Fundamental Research On Optimization And Synergy Of Material Flow And Energy Flow In Steel Manufacturing Process

It is more and more difficult for energy conservation in steel manufacturing process (SMP) with small energy conservation space, by reviewing energy conservation course of iron and steel industry in China in recent 30 years. In the future, only through synergy of material flow (MF) and energy flow (EF), can the energy conservation work enter into a new stage. However, mainly focusing on the static optimization of single equipment or energy medium, current research is less involved in dynamic interaction research between MF and EF in the whole process. It is much rarer to see the reports of synergy of MF and EF. Aiming at the above problems, the following work is accomplished.(1) Dissecting the running law of MF and EF to construct the reasonable running modes.According to the physical nature of dynamic operation of SMP, the running elements of SMP were devised, and the basic running modes of MF and EF were built. Also the running law of MF and EF were revealed essentially, and the dynamic properties of MF and EF were studied. At the meantime, the mathematical methods and measurable indices to describe the dynamic MF and EF, especially the definition of equilibrium degree of MF and EF to describe the dynamic volatility, were put forward in this work.(2) Studying dynamic optimization of MF with EF consumption constraints.According to the order of’production plan, maintenance plan and operation schedule’, dynamic optimization of EF was studied from system level, and simulation analyses were carried out. To improve equipment efficiency and availability, production back-casting decision-making model for process products was established, and the optimal output of each process was studied, combined with contract orders and inventory situation. To minimize EF loss, equipment maintenance plan ranking model was set up, and the effect of maintenance order on EF loss was studied. To minimize EF consumption, production allocation model for continuous equipment group was established, and the equipment operation adjustment strategy was studied when MF productivity deviating from’economic zone’. To maximize EF equilibrium degree, synergistic operation model for batch-type equipment group was built, and how output fluctuation of MF effects on EF equilibrium degree was pointed out.(3) Studying dynamic optimization of EF based on MF parameters and equipment status.According to the order of’node supply and demand, fixed user consumption, waste recovery and surplus buffer’, dynamic optimization of EF was studied from system level, using Eulerian method and Lagrangian method, and simulation analyses were carried out. Based on exergy analysis and specific energy consumption analysis theories, EF demand model was established, and the limit EF demand was summarized. Based on MF parameters and process control system, EF average model and dynamic compensation model were established, and the instantaneous EF generation, consumption and surplus of each node were discussed. Based on MF parameters and equipment status, demand-oriented EF dispatch model was built, and EF allocation among fixed users was studied with dynamic clustering analysis. Based on energy grade analysis theory, the concept of’equivalent energy grade difference’was proposed, and waste EF recovery model was established, then the best recovery mode of waste EF was analyzed. To maximize the recycling benefit, surplus EF buffer model was built, and the optimal dispatch of surplus EF between buffer equipment and buffer device was presented.(4) Establishing evaluation methods and indices of synergy of MF and EF and proposing the direction of furture technology development.The connotation of synergy of MF and EF was expounded. The order parameters of SMP were identified, and the synergy degree of MF and EF was defined, and then the evaluation method and indices to measure the synergy degree were set up. Also the direction of furture technology development is proposed and several suggestions of synergy of MF and EF were given in this work.(5) Developing optimization algorithm for solving mathematical models.In view of the requirement of real-time optimization and scheduling in production, new algorithms, targeting at solving difficult mathematical models, were developed in this work. By converting objective function to equivalent inequality through introducing variable, the optimization problem whose objective function contains discontinuous function Sgn was solved. By setting associated constraint and rapid exception enumeration, the span of decision variables was reduced. By introducing Euclidean distance to adjust edge elements, the computational accuracy of dynamic clustering analysis model was improved. And reduced state space algorithm was proposed to solve dynamic programming problems with state variables and decision variables of wide range, which greatly improves the calculation speed.