Abstract

Coal pulverizers play an important role in the functioning and performance of a PC-fired boiler. The main functions of a pulverizer are crushing, drying and separating the fine coal particles toward combustion in the furnace. It is a common experience that mill outlet pipes have unequal coal flow in each pipe and contain some coarse particles. Unequal coal flow translates into unequal air-to-fuel ratio in the burner, deviating from the design value and thus increasing unburned carbon in fly ash, NO x and CO. Coarser particles at the mill outlet originate from poor separation and decrease the unit efficiency. In addition, coarser particles reduce burner stability at low load. Air flow distribution at the mill throat, as well as inside the mill, significantly influences the mill performance in terms of separation, drying, coal/air flow uniformity at the mill outlet, wear patterns and mill safety. In the present work, a three-dimensional computational fluid dynamics (CFD) model of the MPS Roll Wheel pulverizer at Alliant Energy's Edgewater Unit 5 has been developed. The Eulerian–Lagrangian simulation approach in conjunction with the coal drying model in Fluent, a commercial CFD software package, has been used to conduct the simulation. Coal drying not only changes the primary air temperature but it also increases the primary air flow rate due to mass transfer from coal. Results of the simulation showed that a non-uniform airflow distribution near the throat contributes significantly to non-uniform air–coal flow at the outlet. It was shown that uniform velocity at the throat improves the air and coal flow distribution at the outlet pipes. A newly developed coal mill model provides a valuable tool that can be used to improve the pulverizer design and optimize unit operation. For example, reject coal rate, which is controlled by the air flow near the mill throat, can be reduced. The model can also be used to further aid in identifying and reducing high temperature or coal-rich areas where mill fires are most likely to start.

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