CFD based investigations into optimization of coal pulveriser performance: Effect of classifier vane settings

• Published in: Fuel processing technology 2009-09, Vol.90 (9), p.1135-1141
• Main Authors: Shah, K.V., Vuthaluru, R., Vuthaluru, H.B.
• Format: Article
• Language: English
• Subjects: Applied sciences; CFD; Classifier; Energy; Energy. Thermal use of fuels; Exact sciences and technology; Installations for energy generation and conversion: thermal and electrical energy; Multiphase flow; Pulveriser; Thermal power plants; Vane
• ISSN: 0378-3820; 1873-7188
• DOI: 10.1016/j.fuproc.2009.05.009

In coal-fired power plant, pulveriser is the first major component, whose performance dictates the total power plant efficiency. Uniform flow rate and desired size fraction at outlet pipes along with higher classifier efficiency are three important measures which decide the pulverizer performance. Optimization of pulverizer at its best operating conditions has been considered as a potential area that needs to be addressed for improving unit performance, emissions, operations, and maintenance. The best operating conditions are optimum air velocity and classifier vane settings. In this investigation, numerical simulations of a typical pf coal based pulveriser have been carried out for different classifier vane settings to evaluate uniform flow rate and desired size fraction at outlet pipes along with high optimum classifier efficiency. The optimum opening for the vanes has been determined based on the above measures, which not only reduces unburnt CO, SO x and NO x emissions at boiler end but also minimise energy consumption of mill (in terms of reductions in regrinding cost). Computational Fluid Dynamics (CFD) simulations of the coal classifier physical model indicate good agreement with the plant data, in terms of internal flow patterns, particle collection efficiency and desired cut size. From the simulation studies, optimum opening for the vanes is found to be 65% for selected utility which leads to closest uniformity with 60% classifying efficiency wherein 70% particles pass through 75 μm sieve.