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Estimación del precio de oferta de la energía eléctrica en Colombia mediante inteligencia artificial || Estimating the Spot Market Price Bid in Colombian Electricity Market by Using Artificial Intelligence

Author

Listed:
  • Hurtado Moreno, Laura

    (Universidad EAFIT, Medellín (Colombia))

  • Quintero Montoya, Olga Lucía

    (Departamento de Ciencias Básicas, Universidad EAFIT, Medellín (Colombia))

  • García Rendón, John Jairo

    (Departamento de Economía, Universidad EAFIT, Medellín (Colombia))

Abstract

Uno de los sectores económicos estratégicos más importantes en cualquier economía es el Mercado de Energía Mayorista, cuya característica fundamental es que se trata de un mercado oligopolístico, provocado por la barrera de entrada que supone tener economías de escala. De esta manera, los agentes pueden presentar comportamientos estratégicos que contribuyen a la maximización de sus utilidades, los cuales se ven reflejados en la oferta diaria del precio y de la cantidad de energía por hora en cada una de sus centrales de generación. En este trabajo se presenta una metodología para la estimación de los precios diarios a los que ofertan la energía que producen los principales recursos hídricos y térmicos en Colombia. Se emplean dos herramientas de Inteligencia Artificial: la Lógica Difusa y las Redes Neuronales. Dichas técnicas resultan ser parcialmente efectivas para seguir las tendencias de dichos precios. También se comparan los resultados con los de modelos autorregresivos, que resultan ser inapropiados para el caso de estudio. || 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 thermal) 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.

Suggested Citation

  • Hurtado Moreno, Laura & Quintero Montoya, Olga Lucía & García Rendón, John Jairo, 2014. "Estimación del precio de oferta de la energía eléctrica en Colombia mediante inteligencia artificial || Estimating the Spot Market Price Bid in Colombian Electricity Market by Using Artificial Intelli," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 18(1), pages 54-87, December.
    • Handle: RePEc:pab:rmcpee:v:18:y:2014:i:1:p:54-87
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    References listed on IDEAS

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    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

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