Viscosity virtual sensor to control combustion in fossil fuel power plants |
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Authors: | Pablo H Ibargüengoytia Miguel Angel Delgadillo Uriel A García Alberto Reyes |
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Affiliation: | Instituto de Investigaciones Eléctricas, Reforma 113, Cuernavaca, Morelos 62490, Mexico |
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Abstract: | Thermo-electrical power plants utilize fossil fuel oil to transform the calorific power of fuel into electric power. An optimal combustion in the boiler requires the fuel oil to be in its best conditions. One of fuel's most important properties to consider is viscosity. Viscosity has influence on the optimal combustion between fuel and air. Hardware viscosity meters for fuel oils are expensive and unreliable to operate in power plant conditions. Chemical laboratory measures viscosity accurately with special apparatus, but they cannot be used in a real time process. This paper describes the development of a virtual sensor that estimates fuel oil viscosity in the combustion process of a power plant. A virtual sensor or soft sensor is a computer program that estimates the value of a certain variable based on related measurements and a model of the process where the variable participates. In this project, a probabilistic model is constructed using automatic learning algorithms with historical data and experts' advice. The learning and validation experiments are described and discussed. The virtual sensor is installed in the Tuxpan Power Plant in Veracruz, Mexico. |
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Keywords: | Virtual sensors Bayesian networks Power plants Automatic learning Fuel oil |
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