前馈修正的循环流化床机组脱硝系统多模型预测控制研究  

Research on Multi-model Predictive Control of Denitrification System of CFB Unit Based on Feedforward Modification

作　　者：谭畅 陈竹 邵宇浩 赵中阳 周灿 李钦武 杨超[3] 郑成航[1] 高翔[1] TAN Chang;CHEN Zhu;SHAO Yuhao;ZHAO Zhongyang;ZHOU Can;LI Qinwu;YANG Chao;ZHENG Chenghang;GAO Xiang(State Key Laboratory of Clean Energy Utilization(Zhejiang University),Hangzhou 310027,Zhejiang Province,China;Zhejiang Hope Environmental Protection Engineering Co.,Ltd.,Hangzhou 310012,Zhejiang Province,China;College of Control Science and Engineering,Zhejiang University,Hangzhou 310027,Zhejiang Province,China)

机构地区：[1]能源清洁利用国家重点实验室(浙江大学),浙江省杭州市310027 [2]浙江浩普环保工程有限公司,浙江省杭州市310012 [3]浙江大学控制科学与工程学院,浙江省杭州市310027

出　　处：《中国电机工程学报》2023年第5期1867-1874,共8页Proceedings of the CSEE

基　　金：国家自然科学基金项目(U1609212);山东省重大科技创新工程项目(2019JZZY010403)。

摘　　要：双碳政策的深入推进对燃煤机组负荷灵活调峰能力提出了更高要求,然而机组负荷大范围变化时会造成烟气NO_(x)浓度的大幅度波动,提升了NO_(x)超低排放控制的难度。针对大范围变负荷工况下难以快速、精准调控喷氨量的难题,以某循环流化床机组联合脱硝系统为研究对象,建立关键参数前馈修正与多模型预测控制耦合的控制策略,以炉膛出口烟气温度为依据划分工况子模型,根据阶跃扰动试验及改进粒子群算法对各子模型进行参数辨识,并通过隶属度加权方法建立多模型控制器。工程应用结果表明,前馈修正的多模型预测控制方法在平稳负荷工况时波动范围达到±5.8mg/m^(3),变负荷工况时为±8.1mg/m^(3),标准差分别为2.10和2.89mg/m^(3),应用结果证明了该控制方法的有效性。The carbon-neutral policy puts forward higher requirement for the load peak shaving capacity of coal-fired power plants.However,the NO_(x) concentration in the flue gas will fluctuate greatly while the load of the unit changes in a large range,which makes it more difficult to control ultra-low NO_(x) emission.Aiming at the problem that it is difficult to quickly and accurately control the spray amount of ammonia under large-scale variable load conditions,this paper took the combined denitrification system of a circulating fluidized bed power plant as the research object,and established a control strategy that coupled key parameter feedforward correction and multi-model predictive control.Using the furnace outlet flue gas temperature as the basis to divide the working condition sub-models,the parameters of each sub-model were identified according to the step disturbance tests and the improved particle swarm optimization.Finally,the multi-model controller was established through the degree of membership weighted method.Engineering application result shows that,the feedforward modified multi-model predictive control method has a fluctuation range of±5.8mg/m^(3) under steady load conditions,and it is±8.1mg/m^(3) under variable load conditions.The standard deviations are 2.10mg/m^(3) and 2.89mg/m^(3) respectively.The application result proves the effectiveness of this control method.

关 键 词：多模型预测控制 前馈控制 选择性非催化还原与选择性催化还原联合脱硝 超低排放 燃煤 循环流化床 

分 类 号：TK39[动力工程及工程热物理—热能工程]