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Model for the Forecast of the purchase of energy in a Utility through artificial neural networks with penetration of renewable energies

Abstract:

Research develops a planning model to carry out the prognosis of energy purchase that the distribution and marketing company is done through the use of energy demand information and with the penetration of renewable generation in the short and medium-term using a computational model of artificial neuronal networks in the MATLAB computational tool, the results obtained show the performance of this model with errors less than 1% both in training and pbkp_rediction. For the respective testing of this algorithm, the historical data of 5 years of the 'Electric Regional Enterprise Sur Centro C. A.' was taken of the city of Cuenca in Ecuador.