1000 MW超超临界锅炉燃烧与脱硝过程优化

Optimization of combustion and denitration process for a 1000 MW ultra-supercritical boiler

为解决锅炉燃烧过程受负荷指令、入炉煤种等因素影响会偏离设计工况,NO_(x)生成浓度偏高,进而导致锅炉效率降低,脱硝系统喷氨量过大等问题,以某发电有限公司1000 MW超超临界锅炉为研究对象,将自寻优控制技术、仿人智能控制技术、智能前馈技术替代原DCS系统中相关控制模块功能,实现锅炉燃烧优化和脱硝过程调整。结果表明:调整后的控制系统可以有效降低机组的发电能耗,一次风机能耗与飞灰含碳量降低所对应发电标准煤耗降低总量为1.04 g/(kW·h);脱硝系统入口NO_(x)浓度与脱硝系统喷氨量大幅降低,SCR入口两侧NO_(x)浓度均值由301 mg/m^(3)下降至219 mg/m^(3),降幅达到27%,脱硝系统两侧平均喷氨流量由327 kg/h降至197 kg/h,降幅为39%。所述方法可供同类锅炉改造参考。

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 NO_(x) 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 1000 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/m^(3) to 219 mg/m^(3) 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.