Abstract:

A computational fluid dynamics (CFD)-based mathematical model is applied to study 
emission formation in an industrial-scale bubbling fluidized bed boiler burning a 
fuel mixture consisting mainly of biomass. A modification of the standard k-epsilon 
model is used to model turbulence, global mechanisms are used to model chemical 
reactions, the eddy-dissipation combustion model and the eddy-dissipation concept 
are used to model turbulence-chemistry interaction, and the finite-volume method 
(discrete ordinates) together with the weighted-sum-of-grey-gases model are used 
to model radiative heat transfer. A simplified approach is used to take into account 
the bubbling bed in the overall CFD model. Experimental data available on the 
temperature and the concentrations of NO and NH3 are presented to validate the 
predictions to a certain extent. It is emphasized that the CFD-based study of a 
real-world industrial boiler contains significant uncertainties and that the results 
must be evaluated with great care.

The error caused by the computational grid may easily dominate the errors caused by 
simplified models used in industrial-scale boiler modeling. It is shown that over 
two million computational cells may be required for the grid-independent solution 
for only a single jet. On the other hand, local grid refinement is shown to be a 
good option for improving the predictions without an excessive increase in the 
number of computational cells.

The predictions are shown to be strongly dependent on the chosen ammonia chemistry 
mechanism. Mechanisms suitable for modeling ammonia injection, i.e. the selective 
noncatalytic reduction (SNCR) process, are identified, and it is shown that the 
correct emission formation trends can be predicted as a function of the SNCR process 
load. Due to the different conditions prevailing in the lower and upper part of the 
boiler, a combination of more than one mechanism may be a good approach in modeling 
the whole boiler.

After the CFD-based model has been validated to a certain extent, it is used for 
optimization. There are nine design variables (nine distinct NH3 injections in the 
SNCR process) and two conflicting objective functions (minimize NO and NH3 emission 
in flue gas). The multiobjective optimization problem is solved using the 
reference-point method involving an achievement scalarizing function. An interactive 
approach is used to incorporate the preferences of decision makers and to generate 
Pareto optimal solutions. Two inherently different optimization algorithms, viz. a 
genetic algorithm and Powell's conjugate-direction method, are applied in the solution 
of the resulting optimization problem. The constraints are incorporated using a penalty 
function.

With respect to the current operating point, approximately 12% decrease in the NO 
emission is obtained, while maintaining the NH3 emission at an acceptable level. It 
is shown that the optimization connected with CFD is a promising and scientific approach 
for combustion optimization. The strengths and weaknesses of the proposed approach and 
of the interactive multiobjective optimization method used are discussed from the point 
of view of the complex real-world optimization problem. Also, the performance of the two 
optimization algorithms is evaluated. Some techniques related to the reduction of overall 
computational cost are applied in the present study, and some other possible techniques 
are reviewed.