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The development of a slagging and fouling predictive methodology for large scale pulverised boilers fired with coal/biomass blends

This dissertation deals with the development of a co-firing advisory tool capable of predicting the effects of biomass co-firing with coal on the ash deposition and thermal performance of pulverised fired (pf) boilers. The developed predictive methodology integrates a one-dimensional zone model of a pf boiler to determine the heat transfer conditions and midsection temperature profile throughout the boiler, with the phase equilibrium–based ash deposition mechanistic model that utilises FactSageTM thermo-chemical data. The designed model enables advanced thermal analysis of a boiler for investigating the impact of fuel switching on boiler performance including the ash deposition effects. With respect to the ash deposition predictive model, the improved phase equilibrium approach, adjusted to the pf boiler conditions was proposed that allows the assessment of the slagging and high temperature fouling severity caused by the deposition of the sticky ash as well as low-temperature fouling due to salts condensation. An additional ash interaction phase equilibrium module was designed in order to estimate the interactions occurring in the furnace between alumino-silicate fly ash and alkali metals originating from biomass. Based on the developed model, the new slagging/fouling indices were defined which take into account the ash burden, slag ratio in the fly ash approaching the tube banks as well as the slag viscosity corresponded to the conditions within the pf boiler. The developed model was validated against field observations data derived from semiindustrial pf coal-fired furnace as well as a large scale 518 MWe pf boiler fired with a blend of imported bituminous coals and biomass mix composed of the various quality biomass/residues, such as meat and bone meal, wood pellets and biomass mix pellets produced on-site: the power plant typically fired up to 20wt% coal substitution. Good agreement has been found for the comparison between predictions and slagging/fouling observations. Based on the validated model the fuel blend optimisation was performed up to 30wt% co-firing shares revealing highly non-additive ash behaviour of the investigated fuel blends.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:600558
Date January 2013
CreatorsPlaza, Piotr
PublisherCardiff University
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://orca.cf.ac.uk/58453/

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