Simulation Optimization And Optimal Control On Spraying Ammonia Of SCR Flue Gas Denitrification

With the increased our country’s environmental protection policy requires,nitrogen oxides（NOx） emission in the flue gas of thermal power units have beenincorporated into the strict supervision. Therefore, how to develop high-effective,reliable and economic flue gas denitrification technology is an urgent affairs. Theselective catalytic reduction （SCR） flue gas denitrification technology has been usedwidely in coal-fired power plant to control NOx emissions, because of a lot ofadvantages, such as a high de-NOx rate （mostly up to90%）, high reliability technology,simple structure, small ammonia escaped rate and so on. Firstly, based on the SCRreaction mechanism, we could analyse the factors of affect denitrification. And then,established of SCR DeNOx system model and simulation to calculate the its flow field,we can provide a certain optimization method, how to design and arrange deflectors andrectifier grilles. While, for improving the accuracy of spraying ammonia, the controlsystem of ammonia injection applied dynamic neural network technology, so the controlsystem can improve the efficiency of denitrification to reduce the amount of ammoniaescaping. Three aspects were focuses to study on the thesis as follows:Firstly, the chemical micro-process model of SCR flue gas deNOx was constructed,the principle of surface chemical reaction and gaseous diffusion were applied to studythe microcosmic reaction process. There are a large number of chemical reactions, butplaying a dominant position in response is4NO+4NH₃+O₂→4N₂+6H₂O; Themicroscopic process contains the following three processes：they are surface chemicalreaction, inside mass transfer and outside mass transferï¼›By the microcosmic reactionshows that，on the certain condition，deNOx reaction rate has been effected of theconcentration of reactants and catalyst microporous surface area， and they areproportional to the relationship.Secondly, take a power plant600MW unit SCR DeNOx system as an example, weconstructed simulation methods and models that contains the flue gas flow field and theconcentration field on the reactor. The model was set boundary conditions and meshed.Through the several simulations analysis of SCR entrance, when deflectors andrectifiers grille were installation right ways, that would effectively improve the flowfield velocity uniformity and reduce the resistance of the system; By simulation analysisof AIG with different spray velocity, how to effect concentration field of the reactor inlet, the results show that when the case of a fixed number of nozzles, the nozzledivided into the edge region and the central region, respectively, using different injetspeed, can improve the degree of mixing of the flue gas and NH3. At the same time,through simulation of the SCR deNOx system under varying load condition, the resultsmeet the uniformity of flow field and concentration field.Finally, spraying ammonia control technology of SCR DeNOx process has beenoptimized, using a dynamic neural network to establish network model which was therelationship about the outlet of NOx concentration with inlet NOx concentration, theexport amount of ammonia, the flue gas temperature, unit load and so on. The minimumNOx emissions as a training signal, the model can achieve optimal control of ammoniainjection amount. Compared with the traditional program of PID, the result shows thatthe changed conditions and the flue gas temperature fluctuations, this program reducedSCR export of NOx emissions and ammonia escape, had a good adaptive capacity,saved the costs of denitrification.