木块气化过程焦油联合脱除工况优化

基于松木块气化试验数据,建立了燃气焦油炉内、炉外联合脱除过程最小二乘支持向量机模型（LS—SVM）。在燃气焦油炉内脱除工况优化基础上,针对催化剂活性进一步拟合了燃气焦油炉外催化裂解脱除过程多目标优化模型,优化计算得到气化燃气焦油联合脱除工况的Pareto最优解集。寻优结果表明,气化炉出口燃气焦油质量浓度低于2g/m3,满足焦油催化裂解器对入口燃气焦油含量要求;焦油催化裂解器出口燃气焦油质量浓度降低至0.126~0.340g/m3之间,同时满足燃气热值大于4MJ/m3的工程要求,燃气总体品质明显优于试验结果。

Conditions Optimization for Tar Combined Removal in the Woodblock Gasification Technological Process

The LS-SVM(least square supporting vector machine) model of combined tar removal process in pine block gasification was established according to the experimental data.On the basis of condition optimizing for tar removal in the furnace,multi-objective optimization function for catalytic activity was put forward,and then the Pareto-optimal solutions were gained after optimization.The results showed that the tar content from gasifier outlet was less than 2 g/m3,which met the requirements of inlet tar content for catalytic cracker.The tar content at the entrance of tar catalytic cracker was between 0.126 g/m3 and 0.340 g/m3.The gas heating value was more than 4 MJ/m3,met the engineering requirements,so after condition optimization,the gas quality is better than that of the experimental results.