Enhancing optimal transmission or subtransmission planning by using decision trees.

J. Peco, E.F. Sánchez-Úbeda, T. Gómez

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

Summary:
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.

DOI: 10.1109/PTC.1999.826607

Publication date: August 1999.

Citation:
Peco, J., Sánchez-Úbeda, E.F., Gómez, T., Enhancing optimal transmission or subtransmission planning by using decision trees., IEEE PowerTech Conference - PowerTech 1999, Budapest (Hungary). 28 August - 02 September 1999.

IIT-99-059A