Research And Application Of Energy Medium Optimization Scheduling Under Multi-Working Conditions In Iron And Steel Enterprises

In recent years,China ’s steel production ranks first in the world.As a pillar industry of the national economy,the steel industry accounts for a large proportion of China ’s total industrial energy consumption.There is still a certain gap between the energy utilization rate of the steel industry and the developed countries.In order to improve energy efficiency and reduce the operation cost of iron and steel enterprises.This paper mainly studies the energy planning optimization and energy scheduling optimization of multi-condition iron and steel enterprises,and reduces the operation cost of energy system of iron and steel enterprises.The main research contents of this paper are as follows :Energy system analysis and establishment of energy conversion equipment model.Firstly,according to the energy system structure of an iron and steel enterprise,the schematic diagram of the energy flow network of the iron and steel enterprise is given.Then,the production and consumption users of the main medium of the energy flow network and the use of each medium are introduced.Then,the operation unit of the energy system is analyzed and the mathematical model of the operation unit is established.Finally,the influence of different working conditions on the operation of the energy system is analyzed.Multi-condition energy plan optimization.Aiming at the production characteristics of steel production,such as long process,many energy media and disturbance of main process conditions,which makes the whole process energy plan difficult to configure,a deep deterministic strategy gradient algorithm with adaptive learning ability is proposed.Firstly,the energy balance constraint is established according to the energy balance mechanism of the whole process of steel production,and the material flow constraint and energy supply and demand constraint of the upstream and downstream processes in the actual production process are considered.Then,the learning framework of the deep deterministic policy gradient algorithm is constructed with the minimum operating cost of the energy system and the energy balance constraint of the whole process.In the solving process,the Gaussian noise with variance convergence and the penalty function of action overrun are introduced to improve the global optimization ability and convergence of the agent of the deep deterministic policy gradient algorithm,so that the agent can adaptively adjust and update the optimal strategy under the main process conditions.Finally,different working conditions of actual cases are simulated to verify the effectiveness of deep reinforcement learning algorithm in energy plan optimization.Multi-condition energy scheduling optimization.Aiming at the problem that it is difficult to search the optimal solution of multi-constrained and multi-variable energy scheduling model due to the uneconomic operation of equipment and the fluctuation of energy medium production and consumption caused by multiple working conditions of energy conversion equipment,an energy scheduling method based on DRL-IDE algorithm is proposed.Firstly,the method based on deep reinforcement learning is used to balance the influence caused by multiple working conditions of energy conversion equipment,so as to reduce the search range of the optimal solution of energy scheduling and the constraints of the objective function.Then,in solving the multi-constrained and multi-variable energy scheduling problem,the distance perturbation + chaotic equation is introduced to generate the initial population of the differential evolution algorithm,and the adaptive mutation strategy based on the variable search range is adopted for the mutation operation of the algorithm.In addition,heuristic rules are introduced in the optimal solution search process.Finally,the actual case of the enterprise is simulated to verify that the proposed method can solve the multi-condition energy scheduling problem and reduce the production cost.Energy optimization scheduling system design.In order to facilitate the management of multi-energy medium scheduling data and the analysis of operation results,an energy optimization scheduling system for iron and steel enterprises was developed.Firstly,according to the actual operation of iron and steel enterprises,the system software requirements and overall architecture are analyzed and designed,and then the implementation of system software front-end,back-end development tools and database is introduced.Finally,based on the research contents of the third and fourth chapters,the energy optimization scheduling system module is displayed.