燃煤烟气污染物超低排放的智慧优化控制方法与关键技术

Pollutants from coal-fired power plants are the major cause of severe air pollution issues in China. Currently, the denitrification, desulfurization, dust removal, and other equipments in coal-fired power plants are operated separately without overall collaborative optimization and intelligent control. It is difficult to achieve ultra-low emissions at wide load range under dynamic change of flue gas flow rate and pollutant composition caused by the variation of boiler load and coal composition. Intelligent optimization control theory and key technology for ultra-low emissions of coal-fired flue gas pollutants will be studied in this project, focusing on: highly precise online analyzer of low concentration flue gas pollutants for ultra-low emissions; advanced control strategy for the key equipments; hybrid modeling method based on fusion of process mechanistic model and data driven model for multiple pollutants; global collaborative optimization algorithm based on energy consumption, material consumption and cost analysis. An experimental platform for the intelligent optimization control of coal-fired flue gas pollutants for ultra-low emissions will be developed. Ultra-low emissions of coal-fired flue gas pollutants with high reliability and low cost will be demonstrated by industrial application validation. Providing technical support to enhance the intelligence of coal-fired pollution comprehensive treatment and air pollution regulation, this project will have significant scientific influence and widespread applications in this nation and Zhejiang Province.

燃煤烟气污染物是形成雾霾的重要原因。在现有的燃煤烟气污染物减排过程中，烟气脱硝、脱硫、除尘等装置彼此独立运行，当锅炉变负荷、燃煤变煤种导致烟气处理量、污染物成分动态变化时，由于缺乏整体的协同优化与智能调控，难以高效稳定地实现超低排放。本项目研究燃煤烟气污染物超低排放的智慧优化控制方法与关键技术，重点突破：超低排放低浓度污染物的高精度在线检测技术，烟气处理关键装置的先进控制策略，烟气多种污染物协同脱除过程基于工艺机理模型与数据驱动模型融合的混合建模方法，基于能耗-物耗-成本分析的全局协同优化算法等，构建可满足燃煤烟气污染物超低排放智慧优化控制研究的实验平台，并开展示范工程应用验证，实现燃煤烟气污染物高可靠低成本超低排放的目标，为全面提升我国和浙江省燃煤污染综合治理及大气污染调控的智能化水平提供关键技术支撑，因此具有重要的科学意义和广阔的应用前景。

项目针对进一步提高燃煤电厂超低排放系统的稳定性、可调性与经济性等关键难题，建立了适用于超低排放系统的污染物高精度在线监测方法，解决了低温、高湿环境的低浓度污染物检测难题；建立了针对超低排放环保系统脱硝、除尘和脱硫等关键装置污染物脱除机理与数据融合的混合模型，解决了变煤质变工况条件下关键装置出口污染物浓度及装置关键运行参数的准确预测难题；开发了脱硝、除尘和脱硫等关键装置的运行优化及智能控制方法，显著减小了变煤质变工况条件下关键装置出口污染物浓度的波动范围，降低了系统能耗。成果在热电机组超低排放系统上实现工程示范应用，长时间结果表明，SCR脱硝装置出口NOx排放浓度波动下降50%以上，WFGD脱硫装置能耗可降低20%以上，除尘装置能耗可下降30%以上，实现了超低排放系统高效与节能降耗优化运行协同。.项目成果可为全国燃煤电厂超低排放系统高效、稳定、经济运行提供重要支撑。依托该项目，已申请发明专利29件，获批软件著作权登记3项；培养何梁何利基金科学与技术创新奖获得者1人，教授1人，博士/硕士研究生30人；项目成果是2017年国家技术发明奖一等奖的重要组成部分。

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