Energy Efficiency Diagnosis And Optimization Of Refinery Atmospheric And Vacuum Unit

The oil refining industry is a pillar industry of China's energy and economic development and plays a very important role in providing chemical raw materials and fuel oil.With the continuous increase in energy consumption,there is a situation that reserves of recoverable resources are low in crude oil in China.This forces oil refining companies to pay close attention to energy conservation and consumption reduction and improve energy efficiency to enhance overall competitiveness.Some companies only focus on the optimization and upgrading of individual parts or independent devices to save energy and reduce consumption,but the economic costs are large and there is no significant effect on improving energy efficiency.Atmospheric and decompression equipment is the largest energy-consuming device for refineries.Its energy efficiency level reflects the utilization efficiency of crude oil and energy and directly affects the economic efficiency of enterprises.Therefore,assessing and diagnosing its energy efficiency,identifying causes and implementing optimized operations are of great significance to the energy efficiency of the oil refining industry.Atmospheric and decompression equipment is a non-linear multivariable object with a complex internal mechanism.Based on the national 863 project “Energy efficiency monitoring,assessment and optimization control technology and system for petrochemical industry”,this paper selects the key index pull-out rate of the atmospheric and vacuum unit,and carries out energy efficiency assessment,diagnosis and modeling optimization research.The energy efficiency management platform is designed and developed to achieve efficient energy management.The research work of this paper is as follows:(1)The process of refining is introduced in detail.According to the energy consumption ratio,the energy consumption characteristics of atmospheric and vacuum equipment are analyzed.The equipment is divided into three levels according to different granularity and evaluation angle: equipment level,process level,system level,and the three-level energy efficiency index system is established.The extraction rate index of atmospheric and vacuum unit which can reflect the energy efficiency level of the system is selected and the main influencing factors are analyzed.(2)The operating state of energy efficiency index of atmospheric and vacuum equipment was evaluated and diagnosed.The main causes of low pullout rate are: abnormal temperature of atmospheric pressure furnace,unbalanced hydraulic pressure of atmospheric tower,abnormal temperature of vacuum furnace and unbalanced temperature and pressure of the vacuum tower.In order to improve the accuracy of the diagnostic model,the refining process is divided into two working conditions because different crude oil processing capacity will have a great effect on the pull-out rate of the unit.Based on the production design value of a refinery,energy efficiency diagnostics were performed on data with total extraction rates below the baseline values under both conditions.A multi-category energy efficiency diagnosis model for dual conditions based on particle swarm optimization support vector machine was established.Through the simulation of actual production data,it is verified that the model can accurately and effectively diagnose and identify the energy efficiency index,and judge the reason of low energy efficiency.Compared with the support vector machine diagnosis model,the diagnosis accuracy of the model is higher.(3)To solve the problem of energy efficiency optimization in atmospheric and vacuum devices,a soft-sensor model of pull-out rate based on the least squares support vector machine is established to accurately predict the yield of the device.With the maximum pull-out rate as the optimization goal,the particle swarm optimization algorithm is used to optimize the temperature and vacuum degree of the top of the vacuum tower,and an energy efficiency optimization model is established.Finally,the energy efficiency level is significantly improved.(4)From the perspective of energy efficiency management,an energy efficiency management platform for oil refinery atmospheric and vacuum units is developed.It realizes the real-time monitoring and energy efficiency management of oil refining production process,integrates the energy efficiency diagnosis and optimization module into the platform,helps enterprises to understand the energy efficiency status in real time,detects anomalies online in time to regulate energy input,and guides actual production.