The Research On Uncertain Optimization Model Of Buproducts Gas Scheduling And Dust Reduction In Steel Company

With the explosive growth of steel industry,a series of problems,including energy exhaustion,environmental pollution and climate change,have attracted extensive attention around the world.As the pillar-type industry with the high energy-consuming and high polluting characteristics,steel industry have caused obvious increase in energy consumption and pollutants emission and prominent contradiction between energy supply and production requirement.This fact make steel industry is under enormous pressure sourced from energy conservation and environmental protection.Therefore,how to realize steel industry's targets for saving energy and reducing pollutant emissions is an important task.In order to realize above-mentioned target and overcome a series of issues existing in using deterministic optimization approaches for supporting byproduct gas scheduling and air pollution control,such as excessive assumptions and oversimplifications,large deviations of the parameters estimation,irrational model structure and inaccurate computational results,in this thesis,based on uncertain optimization approaches,the theoretical and practical research associated with the design and execution of the gas scheduling schemes and the dust reduction and control alternatives are conducted.The accurate identification and expression of components,structure and operation pattern belonging to gas scheduling system and dust reduction and control system in the steel company is the important base for formulating byproduct gas allocation model and dust reduction and control model.In this study,benefit maximization of gas system and cost minimization of dust reduction and control are considered as major system targets;meanwhile,some system requirements and logical relationships,including the operation rules of gas storage tank,user demand,operation limitations of boilers and turbines,emission restrictions of pollution sources and regional environmental capacities,are regarding as system constraints,such that two systems are established,i.e.the byproduct gas allocation system with gas-generation facilities,users,gas-storage tank and boilers,the air pollution control and management system composing of emission sources,weather stations,environmental monitoring stations,residential areas and pollutants-reduction technologies.They provide critical support for formulation of optimization model and generation of decision alternatives.The energy conservation of gas system is major job of steel company,since the byproduct gas is valuable secondary energy.In order to overcome the difficulties in data analysis and statistics sourced from gas generation,transportation,allocation and utilization,eliminate the impact on the gas allocation system caused by the design of company-production schedule,the operation of company-production technology and subjective initiative of schedule staff and avoid these situations that model results are inaccurate and generated gas allocation schemes are irrational because traditional deterministic optimization models are incapable of reflecting the realistic situation,in this thesis,the uncertain optimization techniques,including interval numbers,type-1 and type-2 fuzzy sets,and birandom variables,are used to build two byproduct-gas allocation models,which are formulated and solved through two-step interactive algorithm,fuzzy chance-constrained programming and stochastic chance-constrained programming.As a result,optimal operation alternatives of gas storage tanks,boilers and turbines are obtained,optimal allocation amounts of byproduct gas in various system components are determined,which provided support and help to the design and execution of energy conservation in steel company.The high energy-consuming and high polluting characteristics owned by steel company imposed a constant pressure on the surroundings.Currently,the dust pollution issue caused by steel company,especially air pollution problem,already affected normal life of local residents.Therefore,how to solve the dust pollution issue is critical.Considering the design and execution of the dust reduction and control patterns in City Tangshan as an example,the major pollution source in the studied region(i.e.Baotai steel company)is selected as the research target,two uncertain optimization methods,including interval stochastic robust optimization and fuzzy fractional programming approaches,are used to establish two corresponding dust reduction and control models,where uncertain properties of pollution control costs,emission standards of pollution sources and regional environmental quality standards are expressed as their respective interval,fuzzy and stochastic forms.As a result,optimal design of pollution-control measures under dispersion simulation of regional air pollutants are accomplished and the best control alternatives of major pollution sources located in the steel company are determined,which provided effective decision support for pollution-sources reduction and regional air environmental management and lead to enhancement of adaptability and robustness of management alternatives.