Byproduct Gas Optimal Distribution Model and its Application for Iron and Steel Enterprises

2011 ◽  
Vol 58-60 ◽  
pp. 816-821
Author(s):  
Tao Du ◽  
Xiang Bin Liu ◽  
Xing Lu Pang
Keyword(s):  
Energy Resource ◽  
Distribution Model ◽  
Optimal Distribution ◽  
Oil Consumption ◽  
Normal Range ◽  
Gas Emission ◽  
Iron And Steel ◽  
Steel Making ◽  
Byproduct Gas ◽  
Gas Supply

A MILP model for optimization of byproduct gas supply in the iron and steel making process is proposed. This model can make the holder fluctuate keep in the normal range, prevent unfavorable byproduct gas emission or shortage, minimize oil consumption and switch the burners in the boil, and it can simultaneously maximize the efficiency of energy resource usage in the iron and steel making process.

Application of Improved Real-Valued Genetic Algorithm in Gas Dispatching of Iron and Steel Enterprise

2015 ◽  
Author(s):  
Fuyong Su
Keyword(s):  
Genetic Algorithm ◽  
Energy Source ◽  
Environmental Pollution ◽  
Energy Use ◽  
Gas Emission ◽  
Optimal Program ◽  
Iron And Steel ◽  
Byproduct Gas ◽  
Objective Model ◽  
Important Kind

Byproduct gas is an important kind of secondary energy generated along with iron and steel products in iron and steel enterprise, which plays an important role in the product process. The use of byproduct gas is not carefully considered, the caloric value doesn’t always match, and the amount of gas is not correctly used, and the fact of gas emission still exists, which is a waste of energy source, and will raise the problem of environmental pollution, of course. Based on the situations above, we have studied the current situation of an iron and steel enterprise, and built the objective model for the optimal use of the gas, and set the constraints accordingly. Finally, based on the concept of Ant Colony Algorism, we improved the algorism to solve our model, and achieved the optimal program, which is an evidence for the energy use.

Research on Temperature Distribution and Stress Distribution Model of Prefabricate Block Electric Furnace Roof

2014 ◽  
Vol 494-495 ◽  
pp. 289-292
Author(s):  
Xin Can Li
Keyword(s):  
Electric Furnace ◽  
Economic Benefits ◽  
Distribution Model ◽  
Electric Steel ◽  
Furnace Roof ◽  
Iron And Steel ◽  
Finite Element Software ◽  
Steel Making ◽  
Stable Temperature ◽  
Heat Preservation

Electric furnace roof is an important device for electric steel making, whose heat preservation performance and life-span have a direct impact on the economic benefits of iron and steel enterprise. Considered contact behavior between prefabricate block, this paper establishes the complete CAD/CAE model of the electric furnace roof with finite element software based on the theory of transferring heating subject, and respectively calculates the stable temperature and stress field of the firebrick roof and the prefabricate block roof in last melting stage, as is advantageous to analyze the level and the distribution of temperature and stress of electric furnace roof.

Online Strategy for Scheduling By-Product Gas Consumption and Adjusting Gas Holder Level in Iron and Steel Industry

2013 ◽  
Vol 798-799 ◽  
pp. 263-266
Author(s):  
Hai Ru ◽  
Feng Gao ◽  
Yin Feng Xu ◽  
Xiao Hong Guan
Keyword(s):  
Production Process ◽  
Reference Value ◽  
Decision Makers ◽  
Iron And Steel ◽  
Steel Making ◽  
Product Gas ◽  
Total Profit ◽  
Gas Consumption ◽  
Online Strategy ◽  
Gas Supply

The more efficient use of by-product gas has always been a hot issue in the iron and steel making process. The gas generated during production process is stochastic and hardly predicted accurately. Specifically, how to regulate the supply of by-product gas from gas holder to power plant in the scheduling period to maximize the total profit of gas reutilization is present work. In response to this objective, online algorithm will be applied here to analyses the optimal strategy, which manages the by-product gas supply scheduling in term of online strategy and competitive analysis. We give the competitive ratio’s lower bound of the problem, and analyze the properties of algorithms, then give the QEW-algorithm with a competitive ratio equals to γ/(γ-β). The results of the study have guiding significance and reference value to decision makers facing the actual production process.

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