2014 19:26
Ultima modificación:18 Agosto 2014 21:47
Ultima modificación:18 Agosto 2014 21:47
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