Model Prediction and Optimal Control of Gas Oxygen Content for A Municipal Solid Waste Incineration Process

In the municipal solid waste incineration process,it is difficult to effectively control the gas oxygen content by setting the air flow according to artificial experience.To address this problem,this paper proposes an optimization control method of gas oxygen content based on model predictive control.First,a stochastic configuration network is utilized to establish a prediction model of gas oxygen content.Second,an improved differential evolution algorithm that is based on parameter adaptive and t-distribution strategy is employed to address the set value of air flow.Finally,model predictive control is combined with the event triggering strategy to reduce the amount of computation and the controller's frequent actions.The experimental results show that the optimization control method proposed in this paper obtains a smaller degree of fluctuation in the air flow set value,which can ensure the tracking control performance of the gas oxygen content while reducing the amount of calculation.

焦炉燃料燃烧控制及污染物排放特性

为了掌握鞍钢焦炉烟气污染物排放特性，提高焦炉燃料燃烧效率，节省煤气消耗，采用MGA5型红外烟气分析仪对鞍钢12座大容积焦炉的废烟气组成成分进行定量测定。结果表明，目前的JN型焦炉废烟气取样点处氧体积分数普遍偏高，平均为4．63％，使得废烟气带走的热量较多，从而导致炼焦耗热量和生产成本增加。根据焦炉燃料及废烟气流经途径，提出焦炉废烟气多点测量技术，在保证燃料充分燃烧的情况下，空气过剩系数明显降低，最大限度地降低了废烟气带走的热量，减少了焦炉废烟气中氮氧化物的排放。此外，采用多点测量技术，还能够及时监控蓄热室封墙的窜漏情况，有利于提高炼焦生产的操作管理水平。