MATEC Web Conf.
Volume 345, 202120th Conference on Power System Engineering
|Number of page(s)||9|
|Published online||12 October 2021|
Machine learning model designed to predict the amount of CO2 produced by a small pellet boiler
KET, SjF, Žilinská Univerzita v Žiline, Univerzitná 1, 010 26 Žilina
* Corresponding author: email@example.com
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.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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