A generalized model of SO2 emissions from large- and small-scale CFB boilers by artificial neural network approach: Part 1. The mathematical model of SO2 emissions in air-firing, oxygen-enriched and oxycombustion CFB conditions

•Artificial neural network approach is used to study SO2 emissions from CFB boilers.•A wide range of operating conditions are considered in the paper.•Large- and small-scales CFB boilers are taken into account by the model.•Calculations are carried out for air-firing, oxygen-enriched and oxycombustion conditions.•The model gives quick and accurate results for large- and small-scale CFB units.

Since the complexity of sulfur capture and release during solid fuel combustion in circulating fluidized bed (CFB) boilers, especially in the oxycombustion conditions is still not sufficiently recognized, the development of a simple SO2 emission model for wide range of operating conditions is of practical significance.The paper introduces the artificial neural network (ANN) approach for the prediction of SO2 emissions from CFB boilers. The model considers a wide range of parameters influencing SO2 emissions. The [16-1-6-1] ANN model was successfully applied to predict SO2 emissions from coal combustion in several large- and small-scale CFB boilers, over a wide range of operating conditions, both in air-firing as well as oxygen-enriched and oxycombustion conditions.Since the method constitutes a quick and easy to run technique this approach makes a complementary tool in relation to the experimental procedures and the programmed computing approach. Therefore, the model can be easily applied by scientists and engineers for simulations and optimizations of CFB units.