Energy-saving Optimization Of Methanol Four-column Distillation Based On BP Neural Network And Aspen Plus

Under the background of the today's dwindling oil resources,methanol as the most important products of coal chemical industry and the new fuel energy,is widely used in organic synthesis,paint,medical and fuel industry,plays an important role in today's global chemical market.So the potential of methanol is huge.However,at present,the concentration of crude methanol synthesized in industry is generally not up to the requirement,so it is necessary to refine crude methanol.Methanol distillation process accounts for about 20%of total energy consumption of methanol production.Therefore,it is of great practical significance to study the methanol distillation process system,and to reduce the energy consumption of methanol distillation process by reasonable design and optimization.This subject is based on the actual operation of a chemical plant in the four towers methanol distillation system,studied in the chemical simulation method to establish the correlation model with using software ASPEN PLUS.Through the study of the system of classification based on the dynamic programming principle,to reduce the dimension of system optimization and the computational complexity.Analysis of the operation of the system parameters to get the mathematical description of the optimization problem.Establish the model of optimization algorithm with using ASPEN PLUS and BP neural network method.The main contents of this project mainly include:(1)The model of methanol distillation system was established with using the chemical simulation software ASPEN PLUS,and the feasibility analysis was carried out.It is proved that to establish the model is valid and feasible by using ASPEN PLUS.(2)A method is proposed to decompose the system which is based on the principle of optimality.And the four-towers methanol distillation system is decomposed into a distillation column,the pressurized distillation tower and the atmospheric distillation column,methanol recovery tower 3 subsystem.You can get the optimal overall system in order to optimize the every subsystem.By this method,the system can be modeled and optimized to reduce the dimension of the system and the complexity of the calculation.At the same time,the corresponding control variables and objective functions can be changed according to the actual situation,and the optimization operation of distillation is transformed into a mathematical problem.(3)the four-towers methanol distillation system was optimized by using the method based on ASPEN PLUS and BP neural network,with the minimum energy consumption and the products quality was satisfied.The optimization results is the energy consumption reduced by 10.4%.It shows that this optimization method is feasible and can provide experience and reference for the optimization of the actual industrial production.