Using of Data Mining and Soft Computing Techniques for Modeling Bidding Prices in Power Markets

Author

Camargo, M. ; Jimenez, Daniel ; Gallego, L.

Author_Institution

Nat. Univ. of Colombia, Medellin, Colombia

fYear

2009

fDate

8-12 Nov. 2009

Firstpage

1

Lastpage

6

Abstract

This paper presents an application of Data Mining (DM) and Soft Computing (SCT) techniques in order to model the bidding prices of Generators Agents (GENCO´s) of the Colombian electricity Market. Several methodologies were applied an hydraulic generator case to discover some patterns about the bidding process and predict values of the bidding price in relation to market variables by using some Data Mining tools (DM). On the other hand techniques of soft computing such as fuzzy systems, neural networks and ANFIS were implemented to describe the behavior of the agent. There are very good tools since work uncertain data helping to represents in this case, the possible strategies of the agents.

Keywords

data mining; fuzzy neural nets; fuzzy reasoning; power engineering computing; power markets; ANFIS; adaptive neuro-fuzzy inference systems; bidding prices; data mining; power markets; soft computing; spot market; Artificial intelligence; Computer networks; Costs; Data mining; Delta modulation; Electricity supply industry; Fuzzy systems; Marketing and sales; Power generation; Power markets; ANFIS; artificial intelligence; bidding price; classification Bayes; data mining; decision tree; electrical market; fuzzy systems; neural network; soft computing; spot market;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent System Applications to Power Systems, 2009. ISAP '09. 15th International Conference on

Conference_Location

Curitiba

Print_ISBN

978-1-4244-5097-8

Type

conf

DOI

10.1109/ISAP.2009.5352872

Filename

5352872