Abstract
Boiler combustion optimization control technology is the most cost-effective and effective method to realize efficient combustion and low pollution emission control in power plants. Considering the actual situation of boiler combustion system of thermal power unit, an improved BP neural network boiler combustion optimization algorithm based on non dominated sorting genetic algorithm with elite strategy (NSGA-II) is proposed in this paper. This method is used to optimize the secondary air valve opening and oxygen setting value of boiler combustion, so as to realize the overall optimization and control of boiler combustion efficiency and NOx emission. By comparing the optimization effect of a unit, it shows that the average NOx concentration at the optimized SCR inlet is reduced by 24.3mg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and the boiler efficiency is increased by 0.25%.
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