Search

Combining biomass fuel with coal in circulating fluidized bed (CFB) boilers is attractive as the increasing of energy demand. The characteristics of biomass/coal co-firing in the industrial boiler are then investigated using computational fluid dynamics (CFD). In this study, fuels of interest are coal, wood chips, and bark. The fuel proportions were set for investigating their effects on the combustion using a simplex centroid mixture design. CFD simulations consist of a standard k-epsilon viscosity flow model, Euler multiphase fluid flow model, and a simplified biomass-char combustion reaction model. The predictive responses of the model are bed temperature, heat flux, and carbon dioxide (CO2) and carbon monoxide (CO) mass flows. The simulation results showed that the operation with coal gave the highest temperature and heat flux, followed by wood chips and bark. On the other hand, the operation with biomass releases fewer gas emissions, CO2 and CO, than those of the operation with coal. The type and proportion of boiler fuel can be easily determined using two methods: predictive equation and ternary contour plot graph, which can be likened to the digital twin of biomass/coal co-firing boiler.

In this work, the industrial-scale co-fired power plant in Thailand was analyzed and the optimization model was proposed to provide a proper fuel selection for the feedstock seasonal planning to minimize the cost of electricity generation. Also, the dust emission model was introduced in this work to investigate the environmental concern of the proposed fuel formula. The seasonal effects including feed price, properties, and availability were also included in the optimization model. The optimum solution reported a set of fuel formulas for each season that is capable of maintaining power production stability and minimizing fuel costs. Although, the global demand for coal was at its peak in the winter season, using biomass (wood chip, wood bark, and fiber) could increase the production to achieve its minimum requirement. The optimization could reduce the cost of electricity (COE) production by up to 14% (in the winter season). Also, the emission model indicated that to increase the steam production rate to meet the requirement in the summer season, a larger amount of mixed fuel consumption rate was needed. This led to an increase in dust emissions in the summer season. However, in the winter season, the result from optimization could decrease dust emissions by up to 50%. In conclusion, increasing biomass utilization is a favorable option in both economic and environmental aspects.