Evaluation,Diagnosis and Optimization Method for Energy Efficiency of Ethylene Production Process

Author:Gong Shi Zuo

Supervisor:shao cheng


Degree Year:2019





As the basic raw material supplier of chemical production and high energy-consuming process,ethylene production is the foundation of chemical industry and the focus of energy conservation and consumption reduction.The general high energy consumption and low energy utilization rate in ethylene production have always been the research hotspots in control and other related fields.Researching the energy efficiency evlaution,diagnosis and optimization methods for ethylene production process are the key technologies to understand the production level,find energy saving potential,improve energy management and increase production.However,there are still many shortcomings in current researches on the energy efficiency analysis and optimization of ethylene production process.Therefore,this paper takes the evaluation,diagnosis and optimization of energy efficiency for ethylene production process as research topic,and carries out the research combining the production technology and actual requirements,and proposes a series of effective energy efficiency analysis and optimization methods for ethylene production,which had been applied to practical enterprises and achieved good effects.The main work of this paper is as follows:In terms of the complicated production technology,the diversity of cracking feedstocks and energy types in the ethylene production process could lead to multi-granular problems of energy efficiency evaluation and diagnosis,where energy efficiency indictors have features of multiple time scales and media.According to the ethylene production technology and the characteristics of energy consumption and conversion process,from the three levels of system,process and equipment,as well as the dynamic monitoring information of energy,material and product flows,a multi-granularity energy efficiency indicator system is established for ethylene production process,which has laid the foundation for a scientific assessment of energy efficiency from the key energy-consumption devices to the entire ethylene production process.The changes of energy consumption and yield caused by the fluctuation of feedstocks,load and parameters in production could lead to the difficulty of reasonable energy efficiency evaluation of ethylene production.Therefore,a multi-model energy efficiency evaluation method with respect to condition classification is proposed.The clustering algorithm is used to identify the working conditions of ethylene production.The factor analysis method is used to screen the input indicators of the energy efficiency evaluation model,and energy efficiency evaluation models for multiple working conditions are established based on DEA model.Then the energy efficiency of ethylene production can be evaluated more reasonably and the improvement scheme for high-efficient energy inputs under different working conditions can be provided.Comparing to traditional evaluation methods,the proposed evaluation method can analyze energy efficiency level more scientifically and comprehensively.The changes of operating conditions of the inner production process and key equipment could lead to the changes of overall energy efficiency,so the deep diagnosis for the cause of changes of energy efficiency is required.Therefore,a distributed energy efficiency diagnosis scheme combining the proposed multi-granularity energy efficiency indicator system and different diagnosis cycles is proposed.The energy efficiency diagnosis boundaries of the ethylene production system layer,process layer and equipment layer are determined based on the change of energy flow in the production process.Distributed energy efficiency diagnosis models that consider the internal link correlation of the ethylene production process are established,and the diagnosis time at different production levels is determined combining with the actual production situation.Comparing to the traditional diagnosis schemes,the proposed diagnosis scheme can diagnose the energy efficiency layer by layer,and analyze the specific reasons of low energy efficiency more deeply.On the basis of dynamic monitoring and evaluation of energy efficiency in ethylene production process as far as possible,scientific analysis and diagnosis can be achieved,which can create conditions for energy efficiency improvement and energy optimization management.Aiming at the energy efficiency optimization of the ethylene production process under multi-working conditions,a multi-condition energy efficiency optimization scheme based on three-level production structure is proposed.Due to the multiple working conditions and multi-level structure of ethylene production process,it is unreasonable to improve the energy efficiency of the whole production by a single model.Therefore,the dynamic description models of ethylene production system layer,process layer and equipment layer based on data-driven method are established as optimization constraints.Then,for different working conditions,multi-objective energy efficiency optimization models are established and solved by multi-objective particle swarm optimization algorithm,incorporating a novel knowledge base of optimal solutions for working conditions to guide the oriented local area search.The optimization results show that based on the proposed energy efficiency optimization scheme in this paper,energy efficiency of ethylene production under different working conditions has been improved significantly.In order to solve the problem of high energy consumption and low energy efficiency of the cracking process in ethylene production,comprehensive means of feedstock proportions optimization and energy management are adopted,and a coordination optimization of energy and materials for the cracking process is proposed to realize the phase-by-stage optimization of the production feedstock proportions and energy materials.Firstly,the prediction and optimization models of economic indicators for the ethylene production based on feedstock proportions are established,and the optimal feedstock proportions under different market demand conditions are determined based on the accurate prediction.Secondly,the energy and material coordination optimization models for cracking furnaces taking fuel-feedstock ratio as optimization objective are established to optimize fuel gas and feedstocks for different furnaces and achieve the goal of energy saving and consumption reduction throughout the whole cracking process.The optimization results show that synthetical energy consumption of the cracking process has been reduced effectively.