Research On Collaborative Online Evaluation Method Of Pollution And Energy Consumption Based On Artificial Intelligence

The overwhelming burden of environmental pollution and energy consumption is currently the main bottleneck restricting the development of China's national economy,and the cooperative coupling mechanism of pollution emissions and comprehensive energy efficiency of the system is the effective way to break through the overwhelming bottleneck of environmental pollution and resource energy consumption.Based on this important social demand and engineering background,this paper constructs an intelligent online soft prediction model for pollution emission and comprehensive energy efficiency of desulfurization system based on ASPEN PLUS mechanism modeling simulation and intelligent deep self-learning modeling based on online sample data of support vector machine.The synergy coupling correlation theory was researched and constructed among coal quality parameters-boiler load parameters-process control parameters-SO2 pollution emissions-system comprehensive energy efficiency,its synergy coupling mechanism was interpreted.In this way,an intelligent online real-time soft prediction method for pollution emission of desulfurization system and comprehensive energy efficiency of the system was constructed,and a collaborative evaluation method for pollution emission and comprehensive energy efficiency of the system was established,which laid a theoretical foundation for the establishment of collaborative evaluation standards for pollution emission and comprehensive energy efficiency of high-energy equipment in China.The main research results are as follows:1.Based on ASPEN PLUS mechanism modeling simulation and intelligent deep self-learning modeling based on support vector machine online sample data,an intelligent real-time online soft prediction model of desulfurization system pollution emissions and system comprehensive energy efficiency indicators is constructed,which realized accurately predicting SO2 pollution emissions and the system's comprehensive energy efficiency indicators by means of online operation data of coal quality parameters,furnace load parameters and key process control parameters based on the central control system of the desulfurization system.The comparative analysis between the predicted values and real-time monitoring values show that the maximum error is within 10%;2.Based on the research and construction of the online real-time soft sensor prediction model of sulfur pollution in the sulfur system,under the condition of equivalent constraint control of SO2 emission index at the exit,the cooperative coupling variation law of maximum treatable inlet flue gas flow,maximum treatable inlet flue gas SO2 concentration and key adjustable process parameters is studied.3.An innovation method was presented by the bridge of collaborative coupling change combination between the maximum treatable inlet flue gas flow,the maximum treatable inlet flue gas SO2 concentration with the key adjustable process parameters under the condition of equivalent constraint control of SO2 emission index at the desulfurization tower outlet.Which realized the research of the collaborative coupling theory among the coal quality parameters-boiler load parameters-process control parameters-export SO2 pollution emission indicators-system comprehensive energy efficiency indicators,its synergistic coupling mechanism was explained,and on this basis,the collaborative evaluation index system and evaluation method of pollution emission and comprehensive energy efficiency of desulfurization tower are established.