Study On Operating Optimization Of Coal-fired Unit Ultra Low Emission System

Coal is the primary energy in China.Many kinds of air pollutants such as sulfur dioxide(SO2),nitrogen oxides(NOx)and particulate matter(PM)are generated during the combustion of coal,which have a negative impact on the atmosphere.In China,coal consumption in the thermal power industry accounts for over 40%of the total coal consumption and is the main source of SO2,NOx and PM emissions.The Chinese government attaches more and more importance to environmental protection.In recent years,it has continuously tightened the standards for the discharge of air pollutants from thermal power plants and actively promoted the transformation of ultra-low emissions of coal-fired power plants.At present,the ultra low emission system is mostly controlled manually.The target value of parameters and the control of facilities are adjusted according to experience.It may cause some problems.On the one hand,excessive materials may be added by manual operation,leading to the raise of cost.On the other hand,there is the possibility of excessive discharge of air pollutants due to improper operation.In order to solve these problems,it is necessary to set the operating parameters within a reasonable range according to scientific guidance,save the energy and material consumption in the pollutant removal process,make the ultra low emission system run in a status of low-cost and high-efficiency.In this paper,studies are focused on the main facilities of ultra low emission system which include selective catalytic reduction device(SCR),electrostatic precipitator(ESP),wet flue gas desulfurization system(WFGD)and wet electrostatic precipitator(WESP).The main contents of the studies are listed as follows:1.Based on the main equipment and structure of SCR,ESP,WFGD and WESP,influence factors were analyzed.Then,the operating cost models of each system were established according to energy and material consumption.2.The operating parameters of WFGD system were optimized using an improved association rules algorithm.The potential correlation between operating parameters and SO2 outlet concentration was analyzed,based on which the optimal operating condition library of WFGD system was established.The results show that SO2 emissions were reduced by 31%on average by adjusting the operating parameters according to the optimal operating condition library,which means that the improved association rules algorithm can effectively reduce SO2 emissions.3.A PM emissions forecast model was established by means of RBF neural network to set up the relationship between the operating parameters and PM emissions,based on which differential evolution algorithm was applied to optimize the operating parameters of ESP system aiming at minimizing the operating cost of the ESP system.The results show that the operating cost was reduced by 5.39%after the optimization.4.The collaborative removal and multivariable coupling in ultra low emission system were studied,based on which the frame of optimization of ultra low emission system was proposed.Aiming at minimizing the total operating cost of ultra low emission system,the optimization based on particle swarm optimization and the collaborative optimization frame was applied to solve the problem with multiple constraints.Through the experiment,the two optimization methods can effectively reduce the operating cost of ultra low emission system.In contrast,particle swarm optimization algorithm has a higher efficiency of analysis while the collaborative optimization has a better search ability.The results show that the optimal cost of ultra low emission system varies with the operation conditions.It decreases with the increase of boiler load,and increases with the raise of pollutant concentration.