Abstract
Emissions, including CO2 emissions, are generated during the combustion process. Perfect combustion of biomass should not lead to the formation of CO, but all carbon should burn perfectly and change to CO2 by the oxidation process. Under real conditions, complete combustion never occurs and part of the carbon is not burned at all or only imperfectly to form CO. The aim of the work was to create a prediction model of machine learning, which allows to predict in advance the amount of CO2 generated during the combustion of wood pellets. This model uses machine learning regression methods. The most accurate model (Gaussian process) showed a root-mean-square error, RMSE = 0.55. The resulting mathematical model was subsequently verified on independent measurements, where the ability of the model to correctly predict the amount of CO2 generated in % was demonstrated. The average deviation of the measured and predicted amount of CO2 represented a difference of 0.53 %, which is 8.8 % of the total measured range (3.08 - 9.2). Such a model can be modified and used in the prediction of other combustion parameters.
Highlights
A number of households include a heat source for heating, in which energy is converted into heat, which is used to ensure thermal comfort
The prediction of the concentration of CH4, CO, CO2 and H2 was calculated using a model based on artificial neural network (ANN) and the results show a good agreement with the experimental outputs by achieving a coefficient of determination - R2 > 0.98 for CH4, CO, CO2 and H2 [8]
An interesting concept for further direction would be to link the information obtained from a specific model with specific combustion phenomena and their application to create a comprehensive combustion model using artificial intelligence tools
Summary
A number of households include a heat source for heating, in which energy is converted into heat, which is used to ensure thermal comfort. When burning pellets in order to obtain energy, it is often necessary to maintain some combustion parameters in the required range of values so that undesirable conditions do not occur or, in order to achieve the necessary combustion outputs. To predicting some combustion parameters, which are based on other measured quantities of combustion, it is appropriate to use regression techniques to obtain specific values. Using this technique, a model is created in this article, where the amount of CO2 emissions generated during the pellet combustion process is determined
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