The Mining Analysis And Model Design Of Iron And Steel Enterprise Energy Optimization

Steel enterprises adjust the industrial structure, which makes the world energy situation increasingly tense. How to reduce energy consumption in steel industry have become important areas, in which the study of energy saving optimization is the key direction. Therefore, it has great social significance and economic value to analyze the key energy consumption factors in steel industry, design and implement an energy optimization model in line with the actual business and develop a reasonable production program. In the background of the actual production of a large domestic steel enterprise, this thesis uses data mining technology and energy information management technology to analyze the production data characteristics. Moreover, this thesis studies the production technology and energy relations in steel enterprises theoretically and actually.In this theis, we study the production technology in a steel enterprise in depth, analyze the mechanism of action quantitative relations among primary production systems, energy conversion systems, auxiliary production systems and other systems and establish model for the material and energy flows throughout the steel production process, which provides a theoretical basis for the whole process energy optimization model. Data mining technology for the first time using a lot of idle production data characteristics is applied to analyze energy consumption in steel enterprises. Firstly, the data characteristics of sintering process, iron-making process and steelmaking process in primary production system are used to develop a specific pretreatment method for the original database from data selection, cleaning, discrete, and several other operations, which ensure the efficiency of data mining and usefulness of the generated rules. Secondly, the improved project constraints association rules algorithm Apriori-rule is used to mine and analyze various processes to get the key logistics factors affect composite per ton energy consumption. Moreover, two reasonable energy efficiency production programs are proposed. Thirdly, due to the difference of energy-saving process and energy-saving system, energy model in steel joint enterprises is designed and a whole process energy optimization model is established. Finally, against the complexity of the model and the defects of the conventional solving methods, solving methods of nonlinear model called CS-SAF which is based on cuckoo evolutionary method by introducing annealing penalty factor and non-differentiable penalty function.The energy correctness of optimization model and feasibility of energy-saving programs are verified on real datasets from certain steel enterprise mills in Benxi, which shows that the established energy optimization model is correct and the proposed programs are available.