Optimization of combustion and denitration process for a 1 000 MW ultra-supercritical boiler
The combustion process of boilers is significantly influenced by many factors such as load instructions and coal types.The boiler operation may deviate from the design conditions with high NOx generation concentration,which leads to decreased efficiency of the boiler and excessive ammonia injection in the denitrification system.This paper optimizes the boiler combustion and denitrification processes of a 1 000 MW ultra-supercritical boiler by replacing the relevant control modules in the original DCS system with the self-optimizing control,artificial intelligence control,and feedforward control techniques.The results demonstrate that the energy consumption of the power unit is effectively reduced after optimizing the control system.The reduction in the primary fan energy consumption and the fly ash carbon content means a 1.04 g/(kW·h)decrease in the standard coal consumption for power generation.The average entrance NOx concentration of the selective catalytic reduction system reduces from 301 mg/m3 to 219 mg/m3 with a decrease rate of 27%while the ammonia injection flow reduces from 327 kg/h to 197 kg/h with a decrease rate of 39%.The method can provide reference for the transformation of similar boilers.
ultra-supercritical boilercombustiondenitrificationoptimizationintelligent control
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