OPTIMIZATION METHODS IN MINIMIZATION
OF EMISSIONS FROM COMBUSTION
SAARIO, A.1, MÄKIRANTA, R.2, BACKLUND, A.3 and OKSANEN, A.4
1 Oilon International Oy, Lahti, Finland
2 Oilon Energy Oy, Lahti, Finland
3 Metso Power Oy, Tampere, Finland
4 Tampere University of Technology, Tampere, Finland
Combustion Optimization
•
Systematic and efficient
•
Both with computational and experimental approaches
•
Three examples
1)
CFD-model and optimization algorithms to minimize NH3 and
NO emission of 40 MW boiler (multiobjective optimization)
2)
CFD-model and design of experiments to minimize NO
emission of low-NOx gas burner
3)
Experimental reactor and design of experiments to study NO
formation in fluidized bed combustion conditions
FIRST EXAMPLE
Interaction of Optimization and CFD
Sketch of Bubbling Fluidized Bed Boiler
Location of Ammonia Injections
Multiobjective Optimization Problem
•
Objective function vector f(x): f(x) = (f1(x), f2(x))T
where f1(x) and f2(x) measure the concentrations of NO and NH3 (ppmvol) in
flue gas (conflicting objectives)
•
Design variable vector x:
x = (X1, X2,…, X9)T
where Xi stands for the concentration of NH3 (vol-%) in the ith injection
•
Feasible set S:
9
S
x
| 0 Xi
•
6.60 for all i 1, 2, ..., 9, g x
mflow
M NH3
M flow
9
Xi
1 100
i
Optimization problem is formulated as
fi x
minimize max
x S
i 1, 2
zinad
ziref
ziid
2
i 1
fi x
zinad
ziref
ziid
r max 0, g x
2
m NH3, max
0
Predicted Points in Objective Space
Predicted Pareto Optimal Points in Design Space
Convergence of Genetic Algorithm
First Example - Conclusions
• A real-world problem solved successfully using CFD and
optimization algorithms
• Over 10% reduction in NO emission obtained while
maintaining NH3 emission at an acceptable level
• Approximation of Pareto-front obtained
• Effectiveness of different optimization algorithms
evaluated
SECOND EXAMPLE
Low-NOx Natural Gas Burner
•
5 MW low-NOx natural gas burner
•
Objective function: minimize NO emission
•
Design variables: sizes of fuel injection
holes
•
Design of experiments method used to
specify the cases to be calculated by
CFD (altogether 21 cases)
•
Response surface model can be
constructed on the basis of these 21
cases to evaluate the minimum NO
emission
Predicted max Temperature and NO Emission
THIRD EXAMPLE
NO Formation in Experimental Reactor
•
Laboratory-scale experimental reactor to study the
formation of NO in fluidized bed combustion
conditions
•
Objective function: NO emission in flue gas
•
Four design variables:
– Temperature in the reactor
– Concentrations of O2, NO, and NH3 in the reactor
•
Design of experiments
– Total of 81 test runs reduced to only 9 test runs
by using Taguchi’s method
Experimental Plan (Taguchi)
Response Table
Conclusions
• Optimization methods
– Systematic and efficient, no guessing
– Obtain more information with fewer CFD-runs / experiments
– Applicable for a wide range of combustion-related problems
– A reliable model / experiment is a pre-requisite for optimization
Thank you for your interest!