基于自适应智能前馈的SCR脱硝系统优化控制

Optimal Control of SCR Denitration System Based on Self-adaptive Intelligent Feedforward

随着环保要求的不断提高,选择性催化还原(selective catalytic reduction,SCR)烟气脱硝系统得到了广泛应用。针对SCR系统具有的大延迟、大惯性特性,将SCR系统机理模型与前馈控制方法相结合,采用滑动窗口法对模型参数进行更新并及时调整反馈系数,提出自适应智能前馈控制方法。利用现场实际运行数据,通过仿真实验对该方法进行验证,实验结果表明,与传统PID控制方法相比,该方法能够实现喷氨量的准确、及时调节,在保证脱硝效率的同时避免了过量喷氨。

With the incessant improvement of environmental requirements,selective catalytic reduction(SCR)flue gas denitration systems are widely used for power plants.For the large delay and great inertia of SCR system,combining mechanism model of SCR and feedforward control method,employing sliding window method to update model parameters and adjust feedback coefficient in time,self-adaptive intelligent feedforward control method was proposed.Actual operation data was applied to verify the method based on simulation experiment.The results show that comparing with traditional PID control method,this method achieves the accurate and timely control of the amount of ammonia and improves the denitration rate as well as avoids excessive ammonia injection.