基于燃料比最优的高炉喷煤设定值多目标优化

Multi-objective Optimization of Blast Furnace Coal Injection Setting Based on Optimal Fuel Ratio

为了降低高炉炼铁的能耗,节约成本,将高炉炼铁过程信息、专家经验与智能模型相结合,提出基于燃料比最优的高炉喷煤设定值多目标优化方案。以燃料比最优为优化目标,炉温预测指标为约束条件,喷煤量为决策变量,采用基于K-均值聚类的径向基神经网络建立多目标优化模型,并通过基于NSGA-Ⅱ算法的多目标优化方法,获取尽可能使多个目标同时达到最优的Pareto最优解。结果表明,该优化方案可以在保证炉温良好的前提下,决策出使燃料比达到最优的喷煤设定值,大大降低能耗,节约成本。不仅为高炉实际生产提供操作指导,也为高炉冶炼的优化运行奠定了基础。

To reduce the energy consumption and cost of blast furnace ironmaking,the blast furnace ironmaking process information,expert experience,and intelligent model were combined,and a multi-objective optimization research plan of blast furnace coal injection setting was proposed based on optimal fuel ratio.The fuel ratio as the optimal target,the furnace temperature prediction index as the constraint condition,and the coal powder quantity as the decision variable,the multi-objective optimization model was established by using the radial basis neural network based on K-means clustering,and the multi-objective optimization method based on NSGA-II algorithm was used to obtain the Pareto optimal solution that maximizes multiple targets at the same time.Results show that under the premise of ensuring good furnace temperature,the optimization scheme could determine the coal injection setting value to optimize the fuel ratio,which greatly reduced the energy consumption and saved the cost,which provides an operational guidance for the actual production of blast furnaces,and lays the foundation for the optimal operation of blast furnace smelting.