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Enhancing optimal transmission or subtransmission planning by using decision trees.

J. Peco, E.F. Sánchez-Úbeda, T. Gómez

IEEE PowerTech Conference - PowerTech 1999, Budapest (Hungría). 28 agosto - 02 septiembre 1999


Resumen:
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.


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


DOI: DOI icon https://doi.org/10.1109/PTC.1999.826607

Fecha de publicación: agosto 1999.



Cita:
Peco, J., Sánchez-Úbeda, E.F., Gómez, T., Enhancing optimal transmission or subtransmission planning by using decision trees., IEEE PowerTech Conference - PowerTech 1999, Budapest (Hungría). 28 agosto - 02 septiembre 1999.


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

IIT-99-059A

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