data mining; power system planning; probabilistic method; random sampling; Monte-Carlo; real example
Abstract :
[en] This paper describes a methodology for the study of long-term network planning under uncertainties. In this approach the major external uncertainties during the planning horizon are modelled as macro-scenarios at different future time instants. The random nature of actual operating conditions is taken into account by using a probabilistic model of micro-scenarios based on past statistics. MonteCarlo simulations are used to generate and simulate a specified number of scenarios. Data mining techniques are then applied to the simulations results collected in a database, so as to extract information and to rank scenarios and network reinforcements according to different performance criteria. The paper describes the application of this approach on a real transmission planning problem faced by the Belgian transmission system operator.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Druet, Christophe
Vassena, Stefano
Rousseaux, Patricia ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Système et modélisation
Wehenkel, Louis ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Language :
English
Title :
Application of a data minig based technique for the evaluation of transmission expansion plans
Publication date :
2005
Event name :
15th Power System computation conference (PSCC)
Event organizer :
ULg - Université de Liège
Event place :
Liège, Belgium
Event date :
August 22-26
Audience :
International
Main work title :
Proceedings of the 15th Power System Computation Conference (PSCC)