Study On Energy Consumption Optimization Of Tissue Machine Drying Section Based On Improved Genetic Algorithm

With the gradual and leapfrog development of the world economy,green economy has become the core competitiveness of the traditional industry.As one of the ten pillar industries of our country,paper industry must firmly take the road of energy conservation,consumption reduction and green development.At present,the high energy consumption is still one of the key problems in paper industry.The steam consumption of drying section is more than 50% of the total papermaking process.Drying energy consumption mainly comes from two parts of dryer and ventilation system.The study shows that making full use of the waste heat of two steam and condensate is an effective means to effectively reduce energy consumption and reduce the cost of energy consumption in papermaking.Therefore,this paper focuses on the modeling and optimization of energy consumption in drying process,in the context of the two subsystems energy consumption of synergistic dryer and ventilation hood,the energy consumption model is established by module partition method,and the energy consumption is optimized by using the improved Dynamic Adaptive Genetic Algorithm(DAGA).This thesis takes the drying section of tissue machine production line in Baoding,Hebei as the research object,and the research process is funded by the Shaanxi science and technology co-ordination innovation project plan(2016KTCQ01-35)project.The main work is presented as follows.I.Establishment of Energy Consumption Model in Tissue Machine Drying SectionOn the basis of the technological process of the energy consumption synergy system in paper machine drying section,the drying unit is divided into five basic modules: dryer,steam hood,heat exchanger,heater and fan.Combined with the basic properties of various materials,the paper drying process is analyzed based on the basic heat and mass transfer principle,and the energy consumption model of tissue machine drying section is established.After verification,the deviation between the model and the actual one is less than 10%.The influence factors of the energy consumption of the two subsystems are analyzed,which lays the foundation for the optimization of energy consumption.II.Genetic Algorithm and its ImprovementThis paper focuses on the Genetic Algorithms(GA)elements and its implementation method.Aiming at the premature phenomenon of Simple Genetic Algorithems(SGA),the improvement strategy is put forward,the index of evaluating the degree of the population precocious maturity is introduced,so as to design dynamic adaptive genetic strategy,two standard test functions are selected to compare the performance of the algorithms,the results show that DAGA can overcome the population premature phenomenon,effectively improve the search accuracy and search speed of SGA.III.Optimization of Energy Consumption in Drying Section Based on DAGAThe performance evaluation index and calculation method of tissue machine drying section are put forward.Based on the energy consumption model of the drying section and using the optimization theory as a tool,the energy consumption optimization model of tissue machine drying section is established,the objective is to minimize the consumption of steam and the power consumption in the drying section,the energy consumption is optimized by DAGA,the setting value of operating parameters when the energy consumption is lowest under the current working condition is obtained,that are the steam inlet pressure and dryer heater,the dryer inlet pressure,the heater inlet pressure,the air supply temperature,the air supply volume,the exhaust air temperature and the exhaust air volume.After optimization,the steam consumption of tons of paper is reduced by 4.9%,the steam efficiency is increased by 4.3%,and the energy conservation effect is obvious.IV.Realization of Energy Consumption Optimization Control System in Drying SectionAccording to the main points of control system for energy consumption optimization of tissue machine drying section,the corresponding control scheme is designed.Taking SIEMENS S7-300 PLC as development platform,the system design,the hardware configuration and the application software development is completed and the distributed control system(DCS)is designed.The optimization control system of drying section energy consumption has been applied in the production line of a tissue machine in Baoding,Hebei.After a period of operation,the results show that the average steam consumption of drying section is reduced from 2.258 T to 2.152 T,saving steam 0.106 T,about 4.7%,and the power consumption of the ton paper is reduced from 262.2 kw/h to 226.6 kw/h,which saves electricity 35.6 kw/h and 13.6%.Excellent control effect has been received,which can effectively reduce the energy consumption of the system.While saving energy and protecting environment,it also reduces production cost and brings notable economic benefits for papermaking enterprises.