Measurements and Prediction of Ash Deposition in a Cyclone-Fired Boiler Operating under Variable Load Conditions

Abstract

Measurements of ash deposition rates were made between the secondary superheater and reheater sections of a 450 MW cyclone-fired lignite boiler as the operational load varied from 33 to 100%. Significant reductions in deposition rates with a decrease in operational load were observed. To uncover the causative mechanisms behind these observations, operational data from the power plant were used to carry out computational fluid dynamic (CFD) simulations of the boiler. After ascertaining that the gas temperatures and velocities at various sections within the boiler were being represented adequately, decoupled simulations of the ash deposition process on the deposit probe were carried out using a finely resolved boundary layer mesh. Fly ash particle size distribution (PSD) and its concentration for the decoupled calculations were determined from stand-alone cyclone barrel simulations. The ash partitioning (mass %) between the fly ash and slag was found to be ~50:50, which was in line with previous field observations, and it did not vary significantly across different cyclone loads. The predicted PSD of the deposit ash was concentrated in the size range 10–30 microns, which was in agreement with cross-sectional images of the deposit obtained from the measurements. At lower loads, sharp variations in the deposition rates were predicted in the gas temperature range 950–1150 K. The particle kinetic energy—particle viscosity-based capture methodology utilized in this study in conjunction with appropriate ash compositions, ash viscosity models and gas temperature estimates can help estimate slagging propensities at different loads reasonably well in these systems.

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“…However, depending on the temperature and composition, µ P predictions can differ by more than an order of magnitude among the models [19,20]. µ P is also a strong function of the gas temperature, and minor variations in gas temperature can cause significant variations in deposition rate predictions when employing the PKE-µ Pbased capture criterion as observed in our recent study in a full-scale boiler [24]. Further compounding this issue is the fact that the constants in the Urbain et al µ P model [23,25], for instance, are based on grouping the species in the molten ash as glass formers, glass modifiers, or amphoterics.…”

“…Senior and Srinivasachar Particle Viscosity Model [22] The particle viscosity model proposed by Senior and Srinivasachar [22] has been shown to be accurate in the low-fouling region corresponding to the temperature range of 1200-1400 K of interest in this study and has been successfully employed to make deposition rate predictions in biomass [20], lignite [24], and bituminous coals [19]. However, its validity in PC fly ash scenarios has not been explored.…”

“…These include gas velocities, temperature, and other transport properties. The validity of such a decoupled simulation approach has been demonstrated by us previously [19,20,24]. The key boundary conditions associated with the deposition rate calculations are summarized in Table 3.…”

“…The deposition rate predictions were close to the measurements and were insensitive to the µ P model formulation employed as long as the deposit ash composition was employed in the µ P calculations (to account for the Fe enrichment). µ P based on the Senior and Srinivasachar [22] model which has previously been found to be accurate in modeling the deposition rates from coal and biomass fly ash in this temperature range (1200 K-1400 K) [19,20,24] underestimated the deposition rates. This likely points to the fact that the fly ash composition for determining µ P is a more important factor for deposition rate prediction than the exact model formulation for µ P .…”

“…While the PKE-critical-viscosity-based capture criterion has generally been employed with coal and biomass ashes [15,19,20,24], its validity in modeling PC ash deposition rates has not been established. In addition, due to the widespread variation in µ P employing different viscosity models as shown in Figure 4a, a second Weber-number-based capture criterion was also explored in this study.…”