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

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.