Artificial intelligence toolbox for planning and operation of power systems

Author

Wehenkel, Louis ; Mack, Philippe

Author_Institution

Dept. of Electr. Eng., Liege Univ., Belgium

Volume

2

fYear

2000

fDate

2000

Firstpage

1057

Abstract

The paper describes an approach based on the combination of Monte-Carlo simulations with a Data Mining toolbox, which has been used extensively to study the behavior of electric power systems, and in particular isolated power systems. We focus on the techniques required by this approach, and in particular the main methods used in the Data Mining toolbox, such as decision and regression tree induction, nearest neighbor methods, and artificial neural networks. Some applications are briefly outlined

Keywords

Monte Carlo methods; data mining; decision trees; neural nets; power system analysis computing; power system planning; statistical analysis; Data Mining toolbox; Monte-Carlo simulations; artificial intelligence toolbox; artificial neural networks; decision tree induction; isolated power systems; nearest neighbor methods; power systems operation; power systems planning; regression tree induction; Analytical models; Artificial intelligence; Data mining; Distributed power generation; Power generation; Power generation economics; Power system modeling; Power system planning; Power system simulation; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society Winter Meeting, 2000. IEEE

Print_ISBN

0-7803-5935-6

Type

conf

DOI

10.1109/PESW.2000.850085

Filename

850085