Improved coal combustion optimization model based on load balance and coal qualities

Abstract Combustion optimization by fine tuning combustion parameters of boilers can cut down NO x emissions effectively with little cost. Coal qualities, which change from time to time, have great influences on NO x emissions. However, the current NO x reduction optimization model cannot handle with this problem well. What is more, the output load would deviate from the demand load as the boiler efficiency is also affected by the optimized manipulated variables (MVs). In this paper, an on-line method to calculate coal qualities based on reverse balance thermal efficiency model was integrated into the optimization model. Furthermore, a new constraint was added to the optimization model to meet the demand load. NO x emission characteristics of some 600 MW capacity utility boiler were investigated. Fine selected MVs were taken as the inputs of support vector machines (SVM) and NO x emission was taken as the output, respectively. Parameters of SVM were fine tuned by particle swarm optimization algorithm (PSO). Combustion optimization for the studied boiler was undertaken based on the proposed optimization model. Results showed that the new model can provide lower NO x emissions and meet demand loads at the same time.

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