钢铁企业高炉煤气供需预测模型及应用-journalofnortheastern.pdf

第31卷第12期 东 北 大 学 学 报 ( 自 然 科 学 版 ) Vol31,No. 12 2010 年 12 月 Journal of Northeastern niversity( Natural Science) Dec. 2 0 10 1 2 1 1 张 琦 , 谷延良 , 提 威 , 蔡九菊 ( 1. , 110004; 2. , 066326) : , ,BP , , :, ,, : ;BP ; ;; : TF 4 : A : 1005-3026(2010) 12-1737-04 Supply-Demand ForecastingModel of BlastFurnace Gasin Iron Steel Works and Its Application 1 2 1 1 ZH A N G Qi , G U Yan-liang , TI Wei , CA I Jiu-j u ( 1. School of Materials Metallurgy, Northeastern niversity, Shenyang 110004, China; 2. Shouqin Metal Materials Co. Ltd., Qinhuangdao 066326, China. Correspondent: ZHANG Qi, E-mail: neu zq @ 126. com) - Abstract: With the blast furnacegas (BFG) system of an iron and steelworks taken as an object, the relationship between the gas throughput and influencing factors on BFG generation/ consumption was analyzed by grey correlation. A prediction model of BFG was developed on the basis of BP neural network for forecasting the supply and demand of BFG in thewhole iron/ stee-l making process. The reasonability of the forecasting of BFG generation and consumption was discussed on various working conditions including normal operation and troubleshooting. The results showed that the forecasting model developed is of high precision with small errors and available to predict actually the BFG supply and demand so as to decrease the unnecessary BFG emission. The model is therefore able to lay a theoretical foundation to schedule the BFG utilization reasonably. ey words: supply and demand forecasting; BP neural network; BFG; iron and steel works; energy saving ( BFG)