Ir arriba
Informacion del artículo en conferencia

Enhancing optimal transmission or subtransmission planning by using decision trees.

J. Peco, E.F. Sánchez-Úbeda, T. Gómez

Due to the large size of electric power systems there is a very high computational burden when obtaining the optimum network by using classical optimization techniques. Several authors have used heuristics and/or sensisitivities in order to guide the search of optimal network investments. This paper proposes an Automatic Learning approach in order to decide whether a network change will improve the overall costs or not. more specifically, Decision Trees methods are used to identifiy a set of simple and reliable rules which combine criteria trees are integrated in a subtransmission planning tool, improving dramatically both the “optimality” of the resultant network and the computational time.


Keywords: Transmission planning, planning rules, automatic learning, decision trees, genetic algorithms, data mining.

Paper BPT99-304-16 . IEEE Power Tech '99 Conference, Budapest, Hungary, August 29-September 2, 1999.

DOI: DOI icon 10.1109/PTC.1999.826607    

Publicado: agosto 1999.


    Líneas de investigación:
  • *Predicción y Análisis de Datos
  • *Planificación táctica a medio plazo

IIT-99-059A

pdf Solicitar el artículo completo a los autores



Aviso legal  |  Política de cookies |  Política de Privacidad

© Universidad Pontificia Comillas, Escuela Técnica Superior de Ingeniería - ICAI, Instituto de Investigación Tecnológica

Calle de Santa Cruz de Marcenado, 26 - 28015 Madrid, España - Tel: (+34) 91 5422 800