Identification of the Air Supply System for Combustion, With the Help of Artificial Neural Networks

Abstract

The production of nickel in Cuba is one of the main export items in our economy. In recent years, its production costs have risen significantly, with a high incidence of electricity costs, which is why it is necessary to take energy shock measures to reverse this situation. Currently there are deficiencies in the Reduction Furnace plant related to the control of the air supply and the electric power used by the asynchronous motors that drive the centrifugal fans, reducing the efficiency levels of the production process and the plant in general. In order to increase the energy efficiency of the combustion process supply system and reach an optimum control model of the airflow of this plant, variants are designed and simulated based on artificial neural networks that allow to establish the air demand from the drive of the fans by means of variable speed drives.