Optimization Of Desulfurization Control System Of Ultra Supercritical Unit Based On Model Predictive Control

In recent years,environmental pollution problems have become increasingly frequent.As a typical high-energy-consumption and high-pollution production enterprise,coal-fired power plants emit a large amount of pollutants such as sulfur dioxide,which causes serious harm to the atmospheric environment and human health.In order to solve the contradiction between the growing power demand and ecological environmental protection in China,in 2014,China officially introduced a new standard for the emission of atmospheric pollutants from thermal power plants.The major power generation groups actively responded to national policies and carried out technological transformation of ultra-clean emissions.Therefore,how to make the power plant desulfurization system stable,efficient and economical has become a research hotspot in the field of control science and energy and environmental protection.At present,Super-Net emissions have been gradually realized in thermal power units.Based on the in-depth analysis of the main technology of limestone-gypsum Wet Flue Gas Desulfurization(WFGD)for ultra-supercritical units,and in view of the existing problems in the current desulfurization control system,this paper has carried out in-depth research based on fuzzy control,predictive control and other algorithms,mainly including the following four parts:1.Investigate and analyze the desulfurization operation process of coal-fired power plants.The system configuration including the whole process,the main chemical reactions,emission standards and by-product treatments were introduced and explained,which provided a theoretical basis for the follow-up work.2.Taking the 1000MW ultra-supercritical unit of Jurong Power Plant as the research object,collecting and processing the historical data of desulfurization operation,and establishing the mathematical model of the desulfurization absorption tower by the least squares method.It is obtained through the plant-level monitoring system,and the data is pre-processed by scientific methods to identify the mathematical model of the desulfurization absorption tower.The six core parameters in the running process are selected to fonn the model structure of 3 input and 3 output,and the correctness of the model is verified,and the research basis is provided for the subsequent experiments.3.Through the analysis of the difficult and dynamic characteristics of the desulfurization absorption tower control system,the fuzzy control strategy is studied and introduced into the traditional PID control.The main loop adjusts the three control parameters of the PID in real time through the fuzzy controller.The experiment.The results show that the fuzzy PID control makes the system obtain good dynamic and static characteristics.4.Although the improved PID algorithm is introduced,due to the limitations of PID control itself and the limited adaptive ability,the dynamic matrix control algorithm in model predictive control is introduced.The mathematical model of the absorption tower is loaded on the constructed platform.Through experiments,the parameters of the error matrix and control matrix of the dynamic matrix control are adjusted.The size makes the system globally optimal.The results show that the desulfurization control system based on model predictive control has obvious improvement on the ability to follow the load change,and the important operating parameter curve is gentle,which improves the stability and economy of the system operation.The robustness of the control system is greatly improved,and the equipment is reduced.The number of starts and stops reduces the workload of the professional personnel of desulfurization and improves the automation and operation efficiency of the desulfurization system.