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Resumen

 

ARTIFICIAL NEURAL NETWORKS APPLIED TO THE PREDICTION OF PRICES IN ENERGY SPOT

REDES NEURONALES APLICADAS A LA PREDICCION DE PRECIOS EN BOLSA DE ENERGIA
MSc. Eliana Mirledy Toro Ocampo.
MSc Alejandro Garcés Ruiz.
MSc. Juan Carlos Galvis Manso.

Abstract: In this document it is presented the development and the implementation of a model to carry out monthly presage of prices in spot market of energy Colombian wholesaler using Artificial Neural Networks. The input data used were the previous month
price of spot, the considered month, the data of the equivalent reservoir and the prospective demand. The training sets correspond to data from January 1998 until September 2005 with those the model validation was carried out. Results were obtained with a standard deviation of 10.65%.

Resumen: En este documento se presenta el desarrollo y la implementación de un modelo para realizar pronóstico mensual de precios en bolsa del mercado de energía mayorista colombiano usando redes neuronales artificiales. Los datos de entrada utilizados fueron el precio de bolsa del mes anterior, el mes considerado, los datos del embalse equivalente y la demanda esperada. El conjunto de entrenamiento corresponde a datos desde enero de 1998 hasta septiembre de 2005 con los que se realizó la validación del modelo. Se obtuvieron resultados con una desviación estándar de 10.65%.

Keywords: Energy spot, prediction, Artificial neural networks, Back propagation.