摘要
在“双碳”背景下,提高废钢消耗比例和降低铁钢比已成为钢铁行业能效提升和节能降碳的重要途径。随着废钢资源的不断积累和环保压力的增加,钢铁企业迫切需要找到一个平衡点,既能有效利用废钢资源,又能控制成本和提高经济效益。基于某厂实际生产数据,首先通过物料平衡和热平衡分析构建了一个静态估计模型,结果显示,物料平衡的计算误差为0.13%,热平衡的计算误差约为0.18%,证实了静态模型的准确性,并通过模型的矫正,调整废钢加入量以减少计算误差。其次,为了进一步提高模型预测的准确性,采用随机森林算法对钢水产量、轻烧白云石加入量和石灰加入量进行预测。测试集数据预测的均方根误差RMSE分别为1.9259、0.25614和0.43336,预测方差分别为0.83741、0.86133和0.87614,这证明随机森林算法在预测中的可靠性和有效性。最后,结合原料价格和预测结果,构建了最佳废钢比的计算模型。根据当前原料价格,模型计算出最佳废钢比例为27%。而当钢水价格上涨、废钢价格下降时,最佳废钢比例增至32%。该模型可以基于原料的不同价格计算出使吨铁水利润达到最大的废钢比,优化废钢利用比例,实现高效利用废钢资源、降低碳排放和提高能源效率,为相关企业实现转炉智能、低碳、高效和低成本生产提供一定的理论基础。
In the context of"Double Carbon,"increasing the proportion of scrap steel consumption and reducing the iron-to-steel ratio have become important pathways for improving energy efficiency and achieving carbon reduction in the steel industry.With the continuous accumulation of scrap steel resources and increasing environmental pressures,steel companies urgently need to find a balance point that allows for effective utilization of scrap steel resources while controlling costs and improving economic benefits.Based on actual production data from a specific plant,a static estimation model was constructed using material balance and heat balance analysis.The results showed a calculation error of only 0.13%for material balance and approximately 0.18%for heat balance,confirming the accuracy of the static model.By adjusting the amount of scrap steel added through model calibration,the calculation error was reduced.Furthermore,to further improve the accuracy of the model predictions,the random forest algorithm was adopted to forecast the steel output,the amount of light-burned dolomite added,and the amount of lime added.The root mean square error(RMSE)for the test dataset predictions was 1.9259,0.25614,and 0.43336,respectively,and the variance was 0.83741,0.86133,and 0.87614,respectively,demonstrating the reliability and effectiveness of the random forest algorithm in prediction.Finally,combining the raw material prices and the prediction results,a calculation model for the optimal scrap steel ratio was developed.Based on the current raw material prices,the model calculated the optimal scrap steel ratio to be 27%.However,when the steel price increases and the scrap steel price decreases,the optimal scrap steel ratio increases to 32%.This model can calculate the scrap steel ratio that maximizes profit per ton of iron based on different raw material prices,optimizing the utilization of scrap steel,achieving efficient utilization of scrap steel resources,reducing carbon emissions,and improving energy efficiency.The present study
作者
王健豪
方庆
王家辉
罗霄
张华
倪红卫
WANG Jianhao;FANG Qing;WANG Jiahui;LUO Xiao;ZHANG Hua;NI Hongwei(Key Laboratory for Ferrous Metallurgy and Resources Utilization of Ministry of Education,Wuhan University of Science and Technology,Wuhan 430081,Hubei,China;Hunan Valin Xiangtan Iron and Steel Co.,Ltd.,Xiangtan 411101,Hunan,China)
出处
《钢铁》
CAS
CSCD
北大核心
2024年第3期79-91,共13页
Iron and Steel
基金
国家自然科学基金资助项目(52004191)
中国博士后科学基金资助项目(2022M711120)
湖北省教育厅科学技术研究资助项目(B2022020)。
关键词
转炉
吨铁水利润
废钢比
随机森林算法
物料预测
converter
profit per ton of molten iron
scrap steel ratio
random forest algorithm
material prediction
