Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/113876
Authors: 
Hurtado Moreno, Laura
Quintero Montoya, Olga Lucía
García Rendón, John Jairo
Year of Publication: 
2014
Citation: 
[Journal:] Revista de Métodos Cuantitativos para la Economía y la Empresa [ISSN:] 1886-516X [Volume:] 18 [Year:] 2014 [Pages:] 54-87
Abstract (Translated): 
One of the most important economic strategic sectors in any economy is the electricity market. Its main feature is its oligopolistic character favoured by the returns to scale which act as an entry barrier. As a result, the energy generators can use their power market in order to increase their benefits through the daily offered price and quantity of energy for each of their power plants. This paper presents a methodology for estimating the daily offered price of the most important power stations in Colombia (hydraulic and ther- mal) by applying artificial intelligence techniques: Fuzzy Logic and Neural Networks. Such techniques are found to be partially useful particularly for price tendencies. It also compares the results with autoregressive models that turned out inappropriate for the case of study.
Subjects: 
wholesale energy market
price bid
Artificial Intelligence
Fuzzy Logic
JEL: 
D43
L11
L81
Document Type: 
Article

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