Using Modelica language, a mathematical model combining static and dynamic contributions of the dense phase region of a 130 t/h biomass circulating fluidized bed boiler combustion system was established on MWorks simulation platform. The mathematical model adopted modular packaging to increase the universality of the model, and it used an implicit, high-order, and multi-step Dassl integration algorithm to conduct the simulation. Under the design condition parameters, the relative error between the bed temperature of the dense phase region obtained by the simulation model and the actual temperature was less than 3.8%, which indicated that the static characteristics of the established simulation model were accurate. The effects of biomass feed and primary air volume step changes on the bed temperature, oxygen content in the flue gas, height of the dense phase region, and the bed pressure difference in the dense phase region were investigated. Both the biomass feeding and the primary wind step of 10% reduced the temperature, and it was obvious that the primary wind had a greater impact on the bed temperature. Meanwhile, the primary wind had a greater impact on the bed pressure difference than the biomass feeding.

The utilization of coal and other fossil fuels is becoming increasingly restricted. Biomass, as a clean and renewable energy, plays a significant role in achieving zero carbon emissions. However, biomass is prone to slagging in the combustion process due to its high alkali metal content. The ash slagging rate and pollutant emission level of flue gas can be reduced by optimizing the air distribution, in order to decrease the fuel layer temperature in the combustion chamber. The results reveal opposite change trends of CO and NO x concentrations in the flue gas. The NO x emissions of corn stalk combustion under the multilayer secondary air distribution are obvious compared with those of rice husk combustion. The slagging rate of corn stalks is highly correlated with temperature T 1 of the fuel bed. The silica ratio ( G ), alkali/acid ratio ( B / A ), Na content index (Na (index)), and alkaline index (Al c ) cannot accurately predict the slagging tendency when temperature T 1 changes. Therefore, the modified predictive index ( G t ) was proposed to predict the slagging tendency of corn stalks with the combustion zone temperature T 1 effectively. The experimental results can contribute to the efficient combustion and low pollutant emissions of biomass.

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