热风炉煤气消耗量灰色预测模型的开发

Development of Grey Prediction Model for Gas Consumption of Hot Blast Stove

针对热风炉系统非线性、大滞后、大惯性,煤气消耗量难以有效预测的问题,以某高炉热风炉为研究对象,采用灰色模型对煤气消耗量进行预测。介绍了预测模型的建模方法、系统软件结构、预测模型的建立步骤,通过粒子群算法优化了模型参数,最后使用灰色模型对该高炉热风炉煤气消耗量进行预测,结果说明该方法预测准确,具有较强的实践意义,为调度人员准确把握煤气资源的波动趋势,进行优化调配提供了可靠依据,降低了能耗。

To solve the problem of nonlinear,big delay,big inertia and difficulty to effectively predict gas consumption,grey model was adopted to predict gas consumption taking the hot blast stove of a blast furnace as study subject.The modeling method,system software structure and construction steps of the prediction model are introduced.The model parameters were optimized through particle swarm algorithm and a grey model was finally used to predict the gas consumption of a hot blast stove.Results showed that the method can predict accurately,bears strong practical significance,provides reliable basis for dispatching personnel to accurately grasp the fluctuating trend of gas resource and carry out optimized dispatching as well as reduces energy consumption.